├── .gitmodules ├── 3rd_party └── SelectiveSearchCodeIJCV │ ├── 000015.jpg │ ├── BlobAverageBestOverlap.m │ ├── BlobBestOverlap.m │ ├── BlobStruct2HierarchicalGrouping.p │ ├── BlobStructColourHist.p │ ├── BlobStructTextureHist.p │ ├── BoxAverageBestOverlap.m │ ├── ChangeEdges.p │ ├── Dependencies │ ├── Blob2Image.p │ ├── Blob2Vector.p │ ├── BlobAddSizes.p │ ├── BlobAddTextureHists.p │ ├── Blobs2Boxes.p │ ├── BoxBestOverlap.m │ ├── BoxIntersection.m │ ├── BoxRemoveDuplicates.m │ ├── BoxSize.m │ ├── BoxUnion.m │ ├── CountVisualWordsIndex.m │ ├── FelzenSegment │ │ ├── COPYING │ │ ├── Makefile │ │ ├── README │ │ ├── convolve.h │ │ ├── disjoint-set.h │ │ ├── filter.h │ │ ├── image.h │ │ ├── imconv.h │ │ ├── imutil.h │ │ ├── mexFelzenSegmentIndex.cpp │ │ ├── misc.h │ │ ├── pnmfile.h │ │ ├── segment-graph.h │ │ ├── segment-image.h │ │ └── segment.cpp │ ├── FilterBoxesWidth.m │ ├── GetPascalOverlap.m │ ├── Image2ColourSpace.p │ ├── Image2OrientedGradients.p │ ├── NormalizeArray.m │ ├── NormalizeRows.m │ ├── PascalOverlap.m │ ├── Rgb2C.p │ ├── Rgb2Ooo.p │ ├── Rgb2Rg.p │ ├── Rgb2Rgi.p │ ├── SegmentIndices2Blobs.p │ ├── ShowBlobs.m │ ├── ShowImageCell.m │ ├── ShowRectsWithinImage.m │ ├── Vector2Hist.p │ ├── anigaussm │ │ ├── anigauss.c │ │ ├── anigauss.m │ │ └── anigauss_mex.c │ ├── gaussianFilter.p │ └── mexCountWordsIndex.cpp │ ├── GroundTruthVOC2007test.mat │ ├── Image2HierarchicalGrouping.m │ ├── License.txt │ ├── MergeBlobs.p │ ├── RecreateBlobHierarchy.m │ ├── RecreateBlobHierarchyIndIm.m │ ├── SSSimBoxFill.p │ ├── SSSimBoxFillOrig.p │ ├── SSSimBoxFillOrigSize.p │ ├── SSSimBoxFillSize.p │ ├── SSSimColour.p │ ├── SSSimColourSize.p │ ├── SSSimColourTextureSizeFill.p │ ├── SSSimColourTextureSizeFillOrig.p │ ├── SSSimSize.m │ ├── SSSimTexture.p │ ├── SSSimTextureSize.p │ ├── SSSimTextureSizeFill.p │ ├── anigauss.mexa64 │ ├── demo.m │ ├── demoPascal2007.m │ ├── mexCountWordsIndex.mexa64 │ └── mexFelzenSegmentIndex.mexa64 ├── ImageNet3D ├── .gitignore ├── VOCap.m ├── VOCevaldet.m ├── VOCevaldet_ignore.m ├── VOCevaldetview.m ├── edgeboxes_ImageNet3D.m ├── globals.m ├── mcg_ImageNet3D.m ├── rotation_matrix.m ├── selective_search_ImageNet3D.m ├── selective_search_boxes.m ├── show_results.m └── test.m ├── KITTI ├── VOCap.m ├── boxoverlap.m ├── compute_3d_points.m ├── compute_matching_scores_segmentation.cc ├── compute_recall.m ├── compute_recall_precision_aos.m ├── compute_recall_precision_aos_3d.m ├── compute_recall_precision_aos_3d_box_only.m ├── compute_recall_precision_aos_box.m ├── compute_recall_simple.m ├── edgeboxes_KITTI.m ├── evaluate_object.cpp ├── exemplar_3d_detections_light.m ├── exemplar_3d_detections_light_box.m ├── exemplar_compute_aps_multiclass.m ├── exemplar_compute_segmentation_overlap.m ├── exemplar_compute_segmentation_overlap_box.m ├── exemplar_display_result_kitti.m ├── exemplar_display_result_kitti_3d.m ├── exemplar_display_result_kitti_bbox.m ├── exemplar_globals.m ├── globals.m ├── kitti_ids_new.mat ├── kitti_ids_val.txt ├── load_off_file.m ├── mcg_KITTI.m ├── nms_new.m ├── selective_search_KITTI.m ├── selective_search_boxes.m ├── selective_search_demo.m ├── write_dets_to_files.m └── write_ids_to_files.m ├── LICENSE ├── MOT ├── VOCap.m ├── boxoverlap.m ├── compute_recall.m ├── compute_recall_precision.m ├── globals.m ├── selective_search_MOT.m ├── selective_search_boxes.m ├── show_detections.m └── show_region_proposals.m ├── NISSAN ├── exemplar_display_result_nissan.m └── exemplar_globals.m ├── NTHU ├── exemplar_display_result_nthu.m └── exemplar_globals.m ├── PASCAL ├── boxoverlap.m ├── compute_recall.m ├── globals.m └── pascal_init.m ├── PASCAL3D ├── boxoverlap.m ├── compute_ap_avp.m ├── compute_recall.m ├── compute_recall_precision_accuracy.m ├── compute_statistics.m ├── exemplar_display_result_pascal3d.m ├── globals.m └── pascal_init.m ├── README.md └── fast-rcnn ├── .gitignore ├── LICENSE ├── README.md ├── data ├── .gitignore ├── KITTI │ ├── test.txt │ ├── train.txt │ ├── trainval.txt │ ├── val.txt │ └── voxel_exemplars.zip ├── NTHU │ ├── mapping.txt │ └── region_proposals │ │ └── RPN_6k8k │ │ └── .gitignore ├── PASCAL3D │ └── voxel_exemplars.zip ├── README.md ├── demo │ ├── 000004.jpg │ ├── 000004_boxes.mat │ ├── 001551.jpg │ └── 001551_boxes.mat ├── pylintrc └── scripts │ ├── fetch_3dvp_rcnn_models.sh │ ├── fetch_fast_rcnn_models.sh │ ├── fetch_imagenet_models.sh │ └── fetch_selective_search_data.sh ├── experiments ├── cfgs │ ├── imagenet3d_rcnn_original_edge_boxes.yml │ ├── imagenet3d_rcnn_original_mcg.yml │ ├── imagenet3d_rcnn_original_rpn.yml │ ├── imagenet3d_rcnn_original_rpn_vgg16.yml │ ├── imagenet3d_rcnn_original_selective_search.yml │ ├── imagenet3d_rcnn_view_edge_boxes.yml │ ├── imagenet3d_rcnn_view_mcg.yml │ ├── imagenet3d_rcnn_view_rpn.yml │ ├── imagenet3d_rcnn_view_rpn_vgg16.yml │ ├── imagenet3d_rcnn_view_selective_search.yml │ ├── imagenet3d_rpn_msr.yml │ ├── kitti_rcnn.yml │ ├── kitti_rcnn_2d_multiscale.yml │ ├── kitti_rcnn_fix.yml │ ├── kitti_rcnn_googlenet.yml │ ├── kitti_rcnn_msr.yml │ ├── kitti_rcnn_msr_fix.yml │ ├── kitti_rcnn_msr_multiscale.yml │ ├── kitti_rcnn_msr_multiscale_fix.yml │ ├── kitti_rcnn_multiscale.yml │ ├── kitti_rcnn_multiscale_6k8k.yml │ ├── kitti_rcnn_noextra.yml │ ├── kitti_rcnn_original.yml │ ├── kitti_rcnn_original_msr.yml │ ├── kitti_rcnn_original_multiscale.yml │ ├── kitti_rcnn_vgg16_multiscale_6k8k.yml │ ├── kitti_rpn.yml │ ├── kitti_rpn_2d.yml │ ├── kitti_rpn_fix.yml │ ├── kitti_rpn_msr.yml │ ├── kitti_tracking_multiscale_6k8k.yml │ ├── kitti_tracking_multiscale_train.yml │ ├── kitti_tracking_multiscale_vgg16.yml │ ├── kitti_tracking_rpn.yml │ ├── mot_rpn.yml │ ├── mot_tracking_multiscale.yml │ ├── mot_tracking_multiscale_vgg16.yml │ ├── nissan_multiscale_6k8k.yml │ ├── nissan_rpn.yml │ ├── nthu_multiscale_6k8k.yml │ ├── nthu_rpn.yml │ ├── pascal3d_rcnn.yml │ ├── pascal3d_rcnn_multiscale.yml │ ├── pascal3d_rcnn_original.yml │ ├── pascal3d_rcnn_pose.yml │ ├── pascal3d_rcnn_pose_multiscale.yml │ ├── pascal3d_rpn.yml │ ├── pascal3d_rpn_msr_vgg16.yml │ ├── pascal3d_rpn_vgg16.yml │ ├── pascal_rcnn.yml │ ├── pascal_rcnn_original.yml │ ├── pascal_rcnn_original_multiscale.yml │ ├── pascal_rpn.yml │ ├── pascal_rpn_cls_vgg16.yml │ └── pascal_rpn_vgg16.yml ├── logs │ └── .gitignore └── scripts │ ├── imagenet3d_caffenet_rcnn_original_edge_boxes.sh │ ├── imagenet3d_caffenet_rcnn_original_mcg.sh │ ├── imagenet3d_caffenet_rcnn_original_rpn.sh │ ├── imagenet3d_caffenet_rcnn_original_selective_search.sh │ ├── imagenet3d_caffenet_rcnn_view_edge_boxes.sh │ ├── imagenet3d_caffenet_rcnn_view_mcg.sh │ ├── imagenet3d_caffenet_rcnn_view_rpn.sh │ ├── imagenet3d_caffenet_rcnn_view_selective_search.sh │ ├── imagenet3d_caffenet_rcnn_view_selective_search_debug.sh │ ├── imagenet3d_caffenet_rpn_msr_test_1.sh │ ├── imagenet3d_caffenet_rpn_msr_test_2.sh │ ├── imagenet3d_caffenet_rpn_msr_test_train.sh │ ├── imagenet3d_caffenet_rpn_msr_test_val.sh │ ├── imagenet3d_caffenet_rpn_msr_train.sh │ ├── imagenet3d_vgg16_rcnn_original_edge_boxes.sh │ ├── imagenet3d_vgg16_rcnn_original_mcg.sh │ ├── imagenet3d_vgg16_rcnn_original_rpn.sh │ ├── imagenet3d_vgg16_rcnn_original_selective_search.sh │ ├── imagenet3d_vgg16_rcnn_view_edge_boxes.sh │ ├── imagenet3d_vgg16_rcnn_view_mcg.sh │ ├── imagenet3d_vgg16_rcnn_view_rpn.sh │ ├── imagenet3d_vgg16_rcnn_view_selective_search.sh │ ├── imagenet3d_vgg16_rpn_msr_test_1.sh │ ├── imagenet3d_vgg16_rpn_msr_test_2.sh │ ├── imagenet3d_vgg16_rpn_msr_test_train.sh │ ├── imagenet3d_vgg16_rpn_msr_test_val.sh │ ├── imagenet3d_vgg16_rpn_msr_train.sh │ ├── kitti_test_caffenet_rcnn_multiscale.sh │ ├── kitti_test_caffenet_rcnn_multiscale_6k8k.sh │ ├── kitti_test_caffenet_rcnn_original_msr.sh │ ├── kitti_test_caffenet_rpn.sh │ ├── kitti_test_caffenet_rpn_6k8k.sh │ ├── kitti_test_caffenet_rpn_msr_6k8k.sh │ ├── kitti_test_googlenet_rcnn.sh │ ├── kitti_test_vgg16_rcnn_multiscale_6k8k.sh │ ├── kitti_tracking.sh │ ├── kitti_tracking_test.sh │ ├── kitti_tracking_test_caffenet_rcnn_multiscale.sh │ ├── kitti_tracking_test_caffenet_rpn.sh │ ├── kitti_tracking_test_caffenet_rpn_test.sh │ ├── kitti_tracking_test_vgg16_rcnn_multiscale.sh │ ├── kitti_tracking_val_caffenet_rcnn_multiscale.sh │ ├── kitti_tracking_val_caffenet_rpn.sh │ ├── kitti_tracking_val_caffenet_rpn_test.sh │ ├── kitti_val_caffenet_rcnn.sh │ ├── kitti_val_caffenet_rcnn_2d_multiscale.sh │ ├── kitti_val_caffenet_rcnn_fix.sh │ ├── kitti_val_caffenet_rcnn_msr.sh │ ├── kitti_val_caffenet_rcnn_msr_fix.sh │ ├── kitti_val_caffenet_rcnn_msr_multiscale.sh │ ├── kitti_val_caffenet_rcnn_msr_multiscale_fix.sh │ ├── kitti_val_caffenet_rcnn_multiscale.sh │ ├── kitti_val_caffenet_rcnn_noextra.sh │ ├── kitti_val_caffenet_rcnn_original.sh │ ├── kitti_val_caffenet_rcnn_original_msr.sh │ ├── kitti_val_caffenet_rcnn_original_multiscale.sh │ ├── kitti_val_caffenet_rpn.sh │ ├── kitti_val_caffenet_rpn_2d.sh │ ├── kitti_val_caffenet_rpn_fix.sh │ ├── kitti_val_caffenet_rpn_msr.sh │ ├── kitti_val_caffenet_rpn_msr_fix.sh │ ├── kitti_val_caffenet_rpn_msr_multiscale_fix.sh │ ├── kitti_val_googlenet_rcnn.sh │ ├── mot_tracking_caffenet_rpn.sh │ ├── mot_tracking_caffenet_rpn_test.sh │ ├── mot_tracking_test_vgg16_rcnn_multiscale.sh │ ├── mot_tracking_val_caffenet_rcnn_multiscale.sh │ ├── nissan_caffenet_combined.sh │ ├── nissan_caffenet_rcnn_multiscale_6k8k.sh │ ├── nissan_caffenet_rpn_6k8k.sh │ ├── nthu_caffenet_rcnn_multiscale_6k8k.sh │ ├── nthu_caffenet_rpn_6k8k.sh │ ├── pascal2007_caffenet_rcnn.sh │ ├── pascal2007_caffenet_rcnn_original.sh │ ├── pascal2007_caffenet_rpn.sh │ ├── pascal2007_vgg16_rcnn_original.sh │ ├── pascal2007_vgg16_rcnn_original_multiscale.sh │ ├── pascal2007_vgg16_rpn.sh │ ├── pascal2007_vgg16_rpn_6k8k.sh │ ├── pascal2007_vgg16_rpn_cls.sh │ ├── pascal3d_vgg16_rcnn.sh │ ├── pascal3d_vgg16_rcnn_multiscale.sh │ ├── pascal3d_vgg16_rcnn_original.sh │ ├── pascal3d_vgg16_rcnn_pose.sh │ ├── pascal3d_vgg16_rcnn_pose_multiscale.sh │ ├── pascal3d_vgg16_rpn.sh │ ├── pascal3d_vgg16_rpn_6k8k.sh │ └── pascal3d_vgg16_rpn_msr.sh ├── lib ├── Makefile ├── datasets │ ├── VOCdevkit-matlab-wrapper │ │ ├── get_voc_opts.m │ │ ├── voc_eval.m │ │ └── xVOCap.m │ ├── __init__.py │ ├── factory.py │ ├── imagenet3d.py │ ├── imdb.py │ ├── kitti.py │ ├── kitti_tracking.py │ ├── mot_tracking.py │ ├── nissan.py │ ├── nthu.py │ ├── pascal3d.py │ └── pascal_voc.py ├── fast_rcnn │ ├── __init__.py │ ├── bbox_transform.py │ ├── config.py │ ├── nms_wrapper.py │ ├── test.py │ └── train.py ├── gt_data_layer │ ├── __init__.py │ ├── layer.py │ ├── minibatch.py │ └── roidb.py ├── nms │ ├── .gitignore │ ├── __init__.py │ ├── cpu_nms.pyx │ ├── gpu_nms.hpp │ ├── gpu_nms.pyx │ ├── nms_kernel.cu │ └── py_cpu_nms.py ├── roi_data_layer │ ├── __init__.py │ ├── layer.py │ ├── minibatch.py │ └── roidb.py ├── roi_generating_layer │ ├── __init__.py │ └── layer.py ├── roi_patch_layer │ ├── __init__.py │ ├── layer.py │ ├── minibatch.py │ └── roidb.py ├── roi_testing_layer │ ├── __init__.py │ └── layer.py ├── roi_visualizing_layer │ ├── __init__.py │ └── layer.py ├── rpn_msr │ ├── __init__.py │ ├── anchor_target_layer.py │ ├── generate.py │ ├── generate_anchors.py │ └── proposal_layer.py ├── setup.py └── utils │ ├── .gitignore │ ├── __init__.py │ ├── bbox.pyx │ ├── blob.py │ ├── boxes_grid.py │ ├── nms.py │ ├── nms.pyx │ └── timer.py ├── models ├── CaffeNet │ ├── compressed │ │ └── test.prototxt │ ├── imagenet3d │ │ ├── solver_rcnn_original.prototxt │ │ ├── solver_rcnn_view.prototxt │ │ ├── solver_rpn_msr.prototxt │ │ ├── test_rcnn_original.prototxt │ │ ├── test_rcnn_view.prototxt │ │ ├── test_rpn_msr.prototxt │ │ ├── train_rcnn_original.prototxt │ │ ├── train_rcnn_view.prototxt │ │ └── train_rpn_msr.prototxt │ ├── kitti_test │ │ ├── solver_rcnn_multiscale.prototxt │ │ ├── solver_rcnn_multiscale_6k8k.prototxt │ │ ├── solver_rcnn_original_msr_6k8k.prototxt │ │ ├── solver_rpn.prototxt │ │ ├── solver_rpn_6k8k.prototxt │ │ ├── solver_rpn_msr_6k8k.prototxt │ │ ├── test_rcnn_multiscale.prototxt │ │ ├── test_rcnn_original.prototxt │ │ ├── test_rpn.prototxt │ │ ├── test_rpn_msr.prototxt │ │ ├── train_rcnn_multiscale.prototxt │ │ ├── train_rcnn_original.prototxt │ │ ├── train_rpn.prototxt │ │ └── train_rpn_msr.prototxt │ ├── kitti_tracking_test │ │ ├── solver_rcnn_multiscale.prototxt │ │ ├── solver_rpn.prototxt │ │ ├── test_rcnn_multiscale.prototxt │ │ ├── test_rpn.prototxt │ │ ├── train_rcnn_multiscale.prototxt │ │ └── train_rpn.prototxt │ ├── kitti_tracking_val │ │ ├── solver_rcnn_multiscale.prototxt │ │ ├── solver_rpn.prototxt │ │ ├── test_rcnn_multiscale.prototxt │ │ ├── test_rpn.prototxt │ │ ├── train_rcnn_multiscale.prototxt │ │ └── train_rpn.prototxt │ ├── kitti_val │ │ ├── solver_rcnn.prototxt │ │ ├── solver_rcnn_2d_multiscale.prototxt │ │ ├── solver_rcnn_fix.prototxt │ │ ├── solver_rcnn_msr.prototxt │ │ ├── solver_rcnn_msr_fix.prototxt │ │ ├── solver_rcnn_msr_multiscale.prototxt │ │ ├── solver_rcnn_msr_multiscale_fix.prototxt │ │ ├── solver_rcnn_multiscale.prototxt │ │ ├── solver_rcnn_noextra.prototxt │ │ ├── solver_rcnn_original.prototxt │ │ ├── solver_rcnn_original_msr.prototxt │ │ ├── solver_rcnn_original_multiscale.prototxt │ │ ├── solver_rpn.prototxt │ │ ├── solver_rpn_2d.prototxt │ │ ├── solver_rpn_fix.prototxt │ │ ├── solver_rpn_msr.prototxt │ │ ├── solver_rpn_msr_fix.prototxt │ │ ├── solver_rpn_msr_multiscale_fix.prototxt │ │ ├── test_rcnn.prototxt │ │ ├── test_rcnn_fix.prototxt │ │ ├── test_rcnn_multiscale.prototxt │ │ ├── test_rcnn_original.prototxt │ │ ├── test_rcnn_original_multiscale.prototxt │ │ ├── test_rpn.prototxt │ │ ├── test_rpn_fix.prototxt │ │ ├── test_rpn_msr.prototxt │ │ ├── train_rcnn.prototxt │ │ ├── train_rcnn_fix.prototxt │ │ ├── train_rcnn_multiscale.prototxt │ │ ├── train_rcnn_multiscale_fix.prototxt │ │ ├── train_rcnn_original.prototxt │ │ ├── train_rcnn_original_multiscale.prototxt │ │ ├── train_rpn.prototxt │ │ ├── train_rpn_fix.prototxt │ │ ├── train_rpn_msr.prototxt │ │ └── train_rpn_msr_fix.prototxt │ ├── mot_tracking_train │ │ ├── solver_rcnn_multiscale.prototxt │ │ ├── solver_rpn.prototxt │ │ ├── test_rcnn_multiscale.prototxt │ │ ├── test_rpn.prototxt │ │ ├── train_rcnn_multiscale.prototxt │ │ └── train_rpn.prototxt │ ├── no_bbox_reg │ │ ├── solver.prototxt │ │ ├── test.prototxt │ │ └── train.prototxt │ ├── pascal2007 │ │ ├── solver_rcnn.prototxt │ │ ├── solver_rcnn_original.prototxt │ │ ├── solver_rpn.prototxt │ │ ├── test_rcnn.prototxt │ │ ├── test_rcnn_original.prototxt │ │ ├── test_rpn.prototxt │ │ ├── train_rcnn.prototxt │ │ ├── train_rcnn_original.prototxt │ │ └── train_rpn.prototxt │ ├── piecewise │ │ ├── solver.prototxt │ │ └── train.prototxt │ ├── solver.prototxt │ ├── test.prototxt │ └── train.prototxt ├── GoogleNet │ ├── deploy.prototxt │ ├── kitti_test │ │ ├── solver_rcnn.prototxt │ │ ├── test_rcnn.prototxt │ │ └── train_rcnn.prototxt │ ├── kitti_val │ │ ├── solver_rcnn.prototxt │ │ ├── test_rcnn.prototxt │ │ └── train_rcnn.prototxt │ ├── quick_solver.prototxt │ ├── readme.md │ ├── solver.prototxt │ └── train_val.prototxt ├── README.md ├── VGG16 │ ├── compressed │ │ └── test.prototxt │ ├── fc_only │ │ ├── solver.prototxt │ │ └── train.prototxt │ ├── imagenet3d │ │ ├── solver_rcnn_original.prototxt │ │ ├── solver_rcnn_view.prototxt │ │ ├── solver_rpn_msr.prototxt │ │ ├── test_rcnn_original.prototxt │ │ ├── test_rcnn_view.prototxt │ │ ├── test_rpn_msr.prototxt │ │ ├── train_rcnn_original.prototxt │ │ ├── train_rcnn_view.prototxt │ │ └── train_rpn_msr.prototxt │ ├── kitti_test │ │ ├── solver_rcnn_multiscale_6k8k.prototxt │ │ ├── test_rcnn_multiscale.prototxt │ │ └── train_rcnn_multiscale.prototxt │ ├── kitti_tracking_test │ │ ├── solver_rcnn_multiscale.prototxt │ │ ├── test_rcnn_multiscale.prototxt │ │ └── train_rcnn_multiscale.prototxt │ ├── mot_tracking_test │ │ ├── solver_rcnn_multiscale.prototxt │ │ ├── test_rcnn_multiscale.prototxt │ │ └── train_rcnn_multiscale.prototxt │ ├── no_bbox_reg │ │ ├── solver.prototxt │ │ ├── test.prototxt │ │ └── train.prototxt │ ├── pascal2007 │ │ ├── solver_rcnn_original.prototxt │ │ ├── solver_rcnn_original_multiscale.prototxt │ │ ├── solver_rpn.prototxt │ │ ├── solver_rpn_6k8k.prototxt │ │ ├── solver_rpn_cls.prototxt │ │ ├── test_rcnn_original.prototxt │ │ ├── test_rcnn_original_multiscale.prototxt │ │ ├── test_rpn.prototxt │ │ ├── test_rpn_cls.prototxt │ │ ├── train_rcnn_original.prototxt │ │ ├── train_rcnn_original_multiscale.prototxt │ │ ├── train_rpn.prototxt │ │ └── train_rpn_cls.prototxt │ ├── pascal3d │ │ ├── solver_rcnn.prototxt │ │ ├── solver_rcnn_multiscale.prototxt │ │ ├── solver_rcnn_original.prototxt │ │ ├── solver_rcnn_pose.prototxt │ │ ├── solver_rcnn_pose_multiscale.prototxt │ │ ├── solver_rpn.prototxt │ │ ├── solver_rpn_6k8k.prototxt │ │ ├── solver_rpn_msr.prototxt │ │ ├── test_rcnn.prototxt │ │ ├── test_rcnn_multiscale.prototxt │ │ ├── test_rcnn_original.prototxt │ │ ├── test_rcnn_pose.prototxt │ │ ├── test_rcnn_pose_multiscale.prototxt │ │ ├── test_rpn.prototxt │ │ ├── test_rpn_msr.prototxt │ │ ├── train_rcnn.prototxt │ │ ├── train_rcnn_multiscale.prototxt │ │ ├── train_rcnn_original.prototxt │ │ ├── train_rcnn_pose.prototxt │ │ ├── train_rcnn_pose_multiscale.prototxt │ │ ├── train_rpn.prototxt │ │ └── train_rpn_msr.prototxt │ ├── piecewise │ │ ├── solver.prototxt │ │ └── train.prototxt │ ├── solver.prototxt │ ├── test.prototxt │ └── train.prototxt └── VGG_CNN_M_1024 │ ├── compressed │ └── test.prototxt │ ├── no_bbox_reg │ ├── solver.prototxt │ ├── test.prototxt │ └── train.prototxt │ ├── piecewise │ ├── solver.prototxt │ └── train.prototxt │ ├── solver.prototxt │ ├── test.prototxt │ └── train.prototxt └── tools ├── README.md ├── _init_paths.py ├── compress_net.py ├── demo.py ├── demo_roi.py ├── reval.py ├── test_net.py ├── train_net.py └── train_svms.py /.gitmodules: -------------------------------------------------------------------------------- 1 | [submodule "caffe-fast-rcnn"] 2 | path = caffe-fast-rcnn 3 | url = https://github.com/yuxng/caffe-fast-rcnn.git 4 | branch = fast-rcnn 5 | -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/000015.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/3rd_party/SelectiveSearchCodeIJCV/000015.jpg -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/BlobBestOverlap.m: -------------------------------------------------------------------------------- 1 | function [scores index] = BlobBestOverlap(gtBlobs, testBlobs) 2 | % [scores index] = BlobBestOverlap(gtBlobs, testBlobs) 3 | % 4 | % Get overlap scores (Pascal-wise) for test blobs 5 | % 6 | % groundTruthBlob: ground truth blobs 7 | % test: Test blobs 8 | % 9 | % scores: Highest overlap scores for each test blob. 10 | % index: Index for each test blob which ground truth blob 11 | % is best 12 | % 13 | % Jasper Uijlings - 2013 14 | 15 | numTarget = length(gtBlobs); 16 | numTest = length(testBlobs); 17 | 18 | scoreM = zeros(numTest, numTarget); 19 | 20 | for i=1:numTest 21 | for j=1:numTarget 22 | scoreM(i,j) = PascalOverlapBlob(gtBlobs{j}, testBlobs{i}); 23 | end 24 | end 25 | 26 | [scores index] = max(scoreM, [], 2); 27 | 28 | -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/BlobStruct2HierarchicalGrouping.p: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/3rd_party/SelectiveSearchCodeIJCV/BlobStruct2HierarchicalGrouping.p -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/BlobStructColourHist.p: -------------------------------------------------------------------------------- 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/3rd_party/SelectiveSearchCodeIJCV/Dependencies/BoxBestOverlap.m: -------------------------------------------------------------------------------- 1 | function [scores index] = BoxBestOverlap(gtBoxes, testBoxes) 2 | % [scores index] = BoxBestOverlap(gtBox, testBoxes) 3 | % 4 | % Get overlap scores (Pascal-wise) for testBoxes bounding boxes 5 | % 6 | % gtBoxes: Ground truth bounding boxes 7 | % testBoxes: Test bounding boxes 8 | % 9 | % scores: Highest overlap scores for each testBoxes bbox. 10 | % index: Index for each testBoxes box which ground truth box is best 11 | % 12 | % Jasper Uijlings - 2013 13 | 14 | numGT = size(gtBoxes,1); 15 | numTest = size(testBoxes,1); 16 | 17 | scoreM = zeros(numGT, numTest); 18 | 19 | 20 | for j=1:numGT 21 | scoreM(j,:) = PascalOverlap(gtBoxes(j,:), testBoxes); 22 | end 23 | 24 | 25 | [scores index] = max(scoreM, [], 2); 26 | 27 | 28 | -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/Dependencies/BoxIntersection.m: -------------------------------------------------------------------------------- 1 | function intersection = BoxIntersection(a, b) 2 | % intersection = BoxIntersection(a, b) 3 | % 4 | % Creates the intersection of two bounding boxes. Returns minus ones if 5 | % there is no intersection 6 | % 7 | % a: Input bonding box "a" 8 | % b: Input bounding box "b" 9 | % 10 | % intersection: Intersection of box a and b 11 | % 12 | % Jasper Uijlings - 2013 13 | 14 | intersection = [max(a(:,1),b(:,1)) max(a(:,2),b(:,2)) ... 15 | min(a(:,3),b(:,3)) min(a(:,4),b(:,4))]; 16 | 17 | [numRows numColumns] = BoxSize(intersection); 18 | 19 | % There is no intersection box 20 | negIds = numRows < 1 | numColumns < 1; 21 | intersection(negIds,:) = -1; 22 | 23 | 24 | -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/Dependencies/BoxRemoveDuplicates.m: -------------------------------------------------------------------------------- 1 | function [boxesOut uniqueIdx] = BoxRemoveDuplicates(boxesIn) 2 | % function boxOut = BoxRemoveDuplicates(boxIn) 3 | % 4 | % Removes duplicate boxes. Leaves the boxes in the same order 5 | % Keeps the first box of each kind. 6 | % 7 | % boxesIn: N x 4 array containing boxes 8 | % 9 | % boxexOut: M x 4 array of boxes witout duplicates. M <= N 10 | % uniqueIdx: Indices of retained boxes from boxesIn 11 | % 12 | % Jasper Uijlings - 2013 13 | 14 | [dummy uniqueIdx] = unique(boxesIn, 'rows', 'first'); 15 | uniqueIdx = sort(uniqueIdx); 16 | boxesOut = boxesIn(uniqueIdx,:); 17 | -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/Dependencies/BoxSize.m: -------------------------------------------------------------------------------- 1 | function [numRows numColumns area] = BoxSize(bbox) 2 | % [numRows numColumns Surface] = BoxSize(bbox) 3 | % 4 | % Retrieves number of rows, columns, and surface area from bounding box 5 | % 6 | % bbox: 4 x N Bounding box as [rowBegin colBegin rowEnd colEnd] 7 | % 8 | % numRows: Number of rows of boxes 9 | % numColumns: Number of columns of boxes 10 | % area: Area of boxes 11 | % 12 | % Jasper Uijlings - 2013 13 | 14 | % Box is empty 15 | if isempty(bbox) 16 | numRows = 0; 17 | numColumns = 0; 18 | area = 0; 19 | return 20 | end 21 | 22 | numRows = bbox(:,3) - bbox(:,1) + 1; 23 | numColumns = bbox(:,4) - bbox(:,2) + 1; 24 | area = numRows .* numColumns; 25 | 26 | -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/Dependencies/BoxUnion.m: -------------------------------------------------------------------------------- 1 | function union = BoxUnion(a, b) 2 | % union = BoxUnion(a, b) 3 | % 4 | % Creates the union box of two bounding boxes. 5 | % 6 | % a: Input bonding box "a" 7 | % b: Input bounding box "b" 8 | % 9 | % union: Intersection of box a and b 10 | % 11 | % Jasper Uijlings - 2013 12 | 13 | union = [min(a(:,1),b(:,1)) min(a(:,2),b(:,2)) ... 14 | max(a(:,3),b(:,3)) max(a(:,4),b(:,4))]; 15 | -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/Dependencies/FelzenSegment/Makefile: -------------------------------------------------------------------------------- 1 | INCDIR = -I. 2 | DBG = -g 3 | OPT = -O3 4 | CPP = g++ 5 | CFLAGS = $(DBG) $(OPT) $(INCDIR) 6 | LINK = -lm 7 | 8 | .cpp.o: 9 | $(CPP) $(CFLAGS) -c $< -o $@ 10 | 11 | all: segment 12 | 13 | segment: segment.cpp segment-image.h segment-graph.h disjoint-set.h 14 | $(CPP) $(CFLAGS) -o segment segment.cpp $(LINK) 15 | 16 | clean: 17 | /bin/rm -f segment *.o 18 | 19 | clean-all: clean 20 | /bin/rm -f *~ 21 | 22 | 23 | 24 | -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/Dependencies/FelzenSegment/README: -------------------------------------------------------------------------------- 1 | 2 | Implementation of the segmentation algorithm described in: 3 | 4 | Efficient Graph-Based Image Segmentation 5 | Pedro F. Felzenszwalb and Daniel P. Huttenlocher 6 | International Journal of Computer Vision, 59(2) September 2004. 7 | 8 | The program takes a color image (PPM format) and produces a segmentation 9 | with a random color assigned to each region. 10 | 11 | 1) Type "make" to compile "segment". 12 | 13 | 2) Run "segment sigma k min input output". 14 | 15 | The parameters are: (see the paper for details) 16 | 17 | sigma: Used to smooth the input image before segmenting it. 18 | k: Value for the threshold function. 19 | min: Minimum component size enforced by post-processing. 20 | input: Input image. 21 | output: Output image. 22 | 23 | Typical parameters are sigma = 0.5, k = 500, min = 20. 24 | Larger values for k result in larger components in the result. 25 | 26 | -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/Dependencies/FilterBoxesWidth.m: -------------------------------------------------------------------------------- 1 | function [outBoxes idsGood]= FilterBoxesWidth(inBoxes, minLen) 2 | % [outBoxes idsGood]= FilterBoxesWidth(inBoxes, minLen) 3 | % 4 | % Filters out small boxes. Boxes have to have a width and height 5 | % larger than minLen 6 | % 7 | % inBoxes: M x 4 array of boxes 8 | % minLen: Minimum width and height of boxes 9 | % 10 | % outBoxes: N x 4 array of boxes, N < M 11 | % idsGood: M x 1 logical array denoting boxes kept 12 | % 13 | % Jasper Uijlings - 2013 14 | 15 | [nr nc] = BoxSize(inBoxes); 16 | 17 | idsGood = (nr >= minLen) & (nc >= minLen); 18 | outBoxes = inBoxes(idsGood,:); -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/Dependencies/GetPascalOverlap.m: -------------------------------------------------------------------------------- 1 | function score = GetPascalOverlap(bb, bbgt) 2 | % Directly copied from Pascal code 3 | % 4 | % Gets the overlap measure according to Pascal 5 | % 6 | % bb: Bounding Box 7 | % bbgt: Ground truth bounding box 8 | % 9 | % score: Score between 0 and 1. 1 is complete overlap. 10 | 11 | score = 0; 12 | 13 | % intersection bbox 14 | bi=[max(bb(1),bbgt(1)) ; max(bb(2),bbgt(2)) ; min(bb(3),bbgt(3)) ; min(bb(4),bbgt(4))]; 15 | iw=bi(3)-bi(1)+1; 16 | ih=bi(4)-bi(2)+1; 17 | if iw>0 & ih>0 % intersection should be non-zero 18 | % compute overlap as area of intersection / area of union 19 | ua=(bb(3)-bb(1)+1)*(bb(4)-bb(2)+1)+... 20 | (bbgt(3)-bbgt(1)+1)*(bbgt(4)-bbgt(2)+1)-... 21 | iw*ih; 22 | score=iw*ih/ua; 23 | end -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/Dependencies/Image2ColourSpace.p: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/3rd_party/SelectiveSearchCodeIJCV/Dependencies/Image2ColourSpace.p -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/Dependencies/Image2OrientedGradients.p: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/3rd_party/SelectiveSearchCodeIJCV/Dependencies/Image2OrientedGradients.p -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/Dependencies/NormalizeArray.m: -------------------------------------------------------------------------------- 1 | function b = NormalizeArray(a) 2 | % Normalizes array a. This means that the minimum value will become 0 and 3 | % the maximum value 1. 4 | % 5 | % a: Input array. 6 | % 7 | % b: Normalized output array 8 | % 9 | % Jasper Uijlings - 2013 10 | 11 | minVal = min(a(:)); 12 | maxVal = max(a(:)); 13 | 14 | diffVal = maxVal - minVal; 15 | 16 | b = a - minVal; 17 | if diffVal ~= 0 18 | b = b ./ diffVal; 19 | end 20 | -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/Dependencies/NormalizeRows.m: -------------------------------------------------------------------------------- 1 | function b = NormalizeRows(a, n) 2 | % Normalizes the rows of a. Makes sure there is no division by zero: b will 3 | % not contain any NaN entries. 4 | % 5 | % a: data with row vectors 6 | % n: The rows will sum to n. By default n = 1 7 | % 8 | % b: normalized data with row vecors. All rows sum to one except 9 | % the ones that are zero in the first place: these remain 10 | % zero. 11 | % 12 | % Jasper Uijlings - 2013 13 | 14 | % Get sums 15 | sumA = sum(a,2); 16 | 17 | % Make sure there is no division by zero 18 | sumA(sumA == 0) = 1; 19 | 20 | % Do the normalization 21 | if nargin == 1 22 | b = bsxfun(@rdivide, a, sumA); 23 | else 24 | b = bsxfun(@rdivide, a, sumA / n); 25 | end 26 | 27 | % Do the normalization 28 | % if nargin == 1 29 | % b = a ./ repmat(sumA, 1, size(a,2)); 30 | % else 31 | % b = a .* n ./ repmat(sumA, 1, size(a,2)); 32 | % end -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/Dependencies/PascalOverlap.m: -------------------------------------------------------------------------------- 1 | function scores = PascalOverlap(targetBox, testBoxes) 2 | % scores = PascalOverlap(targetBox, testBoxes) 3 | % 4 | % Function obtains the pascal overlap scores between the targetBox and 5 | % all testBoxes 6 | % 7 | % targetBox: 1 x 4 array containing target box 8 | % testBoxes: N x 4 array containing test boxes 9 | % 10 | % scores: N x 1 array containing for each testBox the pascal 11 | % overlap score. 12 | % 13 | % Jasper Uijlings - 2013 14 | 15 | intersectBoxes = BoxIntersection(targetBox, testBoxes); 16 | overlapI = intersectBoxes(:,1) ~= -1; % Get which boxes overlap 17 | 18 | % Intersection size 19 | [nr nc intersectionSize] = BoxSize(intersectBoxes(overlapI,:)); 20 | 21 | % Union size 22 | [nr nc testBoxSize] = BoxSize(testBoxes(overlapI,:)); 23 | [nr nc targetBoxSize] = BoxSize(targetBox); 24 | unionSize = testBoxSize + targetBoxSize - intersectionSize; 25 | 26 | scores = zeros(size(testBoxes,1),1); 27 | scores(overlapI) = intersectionSize ./ unionSize; 28 | -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/Dependencies/Rgb2C.p: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/3rd_party/SelectiveSearchCodeIJCV/Dependencies/Rgb2C.p -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/Dependencies/Rgb2Ooo.p: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/3rd_party/SelectiveSearchCodeIJCV/Dependencies/Rgb2Ooo.p -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/Dependencies/Rgb2Rg.p: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/3rd_party/SelectiveSearchCodeIJCV/Dependencies/Rgb2Rg.p -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/Dependencies/Rgb2Rgi.p: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/3rd_party/SelectiveSearchCodeIJCV/Dependencies/Rgb2Rgi.p -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/Dependencies/SegmentIndices2Blobs.p: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/3rd_party/SelectiveSearchCodeIJCV/Dependencies/SegmentIndices2Blobs.p -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/Dependencies/ShowRectsWithinImage.m: -------------------------------------------------------------------------------- 1 | function ShowRectsWithinImage(rects, numRow, numCol, image, imageNames) 2 | % ShowRects(Rects, numRow, numCol, image) 3 | % 4 | % Shows only the rectangles of the image 5 | % 6 | % Jasper Uijlings - 2013 7 | 8 | if ~exist('imageNames', 'var') 9 | imageNames = cell(size(rects,1), 1); 10 | for i=1:size(rects,1) 11 | imageNames{i} = sprintf('%d', i); 12 | end 13 | end 14 | 15 | % Convert to images 16 | idx = 1; 17 | images = cell(size(rects,1),1); 18 | for i=1:size(rects,1) 19 | bbox = rects(i,:); 20 | images{idx} = image(bbox(1):bbox(3),bbox(2):bbox(4),:); 21 | idx = idx + 1; 22 | end 23 | 24 | ShowImageCell(images, numRow, numCol, 'rects', imageNames); -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/Dependencies/Vector2Hist.p: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/3rd_party/SelectiveSearchCodeIJCV/Dependencies/Vector2Hist.p -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/Dependencies/gaussianFilter.p: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/3rd_party/SelectiveSearchCodeIJCV/Dependencies/gaussianFilter.p -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/GroundTruthVOC2007test.mat: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/3rd_party/SelectiveSearchCodeIJCV/GroundTruthVOC2007test.mat -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/MergeBlobs.p: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/3rd_party/SelectiveSearchCodeIJCV/MergeBlobs.p -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/RecreateBlobHierarchy.m: -------------------------------------------------------------------------------- 1 | function hBlobs = RecreateBlobHierarchy(blobs, hierarchy) 2 | % [blobs hierarchy] = RecreateBlobHierarchy(blobs, hierarchy) 3 | % 4 | % Recreates the hierarchical grouping using the starting blobs and the 5 | % resulting hierarchy. This allows one to save the grouping using 6 | % relatively small disk space while still being able to fastly recreate the 7 | % complete grouping. 8 | % 9 | % blobs: Input cell array with blobs 10 | % hierarchy: Hierarchy of the blobs as created by 11 | % HierarchicalGrouping.m 12 | % 13 | % hBlobs: All segments of the hierarchical grouping. 14 | % 15 | % Jasper Uijlings - 2013 16 | 17 | hBlobs = cell(length(hierarchy) + 1,1); 18 | 19 | hBlobs(1:length(blobs)) = blobs; 20 | 21 | for i=length(blobs)+1:length(hBlobs) 22 | n = find(hierarchy == i); 23 | 24 | if length(n) ~= 2 25 | error('One can not merge more than 2 blobs!'); 26 | end 27 | 28 | hBlobs{i} = MergeBlobs(hBlobs{n(1)}, hBlobs{n(2)}); 29 | end -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/RecreateBlobHierarchyIndIm.m: -------------------------------------------------------------------------------- 1 | function [hBlobs blobsInit blobsRest] = RecreateBlobHierarchyIndIm(blobIndIm, blobBoxes, hierarchy) 2 | % function hBlobs = RecreateBlobHierarchyIndIm(blobIndIm, boxes, hierarchy) 3 | % 4 | % Recreate hierarchy from the initial segmentation image 5 | % 6 | % blobIndIm: Image with indices denoting segments 7 | % blobBoxes: Boxes belonging to blobs in blobIndIm 8 | % hierarchy: Hierarchy denoting hierarchical merging 9 | % 10 | % hBlobs: All blobs in the hierarchy 11 | % blobsInit: The initial blobs 12 | % blobsRest: All blobs but the initial blobs 13 | % 14 | % Jasper Uijlings - 2013 15 | 16 | % Get blobs of initial segmentation 17 | blobsInit = SegmentIndices2Blobs(blobIndIm, blobBoxes); 18 | 19 | % Add sizes 20 | blobsInit = BlobAddSizes(blobsInit); 21 | 22 | % Reconstruct hierarchy 23 | hBlobs = RecreateBlobHierarchy(blobsInit, hierarchy); 24 | 25 | if nargout == 3 26 | blobsRest = hBlobs(length(blobsInit)+1:end); 27 | end -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/SSSimBoxFill.p: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/3rd_party/SelectiveSearchCodeIJCV/SSSimBoxFill.p -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/SSSimBoxFillOrig.p: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/3rd_party/SelectiveSearchCodeIJCV/SSSimBoxFillOrig.p -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/SSSimBoxFillOrigSize.p: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/3rd_party/SelectiveSearchCodeIJCV/SSSimBoxFillOrigSize.p -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/SSSimBoxFillSize.p: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/3rd_party/SelectiveSearchCodeIJCV/SSSimBoxFillSize.p -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/SSSimColour.p: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/3rd_party/SelectiveSearchCodeIJCV/SSSimColour.p -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/SSSimColourSize.p: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/3rd_party/SelectiveSearchCodeIJCV/SSSimColourSize.p -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/SSSimColourTextureSizeFill.p: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/3rd_party/SelectiveSearchCodeIJCV/SSSimColourTextureSizeFill.p -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/SSSimColourTextureSizeFillOrig.p: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/3rd_party/SelectiveSearchCodeIJCV/SSSimColourTextureSizeFillOrig.p -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/SSSimSize.m: -------------------------------------------------------------------------------- 1 | function [similarity indSim] = SSSimSize(a, b, blobStruct) 2 | % function similarity = SSSimSize(a, b, blobStruct) 3 | % 4 | % Calculate size similarity 5 | 6 | similarity = (blobStruct.imSize - blobStruct.size(a) - blobStruct.size(b)) ... 7 | ./ blobStruct.imSize; 8 | 9 | indSim = similarity; -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/SSSimTexture.p: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/3rd_party/SelectiveSearchCodeIJCV/SSSimTexture.p -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/SSSimTextureSize.p: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/3rd_party/SelectiveSearchCodeIJCV/SSSimTextureSize.p -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/SSSimTextureSizeFill.p: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/3rd_party/SelectiveSearchCodeIJCV/SSSimTextureSizeFill.p -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/anigauss.mexa64: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/3rd_party/SelectiveSearchCodeIJCV/anigauss.mexa64 -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/mexCountWordsIndex.mexa64: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/3rd_party/SelectiveSearchCodeIJCV/mexCountWordsIndex.mexa64 -------------------------------------------------------------------------------- /3rd_party/SelectiveSearchCodeIJCV/mexFelzenSegmentIndex.mexa64: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/3rd_party/SelectiveSearchCodeIJCV/mexFelzenSegmentIndex.mexa64 -------------------------------------------------------------------------------- /ImageNet3D/.gitignore: -------------------------------------------------------------------------------- 1 | *.txt 2 | *.mat 3 | -------------------------------------------------------------------------------- /ImageNet3D/VOCap.m: -------------------------------------------------------------------------------- 1 | function ap = VOCap(rec,prec) 2 | 3 | mrec=[0 ; rec ; 1]; 4 | mpre=[0 ; prec ; 0]; 5 | for i=numel(mpre)-1:-1:1 6 | mpre(i)=max(mpre(i),mpre(i+1)); 7 | end 8 | i=find(mrec(2:end)~=mrec(1:end-1))+1; 9 | ap=sum((mrec(i)-mrec(i-1)).*mpre(i)); 10 | 11 | -------------------------------------------------------------------------------- /ImageNet3D/globals.m: -------------------------------------------------------------------------------- 1 | function opt = globals() 2 | 3 | % KITTI paths 4 | path_kitti = '/net/acadia0a/data/yxiang/KITTI_Dataset'; 5 | if exist(path_kitti, 'dir') == 0 6 | path_kitti = '/home/yuxiang/Projects/KITTI_Dataset'; 7 | end 8 | if exist(path_kitti, 'dir') == 0 9 | path_kitti = '/scail/scratch/u/yuxiang/KITTI_Dataset'; 10 | end 11 | 12 | opt.path_kitti = path_kitti; 13 | opt.path_kitti_devkit = [opt.path_kitti '/devkit/matlab']; 14 | opt.path_kitti_root = [opt.path_kitti '/data_object_image_2']; 15 | 16 | % add kitti devit path 17 | addpath(opt.path_kitti_devkit); 18 | 19 | % ImageNet3D paths 20 | path_imagenet3d = '/capri5/Projects/ImageNet3D'; 21 | if exist(path_imagenet3d, 'dir') == 0 22 | path_imagenet3d = '/scail/scratch/u/yuxiang/ImageNet3D'; 23 | end 24 | opt.path_imagenet3d = path_imagenet3d; 25 | 26 | % add selective search path 27 | addpath(genpath('../3rd_party/SelectiveSearchCodeIJCV')); 28 | -------------------------------------------------------------------------------- /ImageNet3D/rotation_matrix.m: -------------------------------------------------------------------------------- 1 | function R = rotation_matrix(a, e, theta) 2 | 3 | a = -a; 4 | e = pi/2+e; 5 | theta=-theta; 6 | 7 | % rotation matrix 8 | Rz = [cos(a) -sin(a) 0; sin(a) cos(a) 0; 0 0 1]; %rotate by a 9 | Rx = [1 0 0; 0 cos(e) -sin(e); 0 sin(e) cos(e)]; %rotate by e 10 | Rz2= [cos(theta), -sin(theta),0; sin(theta), cos(theta), 0; 0,0,1]; 11 | R = Rz2*Rx*Rz; -------------------------------------------------------------------------------- /ImageNet3D/selective_search_ImageNet3D.m: -------------------------------------------------------------------------------- 1 | function selective_search_ImageNet3D 2 | 3 | matlabpool open; 4 | 5 | opt = globals(); 6 | 7 | % ImageNet3D paths 8 | root_dir = opt.path_imagenet3d; 9 | image_dir = fullfile(root_dir, 'Images'); 10 | image_set_dir = fullfile(root_dir, 'Image_sets'); 11 | 12 | % output dir 13 | out_dir = 'region_proposals/selective_search'; 14 | if exist(out_dir, 'dir') == 0 15 | mkdir(out_dir); 16 | end 17 | 18 | % read ids 19 | ids = textread(fullfile(image_set_dir, 'all.txt'), '%s'); 20 | N = numel(ids); 21 | 22 | % main loop 23 | parfor i = 1:N 24 | filename = sprintf('%s/%s.JPEG', image_dir, ids{i}); 25 | I = imread(filename); 26 | boxes = selective_search_boxes(I); 27 | fprintf('%d \\ %d, %d boxes\n', i, N, size(boxes, 1)); 28 | % write results 29 | fid = fopen(sprintf('%s/%s.txt', out_dir, ids{i}), 'w'); 30 | for j = 1:size(boxes,1) 31 | fprintf(fid, '%d %d %d %d\n', boxes(j,1), boxes(j,2), boxes(j,3), boxes(j,4)); 32 | end 33 | fclose(fid); 34 | end 35 | 36 | matlabpool close; -------------------------------------------------------------------------------- /KITTI/VOCap.m: -------------------------------------------------------------------------------- 1 | function ap = VOCap(rec,prec) 2 | 3 | mrec=[0 ; rec ; 1]; 4 | mpre=[0 ; prec ; 0]; 5 | for i=numel(mpre)-1:-1:1 6 | mpre(i)=max(mpre(i),mpre(i+1)); 7 | end 8 | i=find(mrec(2:end)~=mrec(1:end-1))+1; 9 | ap=sum((mrec(i)-mrec(i-1)).*mpre(i)); 10 | 11 | -------------------------------------------------------------------------------- /KITTI/boxoverlap.m: -------------------------------------------------------------------------------- 1 | function [o, o2] = boxoverlap(a, b) 2 | % Compute the symmetric intersection over union overlap between a set of 3 | % bounding boxes in a and a single bounding box in b. 4 | % 5 | % a a matrix where each row specifies a bounding box 6 | % b a single bounding box 7 | 8 | x1 = max(a(:,1), b(1)); 9 | y1 = max(a(:,2), b(2)); 10 | x2 = min(a(:,3), b(3)); 11 | y2 = min(a(:,4), b(4)); 12 | 13 | % w = x2-x1+1; 14 | % h = y2-y1+1; 15 | % inter = w.*h; 16 | % aarea = (a(:,3)-a(:,1)+1) .* (a(:,4)-a(:,2)+1); 17 | % barea = (b(3)-b(1)+1) * (b(4)-b(2)+1); 18 | 19 | w = x2-x1; 20 | h = y2-y1; 21 | inter = w.*h; 22 | aarea = (a(:,3)-a(:,1)) .* (a(:,4)-a(:,2)); 23 | barea = (b(3)-b(1)) * (b(4)-b(2)); 24 | 25 | % intersection over union overlap 26 | o = inter ./ (aarea+barea-inter); 27 | % set invalid entries to 0 overlap 28 | o(w <= 0) = 0; 29 | o(h <= 0) = 0; 30 | 31 | if nargout == 2 32 | o2 = inter ./ aarea; 33 | % set invalid entries to 0 overlap 34 | o2(w <= 0) = 0; 35 | o2(h <= 0) = 0; 36 | end 37 | -------------------------------------------------------------------------------- /KITTI/compute_3d_points.m: -------------------------------------------------------------------------------- 1 | % compute the 3D point locations of a CAD model 2 | function x3d = compute_3d_points(vertices, object) 3 | 4 | x3d = vertices'; 5 | 6 | % rotation matrix to transform coordinate systems 7 | Rx = [1 0 0; 0 0 -1; 0 1 0]; 8 | Ry = [cos(-pi/2) 0 sin(-pi/2); 0 1 0; -sin(-pi/2) 0 cos(-pi/2)]; 9 | x3d = Ry*Rx*x3d; 10 | 11 | % scaling factors 12 | sx = object.l / (max(x3d(1,:)) - min(x3d(1,:))); 13 | sy = object.h / (max(x3d(2,:)) - min(x3d(2,:))); 14 | sz = object.w / (max(x3d(3,:)) - min(x3d(3,:))); 15 | x3d = diag([sx sy sz]) * x3d; 16 | 17 | % compute rotational matrix around yaw axis 18 | R = [+cos(object.ry), 0, +sin(object.ry); 19 | 0, 1, 0; 20 | -sin(object.ry), 0, +cos(object.ry)]; 21 | 22 | % rotate and translate 3D bounding box 23 | x3d = R*x3d; 24 | x3d(1,:) = x3d(1,:) + object.t(1); 25 | x3d(2,:) = x3d(2,:) + object.t(2) - object.h/2; 26 | x3d(3,:) = x3d(3,:) + object.t(3); -------------------------------------------------------------------------------- /KITTI/globals.m: -------------------------------------------------------------------------------- 1 | function opt = globals() 2 | 3 | % KITTI paths 4 | path_kitti = '/net/acadia0a/data/yxiang/KITTI_Dataset'; 5 | if exist(path_kitti, 'dir') == 0 6 | path_kitti = '/home/yuxiang/Projects/KITTI_Dataset'; 7 | end 8 | if exist(path_kitti, 'dir') == 0 9 | path_kitti = '/scail/scratch/u/yuxiang/KITTI_Dataset'; 10 | end 11 | 12 | opt.path_kitti = path_kitti; 13 | opt.path_kitti_devkit = [opt.path_kitti '/devkit/matlab']; 14 | opt.path_kitti_root = [opt.path_kitti '/data_object_image_2']; 15 | 16 | % add kitti devit path 17 | addpath(opt.path_kitti_devkit); 18 | 19 | % add selective search path 20 | addpath(genpath('../3rd_party/SelectiveSearchCodeIJCV')); 21 | -------------------------------------------------------------------------------- /KITTI/kitti_ids_new.mat: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/KITTI/kitti_ids_new.mat -------------------------------------------------------------------------------- /KITTI/load_off_file.m: -------------------------------------------------------------------------------- 1 | % load an off file 2 | function [vertices, faces] = load_off_file(filename) 3 | 4 | vertices = []; 5 | faces = []; 6 | 7 | fid = fopen(filename, 'r'); 8 | line = fgetl(fid); 9 | if strcmp(line, 'OFF') == 0 10 | fprintf('Wrong format .off file %s!\n', filename); 11 | return; 12 | end 13 | 14 | line = fgetl(fid); 15 | num = sscanf(line, '%f', 3); 16 | nv = num(1); 17 | nf = num(2); 18 | vertices = zeros(nv, 3); 19 | faces = zeros(nf, 3); 20 | 21 | for i = 1:nv 22 | line = fgetl(fid); 23 | vertices(i,:) = sscanf(line, '%f', 3); 24 | end 25 | 26 | for i = 1:nf 27 | line = fgetl(fid); 28 | fsize = sscanf(line, '%f', 1); 29 | if fsize ~= 3 30 | printf('Face contains more than 3 vertices!'); 31 | end 32 | temp = sscanf(line, '%f', 4); 33 | faces(i,:) = temp(2:4); 34 | end 35 | faces = faces + 1; 36 | 37 | fclose(fid); -------------------------------------------------------------------------------- /KITTI/selective_search_KITTI.m: -------------------------------------------------------------------------------- 1 | function selective_search_KITTI 2 | 3 | matlabpool open; 4 | 5 | opt = globals(); 6 | 7 | % KITTI paths 8 | root_dir = opt.path_kitti_root; 9 | data_set = 'training'; 10 | 11 | % get sub-directories 12 | cam = 2; % 2 = left color camera 13 | image_dir = fullfile(root_dir,[data_set '/image_' num2str(cam)]); 14 | 15 | % get number of images for this dataset 16 | N = length(dir(fullfile(image_dir, '*.png'))); 17 | boxes = cell(1, N); 18 | images = cell(1, N); 19 | 20 | % main loop 21 | parfor i = 1:N 22 | img_idx = i - 1; 23 | filename = sprintf('%s/%06d.png', image_dir, img_idx); 24 | I = imread(filename); 25 | boxes{i} = selective_search_boxes(I); 26 | images{i} = sprintf('%06d', img_idx); 27 | fprintf('%d \\ %d, %d boxes\n', i, N, size(boxes{i}, 1)); 28 | end 29 | 30 | filename = sprintf('KITTI_%s.mat', data_set); 31 | save(filename, 'boxes', 'images', '-v7.3'); 32 | 33 | matlabpool close; -------------------------------------------------------------------------------- /KITTI/selective_search_demo.m: -------------------------------------------------------------------------------- 1 | function selective_search_demo 2 | 3 | opt = globals(); 4 | 5 | % KITTI paths 6 | root_dir = opt.path_kitti_root; 7 | data_set = 'training'; 8 | 9 | % get sub-directories 10 | cam = 2; % 2 = left color camera 11 | image_dir = fullfile(root_dir,[data_set '/image_' num2str(cam)]); 12 | 13 | % get number of images for this dataset 14 | nimages = length(dir(fullfile(image_dir, '*.png'))); 15 | 16 | % main loop 17 | figure(1); 18 | for img_idx = 0:nimages-1 19 | I = imread(sprintf('%s/%06d.png', image_dir, img_idx)); 20 | boxes = selective_search_boxes(I); 21 | 22 | % show the boxes 23 | imshow(I); 24 | hold on; 25 | for i = 1:size(boxes,1) 26 | box = boxes(i,:); 27 | box_draw = [box(2) box(1) box(4)-box(2) box(3)-box(1)]; 28 | rectangle('Position', box_draw, 'EdgeColor', 'g', 'LineWidth', 2); 29 | end 30 | pause; 31 | end -------------------------------------------------------------------------------- /KITTI/write_dets_to_files.m: -------------------------------------------------------------------------------- 1 | function write_dets_to_files 2 | 3 | % load ids 4 | object = load('kitti_ids_new.mat'); 5 | ids_train = object.ids_train; 6 | ids_val = object.ids_val; 7 | ids_test = object.ids_test; 8 | 9 | % load detections 10 | object = load('car_3d_aps_125_combined_train.mat'); 11 | dets_train = object.dets; 12 | object = load('car_3d_aps_125_combined_test.mat'); 13 | dets_val = object.dets; 14 | 15 | for i = 1:numel(ids_train) 16 | filename = sprintf('3DVP_125/training/%06d.txt', ids_train(i)); 17 | disp(filename); 18 | fid = fopen(filename, 'w'); 19 | 20 | det = dets_train{i}; 21 | for j = 1:size(det,1) 22 | fprintf(fid, '%f %f %f %f\n', det(j,1), det(j,2), det(j,3), det(j,4)); 23 | end 24 | 25 | fclose(fid); 26 | end 27 | 28 | for i = 1:numel(ids_val) 29 | filename = sprintf('3DVP_125/training/%06d.txt', ids_val(i)); 30 | disp(filename); 31 | fid = fopen(filename, 'w'); 32 | 33 | det = dets_val{i}; 34 | for j = 1:size(det,1) 35 | fprintf(fid, '%f %f %f %f\n', det(j,1), det(j,2), det(j,3), det(j,4)); 36 | end 37 | 38 | fclose(fid); 39 | end 40 | -------------------------------------------------------------------------------- /KITTI/write_ids_to_files.m: -------------------------------------------------------------------------------- 1 | function write_ids_to_files 2 | 3 | object = load('kitti_ids_new.mat'); 4 | ids_train = object.ids_train; 5 | ids_val = object.ids_val; 6 | ids_test = object.ids_test; 7 | 8 | filename = 'train.txt'; 9 | fid = fopen(filename, 'w'); 10 | ids = ids_train; 11 | for i = 1:numel(ids) 12 | fprintf(fid, '%06d\n', ids(i)); 13 | end 14 | fclose(fid); 15 | 16 | filename = 'val.txt'; 17 | fid = fopen(filename, 'w'); 18 | ids = ids_val; 19 | for i = 1:numel(ids) 20 | fprintf(fid, '%06d\n', ids(i)); 21 | end 22 | fclose(fid); 23 | 24 | 25 | filename = 'trainval.txt'; 26 | fid = fopen(filename, 'w'); 27 | ids = sort([ids_train ids_val]); 28 | for i = 1:numel(ids) 29 | fprintf(fid, '%06d\n', ids(i)); 30 | end 31 | fclose(fid); 32 | 33 | filename = 'test.txt'; 34 | fid = fopen(filename, 'w'); 35 | ids = ids_test; 36 | for i = 1:numel(ids) 37 | fprintf(fid, '%06d\n', ids(i)); 38 | end 39 | fclose(fid); -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | The MIT License (MIT) 2 | 3 | Copyright (c) 2015 yuxng 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | 23 | -------------------------------------------------------------------------------- /MOT/VOCap.m: -------------------------------------------------------------------------------- 1 | function ap = VOCap(rec,prec) 2 | 3 | mrec=[0 ; rec ; 1]; 4 | mpre=[0 ; prec ; 0]; 5 | for i=numel(mpre)-1:-1:1 6 | mpre(i)=max(mpre(i),mpre(i+1)); 7 | end 8 | i=find(mrec(2:end)~=mrec(1:end-1))+1; 9 | ap=sum((mrec(i)-mrec(i-1)).*mpre(i)); 10 | 11 | -------------------------------------------------------------------------------- /MOT/boxoverlap.m: -------------------------------------------------------------------------------- 1 | function [o, o2] = boxoverlap(a, b) 2 | % Compute the symmetric intersection over union overlap between a set of 3 | % bounding boxes in a and a single bounding box in b. 4 | % 5 | % a a matrix where each row specifies a bounding box 6 | % b a single bounding box 7 | 8 | x1 = max(a(:,1), b(1)); 9 | y1 = max(a(:,2), b(2)); 10 | x2 = min(a(:,3), b(3)); 11 | y2 = min(a(:,4), b(4)); 12 | 13 | % w = x2-x1+1; 14 | % h = y2-y1+1; 15 | % inter = w.*h; 16 | % aarea = (a(:,3)-a(:,1)+1) .* (a(:,4)-a(:,2)+1); 17 | % barea = (b(3)-b(1)+1) * (b(4)-b(2)+1); 18 | 19 | w = x2-x1; 20 | h = y2-y1; 21 | inter = w.*h; 22 | aarea = (a(:,3)-a(:,1)) .* (a(:,4)-a(:,2)); 23 | barea = (b(3)-b(1)) * (b(4)-b(2)); 24 | 25 | % intersection over union overlap 26 | o = inter ./ (aarea+barea-inter); 27 | % set invalid entries to 0 overlap 28 | o(w <= 0) = 0; 29 | o(h <= 0) = 0; 30 | 31 | if nargout == 2 32 | o2 = inter ./ aarea; 33 | % set invalid entries to 0 overlap 34 | o2(w <= 0) = 0; 35 | o2(h <= 0) = 0; 36 | end 37 | -------------------------------------------------------------------------------- /PASCAL/boxoverlap.m: -------------------------------------------------------------------------------- 1 | function [o, o2] = boxoverlap(a, b) 2 | % Compute the symmetric intersection over union overlap between a set of 3 | % bounding boxes in a and a single bounding box in b. 4 | % 5 | % a a matrix where each row specifies a bounding box 6 | % b a single bounding box 7 | 8 | x1 = max(a(:,1), b(1)); 9 | y1 = max(a(:,2), b(2)); 10 | x2 = min(a(:,3), b(3)); 11 | y2 = min(a(:,4), b(4)); 12 | 13 | % w = x2-x1+1; 14 | % h = y2-y1+1; 15 | % inter = w.*h; 16 | % aarea = (a(:,3)-a(:,1)+1) .* (a(:,4)-a(:,2)+1); 17 | % barea = (b(3)-b(1)+1) * (b(4)-b(2)+1); 18 | 19 | w = x2-x1; 20 | h = y2-y1; 21 | inter = w.*h; 22 | aarea = (a(:,3)-a(:,1)) .* (a(:,4)-a(:,2)); 23 | barea = (b(3)-b(1)) * (b(4)-b(2)); 24 | 25 | % intersection over union overlap 26 | o = inter ./ (aarea+barea-inter); 27 | % set invalid entries to 0 overlap 28 | o(w <= 0) = 0; 29 | o(h <= 0) = 0; 30 | 31 | if nargout == 2 32 | o2 = inter ./ aarea; 33 | % set invalid entries to 0 overlap 34 | o2(w <= 0) = 0; 35 | o2(h <= 0) = 0; 36 | end 37 | -------------------------------------------------------------------------------- /PASCAL/globals.m: -------------------------------------------------------------------------------- 1 | function opt = globals() 2 | 3 | opt.path_pascal = '/home/yuxiang/Projects/VOCdevkit'; -------------------------------------------------------------------------------- /PASCAL/pascal_init.m: -------------------------------------------------------------------------------- 1 | % initialize the PASCAL development kit 2 | tmp = pwd; 3 | cd(opt.path_pascal); 4 | addpath([cd '/VOCcode']); 5 | VOCinit; 6 | cd(tmp); 7 | -------------------------------------------------------------------------------- /PASCAL3D/boxoverlap.m: -------------------------------------------------------------------------------- 1 | function [o, o2] = boxoverlap(a, b) 2 | % Compute the symmetric intersection over union overlap between a set of 3 | % bounding boxes in a and a single bounding box in b. 4 | % 5 | % a a matrix where each row specifies a bounding box 6 | % b a single bounding box 7 | 8 | x1 = max(a(:,1), b(1)); 9 | y1 = max(a(:,2), b(2)); 10 | x2 = min(a(:,3), b(3)); 11 | y2 = min(a(:,4), b(4)); 12 | 13 | % w = x2-x1+1; 14 | % h = y2-y1+1; 15 | % inter = w.*h; 16 | % aarea = (a(:,3)-a(:,1)+1) .* (a(:,4)-a(:,2)+1); 17 | % barea = (b(3)-b(1)+1) * (b(4)-b(2)+1); 18 | 19 | w = x2-x1; 20 | h = y2-y1; 21 | inter = w.*h; 22 | aarea = (a(:,3)-a(:,1)) .* (a(:,4)-a(:,2)); 23 | barea = (b(3)-b(1)) * (b(4)-b(2)); 24 | 25 | % intersection over union overlap 26 | o = inter ./ (aarea+barea-inter); 27 | % set invalid entries to 0 overlap 28 | o(w <= 0) = 0; 29 | o(h <= 0) = 0; 30 | 31 | if nargout == 2 32 | o2 = inter ./ aarea; 33 | % set invalid entries to 0 overlap 34 | o2(w <= 0) = 0; 35 | o2(h <= 0) = 0; 36 | end 37 | -------------------------------------------------------------------------------- /PASCAL3D/compute_ap_avp.m: -------------------------------------------------------------------------------- 1 | function compute_ap_avp(vnum_train) 2 | 3 | vnum_test = vnum_train; 4 | 5 | classes = {'aeroplane', 'bicycle', 'boat', ... 6 | 'bottle', 'bus', 'car', 'chair', ... 7 | 'diningtable', 'motorbike', ... 8 | 'sofa', 'train', 'tvmonitor'}; 9 | num_cls = numel(classes); 10 | 11 | aps = zeros(num_cls, 1); 12 | avps = zeros(num_cls, 1); 13 | for i = 1:num_cls 14 | cls = classes{i}; 15 | [recall, precision, accuracy, ap, aa] = compute_recall_precision_accuracy(cls, vnum_train, vnum_test); 16 | aps(i) = ap; 17 | avps(i) = aa; 18 | end 19 | 20 | for i = 1:num_cls 21 | cls = classes{i}; 22 | fprintf('%s %f %f\n', cls, aps(i), avps(i)); 23 | end -------------------------------------------------------------------------------- /PASCAL3D/compute_statistics.m: -------------------------------------------------------------------------------- 1 | function compute_statistics 2 | 3 | opt = globals; 4 | pascal_init; 5 | 6 | classes = {'aeroplane', 'bicycle', 'boat', ... 7 | 'bottle', 'bus', 'car', 'chair', ... 8 | 'diningtable', 'motorbike', ... 9 | 'sofa', 'train', 'tvmonitor'}; 10 | num_cls = numel(classes); 11 | nums = zeros(num_cls, 1); 12 | 13 | % load test set 14 | [ids, t] = textread(sprintf(VOCopts.imgsetpath, 'train'), '%s %d'); 15 | M = numel(ids); 16 | 17 | % read ground truth 18 | for i = 1:M 19 | % read ground truth 20 | rec = PASreadrecord(sprintf(VOCopts.annopath, ids{i})); 21 | objects = rec.objects; 22 | 23 | for j = 1:numel(objects) 24 | difficult = objects(j).difficult; 25 | cls = objects(j).class; 26 | index = find(strcmp(cls, classes) == 1); 27 | if isempty(index) == 0 28 | nums(index) = nums(index) + 1; 29 | end 30 | end 31 | end 32 | 33 | fprintf('%d images\n', M); 34 | for i = 1:numel(classes) 35 | fprintf('%s: %d objects\n', classes{i}, nums(i)); 36 | end -------------------------------------------------------------------------------- /PASCAL3D/globals.m: -------------------------------------------------------------------------------- 1 | function opt = globals() 2 | 3 | opt.root = '/home/yuxiang/Projects/PASCAL3D+_release1.1'; 4 | opt.path_pascal = '/home/yuxiang/Projects/PASCAL3D+_release1.1/PASCAL/VOCdevkit'; 5 | 6 | SLMpaths = {'/net/skyserver30/workplace/local/wongun/yuxiang/SLM', ... 7 | '/net/skyserver10/workplace/yxiang/SLM', ... 8 | '/home/yuxiang/Projects/SLM', ... 9 | '/scail/scratch/u/yuxiang/SLM'}; 10 | 11 | for i = 1:numel(SLMpaths) 12 | if exist(SLMpaths{i}, 'dir') 13 | opt.SLMroot = SLMpaths{i}; 14 | break; 15 | end 16 | end -------------------------------------------------------------------------------- /PASCAL3D/pascal_init.m: -------------------------------------------------------------------------------- 1 | % initialize the PASCAL development kit 2 | tmp = pwd; 3 | cd(opt.path_pascal); 4 | addpath([cd '/VOCcode']); 5 | VOCinit; 6 | cd(tmp); 7 | -------------------------------------------------------------------------------- /fast-rcnn/.gitignore: -------------------------------------------------------------------------------- 1 | *.pyc 2 | .ipynb_checkpoints 3 | utils/*.c 4 | utils/*.so 5 | -------------------------------------------------------------------------------- /fast-rcnn/data/.gitignore: -------------------------------------------------------------------------------- 1 | selective_search* 2 | imagenet_models* 3 | fast_rcnn_models* 4 | VOCdevkit* 5 | cache 6 | -------------------------------------------------------------------------------- /fast-rcnn/data/KITTI/voxel_exemplars.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/fast-rcnn/data/KITTI/voxel_exemplars.zip -------------------------------------------------------------------------------- /fast-rcnn/data/NTHU/region_proposals/RPN_6k8k/.gitignore: -------------------------------------------------------------------------------- 1 | 71/* 2 | 370/* 3 | -------------------------------------------------------------------------------- /fast-rcnn/data/PASCAL3D/voxel_exemplars.zip: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/fast-rcnn/data/PASCAL3D/voxel_exemplars.zip -------------------------------------------------------------------------------- /fast-rcnn/data/demo/000004.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/fast-rcnn/data/demo/000004.jpg -------------------------------------------------------------------------------- /fast-rcnn/data/demo/000004_boxes.mat: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/fast-rcnn/data/demo/000004_boxes.mat -------------------------------------------------------------------------------- /fast-rcnn/data/demo/001551.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/fast-rcnn/data/demo/001551.jpg -------------------------------------------------------------------------------- /fast-rcnn/data/demo/001551_boxes.mat: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/fast-rcnn/data/demo/001551_boxes.mat -------------------------------------------------------------------------------- /fast-rcnn/data/pylintrc: -------------------------------------------------------------------------------- 1 | [TYPECHECK] 2 | 3 | ignored-modules = numpy, numpy.random, cv2 4 | -------------------------------------------------------------------------------- /fast-rcnn/data/scripts/fetch_3dvp_rcnn_models.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )/../" && pwd )" 4 | cd $DIR 5 | 6 | FILE=3DVP_RCNN_models.zip 7 | URL=ftp://cs.stanford.edu/cs/cvgl/$FILE 8 | 9 | echo "Downloading 3DVP RCNN KITTI models (228M)..." 10 | 11 | wget $URL -O $FILE 12 | 13 | echo "Unzipping..." 14 | 15 | unzip $FILE 16 | -------------------------------------------------------------------------------- /fast-rcnn/data/scripts/fetch_fast_rcnn_models.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )/../" && pwd )" 4 | cd $DIR 5 | 6 | FILE=fast_rcnn_models.tgz 7 | URL=http://www.cs.berkeley.edu/~rbg/fast-rcnn-data/$FILE 8 | CHECKSUM=5f7dde9f5376e18c8e065338cc5df3f7 9 | 10 | if [ -f $FILE ]; then 11 | echo "File already exists. Checking md5..." 12 | os=`uname -s` 13 | if [ "$os" = "Linux" ]; then 14 | checksum=`md5sum $FILE | awk '{ print $1 }'` 15 | elif [ "$os" = "Darwin" ]; then 16 | checksum=`cat $FILE | md5` 17 | fi 18 | if [ "$checksum" = "$CHECKSUM" ]; then 19 | echo "Checksum is correct. No need to download." 20 | exit 0 21 | else 22 | echo "Checksum is incorrect. Need to download again." 23 | fi 24 | fi 25 | 26 | echo "Downloading Fast R-CNN demo models (0.96G)..." 27 | 28 | wget $URL -O $FILE 29 | 30 | echo "Unzipping..." 31 | 32 | tar zxvf $FILE 33 | 34 | echo "Done. Please run this command again to verify that checksum = $CHECKSUM." 35 | -------------------------------------------------------------------------------- /fast-rcnn/data/scripts/fetch_imagenet_models.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )/../" && pwd )" 4 | cd $DIR 5 | 6 | FILE=imagenet_models.tgz 7 | URL=http://www.cs.berkeley.edu/~rbg/fast-rcnn-data/$FILE 8 | CHECKSUM=8b1d4b9da0593fc70ef403284f810adc 9 | 10 | if [ -f $FILE ]; then 11 | echo "File already exists. Checking md5..." 12 | os=`uname -s` 13 | if [ "$os" = "Linux" ]; then 14 | checksum=`md5sum $FILE | awk '{ print $1 }'` 15 | elif [ "$os" = "Darwin" ]; then 16 | checksum=`cat $FILE | md5` 17 | fi 18 | if [ "$checksum" = "$CHECKSUM" ]; then 19 | echo "Checksum is correct. No need to download." 20 | exit 0 21 | else 22 | echo "Checksum is incorrect. Need to download again." 23 | fi 24 | fi 25 | 26 | echo "Downloading pretrained ImageNet models (1G)..." 27 | 28 | wget $URL -O $FILE 29 | 30 | echo "Unzipping..." 31 | 32 | tar zxvf $FILE 33 | 34 | echo "Done. Please run this command again to verify that checksum = $CHECKSUM." 35 | -------------------------------------------------------------------------------- /fast-rcnn/data/scripts/fetch_selective_search_data.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )/../" && pwd )" 4 | cd $DIR 5 | 6 | FILE=selective_search_data.tgz 7 | URL=http://www.cs.berkeley.edu/~rbg/fast-rcnn-data/$FILE 8 | CHECKSUM=7078c1db87a7851b31966b96774cd9b9 9 | 10 | if [ -f $FILE ]; then 11 | echo "File already exists. Checking md5..." 12 | os=`uname -s` 13 | if [ "$os" = "Linux" ]; then 14 | checksum=`md5sum $FILE | awk '{ print $1 }'` 15 | elif [ "$os" = "Darwin" ]; then 16 | checksum=`cat $FILE | md5` 17 | fi 18 | if [ "$checksum" = "$CHECKSUM" ]; then 19 | echo "Checksum is correct. No need to download." 20 | exit 0 21 | else 22 | echo "Checksum is incorrect. Need to download again." 23 | fi 24 | fi 25 | 26 | echo "Downloading precomputed selective search boxes (0.5G)..." 27 | 28 | wget $URL -O $FILE 29 | 30 | echo "Unzipping..." 31 | 32 | tar zxvf $FILE 33 | 34 | echo "Done. Please run this command again to verify that checksum = $CHECKSUM." 35 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/imagenet3d_rpn_msr.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: imagenet3d 2 | IS_RPN: True 3 | IS_MULTISCALE: False 4 | TRAIN: 5 | SCALES_BASE: !!python/tuple [2.0] 6 | IMS_PER_BATCH: 1 7 | FG_THRESH: !!python/tuple [0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 8 | 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 9 | 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 10 | 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 11 | 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7] 12 | SNAPSHOT_INFIX: imagenet3d 13 | BBOX_REG: False 14 | SUBCLS: False 15 | SNAPSHOT_ITERS: 40000 16 | RPN_ASPECTS: !!python/tuple [0.125, 0.25, 0.5, 0.75, 1, 1.5, 2, 3, 4, 6, 8] 17 | RPN_SCALES: !!python/tuple [2, 2.82842712, 4, 5.65685425, 8, 11.3137085, 16, 22.627417, 32, 45.254834, 64] 18 | TEST: 19 | SCALES_BASE: !!python/tuple [2.0] 20 | NMS: 0.5 21 | BBOX_REG: False 22 | SUBCLS: False 23 | RPN_PRE_NMS_TOP_N: 80000 24 | RPN_POST_NMS_TOP_N: 2000 25 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/kitti_rcnn.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: kitti 2 | IS_RPN: False 3 | IS_MULTISCALE: False 4 | REGION_PROPOSAL: 'RPN' 5 | TRAIN: 6 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 7 | NUM_PER_OCTAVE: 4 8 | IMS_PER_BATCH: 2 9 | FG_FRACTION: 0.25 10 | FG_THRESH: !!python/tuple [0.7, 0.5, 0.5] 11 | BG_THRESH_HI: !!python/tuple [0.7, 0.5, 0.5] 12 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1] 13 | BBOX_THRESH: !!python/tuple [0.7, 0.5, 0.5] 14 | ROI_THRESHOLD: 0.01 15 | SNAPSHOT_INFIX: kitti 16 | TEST: 17 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 18 | NUM_PER_OCTAVE: 4 19 | NMS: 0.5 20 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/kitti_rcnn_2d_multiscale.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: kitti 2 | IS_RPN: False 3 | IS_MULTISCALE: True 4 | REGION_PROPOSAL: 'RPN_2D' 5 | SUBCLS_NAME: '2d_exemplars' 6 | TRAIN: 7 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 8 | NUM_PER_OCTAVE: 4 9 | IMS_PER_BATCH: 2 10 | FG_FRACTION: 0.25 11 | FG_THRESH: !!python/tuple [0.7, 0.5, 0.5] 12 | BG_THRESH_HI: !!python/tuple [0.7, 0.5, 0.5] 13 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1] 14 | BBOX_THRESH: !!python/tuple [0.7, 0.5, 0.5] 15 | ROI_THRESHOLD: 0.01 16 | SNAPSHOT_INFIX: kitti 17 | TEST: 18 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 19 | NUM_PER_OCTAVE: 4 20 | NMS: 0.5 21 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/kitti_rcnn_fix.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: kitti 2 | IS_RPN: False 3 | IS_MULTISCALE: False 4 | REGION_PROPOSAL: 'RPN' 5 | TRAIN: 6 | SCALES_BASE: !!python/tuple [0.25, 0.5, 1.0, 2.0, 3.0] 7 | NUM_PER_OCTAVE: 4 8 | IMS_PER_BATCH: 2 9 | FG_FRACTION: 0.25 10 | FG_THRESH: !!python/tuple [0.7, 0.5, 0.5] 11 | BG_THRESH_HI: !!python/tuple [0.7, 0.5, 0.5] 12 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1] 13 | BBOX_THRESH: !!python/tuple [0.7, 0.5, 0.5] 14 | ROI_THRESHOLD: 0.01 15 | SNAPSHOT_INFIX: kitti 16 | TEST: 17 | SCALES_BASE: !!python/tuple [0.25, 0.5, 1.0, 2.0, 3.0] 18 | NUM_PER_OCTAVE: 4 19 | NMS: 0.5 20 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/kitti_rcnn_googlenet.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: kitti 2 | IS_RPN: False 3 | IS_MULTISCALE: False 4 | REGION_PROPOSAL: 'RPN' 5 | TRAIN: 6 | SCALES_BASE: !!python/tuple [1.0] 7 | NUM_PER_OCTAVE: 4 8 | IMS_PER_BATCH: 2 9 | FG_FRACTION: 0.25 10 | FG_THRESH: !!python/tuple [0.7, 0.5, 0.5] 11 | BG_THRESH_HI: !!python/tuple [0.7, 0.5, 0.5] 12 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1] 13 | BBOX_THRESH: !!python/tuple [0.7, 0.5, 0.5] 14 | ROI_THRESHOLD: 0.01 15 | SNAPSHOT_INFIX: kitti 16 | TEST: 17 | IS_PATCH: True 18 | SCALES_BASE: !!python/tuple [1.0] 19 | NUM_PER_OCTAVE: 4 20 | NMS: 0.5 21 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/kitti_rcnn_msr.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: kitti 2 | IS_RPN: False 3 | IS_MULTISCALE: False 4 | REGION_PROPOSAL: 'RPN_MSR' 5 | TRAIN: 6 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 7 | NUM_PER_OCTAVE: 4 8 | IMS_PER_BATCH: 2 9 | FG_FRACTION: 0.25 10 | FG_THRESH: !!python/tuple [0.7, 0.5, 0.5] 11 | BG_THRESH_HI: !!python/tuple [0.7, 0.5, 0.5] 12 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1] 13 | BBOX_THRESH: !!python/tuple [0.7, 0.5, 0.5] 14 | ROI_THRESHOLD: 0.01 15 | SNAPSHOT_INFIX: kitti 16 | TEST: 17 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 18 | NUM_PER_OCTAVE: 4 19 | NMS: 0.5 20 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/kitti_rcnn_msr_fix.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: kitti 2 | IS_RPN: False 3 | IS_MULTISCALE: False 4 | REGION_PROPOSAL: 'RPN_MSR_FIX' 5 | TRAIN: 6 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 7 | NUM_PER_OCTAVE: 4 8 | IMS_PER_BATCH: 2 9 | FG_FRACTION: 0.25 10 | FG_THRESH: !!python/tuple [0.7, 0.5, 0.5] 11 | BG_THRESH_HI: !!python/tuple [0.7, 0.5, 0.5] 12 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1] 13 | BBOX_THRESH: !!python/tuple [0.7, 0.5, 0.5] 14 | ROI_THRESHOLD: 0.01 15 | SNAPSHOT_INFIX: kitti 16 | TEST: 17 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 18 | NUM_PER_OCTAVE: 4 19 | NMS: 0.5 20 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/kitti_rcnn_msr_multiscale.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: kitti 2 | IS_RPN: False 3 | IS_MULTISCALE: True 4 | REGION_PROPOSAL: 'RPN_MSR' 5 | TRAIN: 6 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 7 | NUM_PER_OCTAVE: 4 8 | IMS_PER_BATCH: 2 9 | FG_FRACTION: 0.25 10 | FG_THRESH: !!python/tuple [0.7, 0.5, 0.5] 11 | BG_THRESH_HI: !!python/tuple [0.7, 0.5, 0.5] 12 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1] 13 | BBOX_THRESH: !!python/tuple [0.7, 0.5, 0.5] 14 | ROI_THRESHOLD: 0.01 15 | SNAPSHOT_INFIX: kitti 16 | TEST: 17 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 18 | NUM_PER_OCTAVE: 4 19 | NMS: 0.5 20 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/kitti_rcnn_msr_multiscale_fix.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: kitti 2 | IS_RPN: False 3 | IS_MULTISCALE: True 4 | REGION_PROPOSAL: 'RPN_MSR_MULTISCALE_FIX' 5 | TRAIN: 6 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 7 | NUM_PER_OCTAVE: 4 8 | IMS_PER_BATCH: 2 9 | FG_FRACTION: 0.25 10 | FG_THRESH: !!python/tuple [0.7, 0.5, 0.5] 11 | BG_THRESH_HI: !!python/tuple [0.7, 0.5, 0.5] 12 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1] 13 | BBOX_THRESH: !!python/tuple [0.7, 0.5, 0.5] 14 | ROI_THRESHOLD: 0.01 15 | SNAPSHOT_INFIX: kitti 16 | TEST: 17 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 18 | NUM_PER_OCTAVE: 4 19 | NMS: 0.5 20 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/kitti_rcnn_multiscale.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: kitti 2 | IS_RPN: False 3 | IS_MULTISCALE: True 4 | REGION_PROPOSAL: 'RPN' 5 | TRAIN: 6 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 7 | NUM_PER_OCTAVE: 4 8 | IMS_PER_BATCH: 2 9 | FG_FRACTION: 0.25 10 | FG_THRESH: !!python/tuple [0.7, 0.5, 0.5] 11 | BG_THRESH_HI: !!python/tuple [0.7, 0.5, 0.5] 12 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1] 13 | BBOX_THRESH: !!python/tuple [0.7, 0.5, 0.5] 14 | ROI_THRESHOLD: 0.01 15 | SNAPSHOT_INFIX: kitti 16 | TEST: 17 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 18 | NUM_PER_OCTAVE: 4 19 | NMS: 0.5 20 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/kitti_rcnn_multiscale_6k8k.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: kitti 2 | IS_RPN: False 3 | IS_MULTISCALE: True 4 | REGION_PROPOSAL: 'RPN_6k8k' 5 | TRAIN: 6 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 7 | NUM_PER_OCTAVE: 4 8 | IMS_PER_BATCH: 2 9 | FG_FRACTION: 0.25 10 | FG_THRESH: !!python/tuple [0.7, 0.5, 0.5] 11 | BG_THRESH_HI: !!python/tuple [0.7, 0.5, 0.5] 12 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1] 13 | BBOX_THRESH: !!python/tuple [0.7, 0.5, 0.5] 14 | ROI_THRESHOLD: 0.01 15 | SNAPSHOT_INFIX: kitti 16 | TEST: 17 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 18 | NUM_PER_OCTAVE: 4 19 | NMS: 0.5 20 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/kitti_rcnn_noextra.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: kitti 2 | IS_RPN: False 3 | IS_MULTISCALE: True 4 | IS_EXTRAPOLATING: False 5 | REGION_PROPOSAL: 'RPN' 6 | TRAIN: 7 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 8 | NUM_PER_OCTAVE: 4 9 | IMS_PER_BATCH: 2 10 | FG_FRACTION: 0.25 11 | FG_THRESH: !!python/tuple [0.7, 0.5, 0.5] 12 | BG_THRESH_HI: !!python/tuple [0.7, 0.5, 0.5] 13 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1] 14 | BBOX_THRESH: !!python/tuple [0.7, 0.5, 0.5] 15 | ROI_THRESHOLD: 0.01 16 | SNAPSHOT_INFIX: kitti 17 | TEST: 18 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 19 | NUM_PER_OCTAVE: 4 20 | NMS: 0.5 21 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/kitti_rcnn_original.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: kitti 2 | IS_RPN: False 3 | IS_MULTISCALE: False 4 | IS_EXTRAPOLATING: False 5 | REGION_PROPOSAL: 'RPN' 6 | TRAIN: 7 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 8 | NUM_PER_OCTAVE: 4 9 | IMS_PER_BATCH: 2 10 | FG_FRACTION: 0.25 11 | FG_THRESH: !!python/tuple [0.7, 0.5, 0.5] 12 | BG_THRESH_HI: !!python/tuple [0.7, 0.5, 0.5] 13 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1] 14 | BBOX_THRESH: !!python/tuple [0.7, 0.5, 0.5] 15 | ROI_THRESHOLD: 0.01 16 | SNAPSHOT_INFIX: kitti 17 | SUBCLS: False 18 | TEST: 19 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 20 | NUM_PER_OCTAVE: 4 21 | NMS: 0.5 22 | SUBCLS: False 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/kitti_rcnn_original_msr.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: kitti 2 | IS_RPN: False 3 | IS_MULTISCALE: False 4 | IS_EXTRAPOLATING: False 5 | REGION_PROPOSAL: 'RPN_MSR' 6 | TRAIN: 7 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 8 | NUM_PER_OCTAVE: 4 9 | IMS_PER_BATCH: 2 10 | FG_FRACTION: 0.25 11 | FG_THRESH: !!python/tuple [0.7, 0.5, 0.5] 12 | BG_THRESH_HI: !!python/tuple [0.7, 0.5, 0.5] 13 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1] 14 | BBOX_THRESH: !!python/tuple [0.7, 0.5, 0.5] 15 | ROI_THRESHOLD: 0.01 16 | SNAPSHOT_INFIX: kitti 17 | SUBCLS: False 18 | TEST: 19 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 20 | NUM_PER_OCTAVE: 4 21 | NMS: 0.5 22 | SUBCLS: False 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/kitti_rcnn_original_multiscale.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: kitti 2 | IS_RPN: False 3 | IS_MULTISCALE: True 4 | IS_EXTRAPOLATING: True 5 | REGION_PROPOSAL: 'RPN' 6 | TRAIN: 7 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 8 | NUM_PER_OCTAVE: 4 9 | IMS_PER_BATCH: 2 10 | FG_FRACTION: 0.25 11 | FG_THRESH: !!python/tuple [0.7, 0.5, 0.5] 12 | BG_THRESH_HI: !!python/tuple [0.7, 0.5, 0.5] 13 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1] 14 | BBOX_THRESH: !!python/tuple [0.7, 0.5, 0.5] 15 | ROI_THRESHOLD: 0.01 16 | SNAPSHOT_INFIX: kitti 17 | SUBCLS: False 18 | TEST: 19 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 20 | NUM_PER_OCTAVE: 4 21 | NMS: 0.5 22 | SUBCLS: False 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/kitti_rcnn_vgg16_multiscale_6k8k.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: kitti 2 | IS_RPN: False 3 | IS_MULTISCALE: True 4 | REGION_PROPOSAL: 'RPN_6k8k' 5 | TRAIN: 6 | SCALES_BASE: !!python/tuple [3.0] 7 | NUM_PER_OCTAVE: 1 8 | IMS_PER_BATCH: 1 9 | FG_FRACTION: 0.25 10 | FG_THRESH: !!python/tuple [0.7, 0.5, 0.5] 11 | BG_THRESH_HI: !!python/tuple [0.7, 0.5, 0.5] 12 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1] 13 | BBOX_THRESH: !!python/tuple [0.7, 0.5, 0.5] 14 | ROI_THRESHOLD: 0.01 15 | SNAPSHOT_INFIX: kitti 16 | TEST: 17 | SCALES_BASE: !!python/tuple [3.0] 18 | NUM_PER_OCTAVE: 1 19 | NMS: 0.5 20 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/kitti_rpn.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: kitti 2 | IS_RPN: True 3 | TRAIN: 4 | SCALES_BASE: !!python/tuple [0.25, 0.5, 1.0, 2.0, 3.0] 5 | NUM_PER_OCTAVE: 4 6 | ASPECTS: !!python/tuple [3.0, 2.0, 1.5, 1.0, 0.75, 0.5, 0.25] 7 | IMS_PER_BATCH: 1 8 | BATCH_SIZE: 128 9 | FG_FRACTION: 0.5 10 | FG_THRESH: !!python/tuple [0.7, 0.7, 0.7] 11 | BG_THRESH_HI: !!python/tuple [0.7, 0.7, 0.7] 12 | BG_THRESH_LO: !!python/tuple [0.0, 0.0, 0.0] 13 | BBOX_THRESH: !!python/tuple [0.7, 0.7, 0.7] 14 | SNAPSHOT_INFIX: kitti 15 | BBOX_REG: True 16 | SNAPSHOT_ITERS: 10000 17 | TEST: 18 | SCALES_BASE: !!python/tuple [0.25, 0.5, 1.0, 2.0, 3.0] 19 | NUM_PER_OCTAVE: 4 20 | ASPECTS: !!python/tuple [3.0, 2.0, 1.5, 1.0, 0.75, 0.5, 0.25] 21 | NMS: 0.5 22 | ROI_THRESHOLD: 0.01 23 | BBOX_REG: True 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/kitti_rpn_2d.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: kitti 2 | IS_RPN: True 3 | SUBCLS_NAME: '2d_exemplars' 4 | TRAIN: 5 | SCALES_BASE: !!python/tuple [0.25, 0.5, 1.0, 2.0, 3.0] 6 | NUM_PER_OCTAVE: 4 7 | ASPECTS: !!python/tuple [3.0, 2.0, 1.5, 1.0, 0.75, 0.5, 0.25] 8 | IMS_PER_BATCH: 1 9 | BATCH_SIZE: 128 10 | FG_FRACTION: 0.5 11 | FG_THRESH: !!python/tuple [0.7, 0.7, 0.7] 12 | BG_THRESH_HI: !!python/tuple [0.7, 0.7, 0.7] 13 | BG_THRESH_LO: !!python/tuple [0.0, 0.0, 0.0] 14 | BBOX_THRESH: !!python/tuple [0.7, 0.7, 0.7] 15 | SNAPSHOT_INFIX: kitti 16 | BBOX_REG: True 17 | SNAPSHOT_ITERS: 10000 18 | TEST: 19 | SCALES_BASE: !!python/tuple [0.25, 0.5, 1.0, 2.0, 3.0] 20 | NUM_PER_OCTAVE: 4 21 | ASPECTS: !!python/tuple [3.0, 2.0, 1.5, 1.0, 0.75, 0.5, 0.25] 22 | NMS: 0.5 23 | ROI_THRESHOLD: 0.01 24 | BBOX_REG: True 25 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/kitti_rpn_fix.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: kitti 2 | IS_RPN: True 3 | TRAIN: 4 | SCALES_BASE: !!python/tuple [0.25, 0.5, 1.0, 2.0, 3.0] 5 | NUM_PER_OCTAVE: 4 6 | ASPECTS: !!python/tuple [3.0, 2.0, 1.5, 1.0, 0.75, 0.5, 0.25] 7 | IMS_PER_BATCH: 1 8 | BATCH_SIZE: 128 9 | FG_FRACTION: 0.5 10 | FG_THRESH: !!python/tuple [0.7, 0.7, 0.7] 11 | BG_THRESH_HI: !!python/tuple [0.7, 0.7, 0.7] 12 | BG_THRESH_LO: !!python/tuple [0.0, 0.0, 0.0] 13 | BBOX_THRESH: !!python/tuple [0.7, 0.7, 0.7] 14 | SNAPSHOT_INFIX: kitti 15 | BBOX_REG: True 16 | SNAPSHOT_ITERS: 10000 17 | TEST: 18 | SCALES_BASE: !!python/tuple [0.25, 0.5, 1.0, 2.0, 3.0] 19 | NUM_PER_OCTAVE: 4 20 | ASPECTS: !!python/tuple [3.0, 2.0, 1.5, 1.0, 0.75, 0.5, 0.25] 21 | NMS: 0.5 22 | ROI_THRESHOLD: 0.01 23 | BBOX_REG: True 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/kitti_rpn_msr.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: kitti 2 | IS_RPN: True 3 | IS_MULTISCALE: False 4 | TRAIN: 5 | SCALES_BASE: !!python/tuple [3.0] 6 | IMS_PER_BATCH: 1 7 | FG_THRESH: !!python/tuple [0.7, 0.7, 0.7] 8 | SNAPSHOT_INFIX: kitti 9 | BBOX_REG: False 10 | SNAPSHOT_ITERS: 10000 11 | TEST: 12 | SCALES_BASE: !!python/tuple [3.0] 13 | NMS: 0.5 14 | BBOX_REG: False 15 | RPN_PRE_NMS_TOP_N: 60000 16 | RPN_POST_NMS_TOP_N: 2000 17 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/kitti_tracking_multiscale_6k8k.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: kitti_tracking 2 | IS_RPN: False 3 | IS_MULTISCALE: True 4 | REGION_PROPOSAL: 'RPN_6k8k' 5 | TRAIN: 6 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 7 | NUM_PER_OCTAVE: 4 8 | IMS_PER_BATCH: 2 9 | FG_FRACTION: 0.25 10 | FG_THRESH: !!python/tuple [0.7, 0.5, 0.5] 11 | BG_THRESH_HI: !!python/tuple [0.7, 0.5, 0.5] 12 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1] 13 | BBOX_THRESH: !!python/tuple [0.7, 0.5, 0.5] 14 | ROI_THRESHOLD: 0.01 15 | SNAPSHOT_INFIX: kitti 16 | TEST: 17 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 18 | NUM_PER_OCTAVE: 4 19 | NMS: 0.5 20 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/kitti_tracking_multiscale_train.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: kitti_tracking 2 | IS_RPN: False 3 | IS_MULTISCALE: True 4 | REGION_PROPOSAL: 'RPN' 5 | TRAIN: 6 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 7 | NUM_PER_OCTAVE: 4 8 | IMS_PER_BATCH: 2 9 | FG_FRACTION: 0.25 10 | FG_THRESH: !!python/tuple [0.7, 0.5, 0.5] 11 | BG_THRESH_HI: !!python/tuple [0.7, 0.5, 0.5] 12 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1] 13 | BBOX_THRESH: !!python/tuple [0.7, 0.5, 0.5] 14 | ROI_THRESHOLD: 0.01 15 | SNAPSHOT_INFIX: kitti 16 | TEST: 17 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 18 | NUM_PER_OCTAVE: 4 19 | NMS: 0.5 20 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/kitti_tracking_multiscale_vgg16.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: kitti_tracking 2 | IS_RPN: False 3 | IS_MULTISCALE: True 4 | REGION_PROPOSAL: 'RPN' 5 | TRAIN: 6 | SCALES_BASE: !!python/tuple [3.0] 7 | NUM_PER_OCTAVE: 1 8 | IMS_PER_BATCH: 1 9 | FG_FRACTION: 0.25 10 | FG_THRESH: !!python/tuple [0.7, 0.5, 0.5] 11 | BG_THRESH_HI: !!python/tuple [0.7, 0.5, 0.5] 12 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1] 13 | BBOX_THRESH: !!python/tuple [0.7, 0.5, 0.5] 14 | ROI_THRESHOLD: 0.01 15 | SNAPSHOT_INFIX: kitti 16 | TEST: 17 | SCALES_BASE: !!python/tuple [3.0] 18 | NUM_PER_OCTAVE: 1 19 | NMS: 0.5 20 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/kitti_tracking_rpn.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: kitti_tracking 2 | IS_RPN: True 3 | TRAIN: 4 | SCALES_BASE: !!python/tuple [0.25, 0.5, 1.0, 2.0, 3.0] 5 | NUM_PER_OCTAVE: 4 6 | ASPECTS: !!python/tuple [3.0, 2.0, 1.5, 1.0, 0.75, 0.5, 0.25] 7 | IMS_PER_BATCH: 1 8 | BATCH_SIZE: 128 9 | FG_FRACTION: 0.5 10 | FG_THRESH: !!python/tuple [0.7, 0.7, 0.7] 11 | BG_THRESH_HI: !!python/tuple [0.7, 0.7, 0.7] 12 | BG_THRESH_LO: !!python/tuple [0.0, 0.0, 0.0] 13 | BBOX_THRESH: !!python/tuple [0.7, 0.7, 0.7] 14 | SNAPSHOT_INFIX: kitti 15 | BBOX_REG: True 16 | SNAPSHOT_ITERS: 10000 17 | TEST: 18 | SCALES_BASE: !!python/tuple [0.25, 0.5, 1.0, 2.0, 3.0] 19 | NUM_PER_OCTAVE: 4 20 | ASPECTS: !!python/tuple [3.0, 2.0, 1.5, 1.0, 0.75, 0.5, 0.25] 21 | NMS: 0.5 22 | ROI_THRESHOLD: 0.01 23 | BBOX_REG: True 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/mot_rpn.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: mot 2 | IS_RPN: True 3 | TRAIN: 4 | SCALES_BASE: !!python/tuple [0.125, 0.25, 0.5, 1.0, 2.0] 5 | NUM_PER_OCTAVE: 4 6 | ASPECTS: !!python/tuple [4.0, 3.5, 3.0, 2.5, 2.0, 1.5, 1.0] 7 | IMS_PER_BATCH: 1 8 | BATCH_SIZE: 128 9 | FG_FRACTION: 0.5 10 | FG_THRESH: !!python/tuple [0.7] 11 | BG_THRESH_HI: !!python/tuple [0.7] 12 | BG_THRESH_LO: !!python/tuple [0.0] 13 | BBOX_THRESH: !!python/tuple [0.7] 14 | SNAPSHOT_INFIX: mot 15 | BBOX_REG: True 16 | SNAPSHOT_ITERS: 10000 17 | TEST: 18 | SCALES_BASE: !!python/tuple [0.125, 0.25, 0.5, 1.0, 2.0] 19 | NUM_PER_OCTAVE: 4 20 | ASPECTS: !!python/tuple [4.0, 3.5, 3.0, 2.5, 2.0, 1.5, 1.0] 21 | NMS: 0.5 22 | ROI_THRESHOLD: 0.02 23 | ROI_NUM: 4000 24 | BBOX_REG: True 25 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/mot_tracking_multiscale.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: mot 2 | IS_RPN: False 3 | IS_MULTISCALE: True 4 | REGION_PROPOSAL: 'RPN' 5 | TRAIN: 6 | SCALES_BASE: !!python/tuple [1.0, 2.0] 7 | NUM_PER_OCTAVE: 4 8 | IMS_PER_BATCH: 2 9 | FG_FRACTION: 0.25 10 | FG_THRESH: !!python/tuple [0.5] 11 | BG_THRESH_HI: !!python/tuple [0.5] 12 | BG_THRESH_LO: !!python/tuple [0.1] 13 | BBOX_THRESH: !!python/tuple [0.5] 14 | ROI_THRESHOLD: 0.01 15 | SNAPSHOT_INFIX: mot 16 | TEST: 17 | SCALES_BASE: !!python/tuple [1.0, 2.0] 18 | NUM_PER_OCTAVE: 4 19 | NMS: 0.5 20 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/mot_tracking_multiscale_vgg16.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: mot 2 | IS_RPN: False 3 | IS_MULTISCALE: True 4 | REGION_PROPOSAL: 'RPN' 5 | TRAIN: 6 | SCALES_BASE: !!python/tuple [1.5] 7 | NUM_PER_OCTAVE: 1 8 | IMS_PER_BATCH: 1 9 | FG_FRACTION: 0.25 10 | FG_THRESH: !!python/tuple [0.5] 11 | BG_THRESH_HI: !!python/tuple [0.5] 12 | BG_THRESH_LO: !!python/tuple [0.1] 13 | BBOX_THRESH: !!python/tuple [0.5] 14 | ROI_THRESHOLD: 0.01 15 | SNAPSHOT_INFIX: mot 16 | TEST: 17 | SCALES_BASE: !!python/tuple [1.5] 18 | NUM_PER_OCTAVE: 1 19 | NMS: 0.5 20 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/nissan_multiscale_6k8k.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: nissan 2 | IS_RPN: False 3 | IS_MULTISCALE: True 4 | REGION_PROPOSAL: 'RPN_6k8k' 5 | TRAIN: 6 | SCALES_BASE: !!python/tuple [3.0] 7 | NUM_PER_OCTAVE: 1 8 | IMS_PER_BATCH: 1 9 | FG_FRACTION: 0.25 10 | FG_THRESH: !!python/tuple [0.7, 0.5, 0.5] 11 | BG_THRESH_HI: !!python/tuple [0.7, 0.5, 0.5] 12 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1] 13 | BBOX_THRESH: !!python/tuple [0.7, 0.5, 0.5] 14 | ROI_THRESHOLD: 0.01 15 | SNAPSHOT_INFIX: kitti 16 | TEST: 17 | SCALES_BASE: !!python/tuple [3.0] 18 | NUM_PER_OCTAVE: 1 19 | NMS: 0.5 20 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/nissan_rpn.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: nissan 2 | IS_RPN: True 3 | TRAIN: 4 | SCALES_BASE: !!python/tuple [0.25, 0.5, 1.0, 2.0, 3.0] 5 | NUM_PER_OCTAVE: 4 6 | ASPECTS: !!python/tuple [3.0, 2.0, 1.5, 1.0, 0.75, 0.5, 0.25] 7 | IMS_PER_BATCH: 1 8 | BATCH_SIZE: 128 9 | FG_FRACTION: 0.5 10 | FG_THRESH: !!python/tuple [0.7, 0.7, 0.7] 11 | BG_THRESH_HI: !!python/tuple [0.7, 0.7, 0.7] 12 | BG_THRESH_LO: !!python/tuple [0.0, 0.0, 0.0] 13 | BBOX_THRESH: !!python/tuple [0.7, 0.7, 0.7] 14 | SNAPSHOT_INFIX: kitti 15 | BBOX_REG: True 16 | SNAPSHOT_ITERS: 10000 17 | TEST: 18 | SCALES_BASE: !!python/tuple [0.25, 0.5, 1.0, 2.0, 3.0] 19 | NUM_PER_OCTAVE: 4 20 | ASPECTS: !!python/tuple [3.0, 2.0, 1.5, 1.0, 0.75, 0.5, 0.25] 21 | NMS: 0.5 22 | ROI_THRESHOLD: 0.01 23 | BBOX_REG: True 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/nthu_multiscale_6k8k.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: nthu 2 | IS_RPN: False 3 | IS_MULTISCALE: True 4 | REGION_PROPOSAL: 'RPN_6k8k' 5 | TRAIN: 6 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 7 | NUM_PER_OCTAVE: 4 8 | IMS_PER_BATCH: 2 9 | FG_FRACTION: 0.25 10 | FG_THRESH: !!python/tuple [0.7, 0.5, 0.5] 11 | BG_THRESH_HI: !!python/tuple [0.7, 0.5, 0.5] 12 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1] 13 | BBOX_THRESH: !!python/tuple [0.7, 0.5, 0.5] 14 | ROI_THRESHOLD: 0.01 15 | SNAPSHOT_INFIX: kitti 16 | TEST: 17 | SCALES_BASE: !!python/tuple [1.0, 2.0, 3.0, 4.0] 18 | NUM_PER_OCTAVE: 4 19 | NMS: 0.5 20 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/nthu_rpn.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: nthu 2 | IS_RPN: True 3 | TRAIN: 4 | SCALES_BASE: !!python/tuple [0.25, 0.5, 1.0, 2.0, 3.0] 5 | NUM_PER_OCTAVE: 4 6 | ASPECTS: !!python/tuple [3.0, 2.0, 1.5, 1.0, 0.75, 0.5, 0.25] 7 | IMS_PER_BATCH: 1 8 | BATCH_SIZE: 128 9 | FG_FRACTION: 0.5 10 | FG_THRESH: !!python/tuple [0.7, 0.7, 0.7] 11 | BG_THRESH_HI: !!python/tuple [0.7, 0.7, 0.7] 12 | BG_THRESH_LO: !!python/tuple [0.0, 0.0, 0.0] 13 | BBOX_THRESH: !!python/tuple [0.7, 0.7, 0.7] 14 | SNAPSHOT_INFIX: kitti 15 | BBOX_REG: True 16 | SNAPSHOT_ITERS: 10000 17 | TEST: 18 | SCALES_BASE: !!python/tuple [0.25, 0.5, 1.0, 2.0, 3.0] 19 | NUM_PER_OCTAVE: 4 20 | ASPECTS: !!python/tuple [3.0, 2.0, 1.5, 1.0, 0.75, 0.5, 0.25] 21 | NMS: 0.5 22 | ROI_THRESHOLD: 0.01 23 | BBOX_REG: True 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/pascal3d_rcnn.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: pascal3d 2 | IS_RPN: False 3 | IS_MULTISCALE: False 4 | IS_EXTRAPOLATING: False 5 | REGION_PROPOSAL: 'RPN_6k8k' 6 | TRAIN: 7 | SCALES_BASE: !!python/tuple [1.0, 2.0] 8 | NUM_PER_OCTAVE: 4 9 | IMS_PER_BATCH: 2 10 | FG_FRACTION: 0.25 11 | FG_THRESH: !!python/tuple [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5] 12 | BG_THRESH_HI: !!python/tuple [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5] 13 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1] 14 | BBOX_THRESH: !!python/tuple [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5] 15 | ROI_THRESHOLD: 0.01 16 | SNAPSHOT_INFIX: pascal3d 17 | SNAPSHOT_ITERS: 10000 18 | TEST: 19 | SCALES_BASE: !!python/tuple [1.0, 2.0] 20 | NUM_PER_OCTAVE: 4 21 | NMS: 0.5 22 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/pascal3d_rcnn_multiscale.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: pascal3d 2 | IS_RPN: False 3 | IS_MULTISCALE: True 4 | IS_EXTRAPOLATING: True 5 | REGION_PROPOSAL: 'RPN_6k8k' 6 | TRAIN: 7 | SCALES_BASE: !!python/tuple [1.0, 2.0] 8 | NUM_PER_OCTAVE: 4 9 | IMS_PER_BATCH: 2 10 | FG_FRACTION: 0.25 11 | FG_THRESH: !!python/tuple [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5] 12 | BG_THRESH_HI: !!python/tuple [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5] 13 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1] 14 | BBOX_THRESH: !!python/tuple [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5] 15 | ROI_THRESHOLD: 0.01 16 | SNAPSHOT_INFIX: pascal3d 17 | SNAPSHOT_ITERS: 10000 18 | TEST: 19 | SCALES_BASE: !!python/tuple [1.0, 2.0] 20 | NUM_PER_OCTAVE: 4 21 | NMS: 0.5 22 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/pascal3d_rcnn_original.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: pascal3d 2 | IS_RPN: False 3 | IS_MULTISCALE: False 4 | IS_EXTRAPOLATING: False 5 | REGION_PROPOSAL: 'RPN' 6 | TRAIN: 7 | SCALES_BASE: !!python/tuple [1.0, 2.0] 8 | NUM_PER_OCTAVE: 4 9 | IMS_PER_BATCH: 2 10 | FG_FRACTION: 0.25 11 | FG_THRESH: !!python/tuple [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5] 12 | BG_THRESH_HI: !!python/tuple [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5] 13 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1] 14 | BBOX_THRESH: !!python/tuple [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5] 15 | ROI_THRESHOLD: 0.01 16 | SNAPSHOT_INFIX: pascal3d 17 | SNAPSHOT_ITERS: 10000 18 | SUBCLS: False 19 | TEST: 20 | SCALES_BASE: !!python/tuple [1.0, 2.0] 21 | NUM_PER_OCTAVE: 4 22 | NMS: 0.5 23 | SUBCLS: False 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/pascal3d_rcnn_pose.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: pascal3d 2 | IS_RPN: False 3 | IS_MULTISCALE: False 4 | IS_EXTRAPOLATING: False 5 | REGION_PROPOSAL: 'RPN_6k8k' 6 | SUBCLS_NAME: 'pose_exemplars' 7 | TRAIN: 8 | SCALES_BASE: !!python/tuple [1.0, 2.0] 9 | NUM_PER_OCTAVE: 4 10 | IMS_PER_BATCH: 2 11 | FG_FRACTION: 0.25 12 | FG_THRESH: !!python/tuple [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5] 13 | BG_THRESH_HI: !!python/tuple [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5] 14 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1] 15 | BBOX_THRESH: !!python/tuple [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5] 16 | ROI_THRESHOLD: 0.01 17 | SNAPSHOT_INFIX: pascal3d 18 | SNAPSHOT_ITERS: 10000 19 | TEST: 20 | SCALES_BASE: !!python/tuple [1.0, 2.0] 21 | NUM_PER_OCTAVE: 4 22 | NMS: 0.5 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/pascal3d_rcnn_pose_multiscale.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: pascal3d 2 | IS_RPN: False 3 | IS_MULTISCALE: True 4 | IS_EXTRAPOLATING: True 5 | REGION_PROPOSAL: 'RPN_6k8k' 6 | SUBCLS_NAME: 'pose_exemplars' 7 | TRAIN: 8 | SCALES_BASE: !!python/tuple [1.0, 2.0] 9 | NUM_PER_OCTAVE: 4 10 | IMS_PER_BATCH: 2 11 | FG_FRACTION: 0.25 12 | FG_THRESH: !!python/tuple [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5] 13 | BG_THRESH_HI: !!python/tuple [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5] 14 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1] 15 | BBOX_THRESH: !!python/tuple [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5] 16 | ROI_THRESHOLD: 0.01 17 | SNAPSHOT_INFIX: pascal3d 18 | SNAPSHOT_ITERS: 10000 19 | TEST: 20 | SCALES_BASE: !!python/tuple [1.0, 2.0] 21 | NUM_PER_OCTAVE: 4 22 | NMS: 0.5 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/pascal3d_rpn.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: pascal3d 2 | IS_RPN: True 3 | TRAIN: 4 | SCALES_BASE: !!python/tuple [0.25, 0.5, 1.0, 2.0] 5 | NUM_PER_OCTAVE: 5 6 | ASPECTS: !!python/tuple [3.0, 2.0, 1.0, 0.5, 0.25] 7 | IMS_PER_BATCH: 1 8 | BATCH_SIZE: 128 9 | FG_FRACTION: 0.5 10 | FG_THRESH: !!python/tuple [0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7] 11 | BG_THRESH_HI: !!python/tuple [0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7] 12 | BG_THRESH_LO: !!python/tuple [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 13 | BBOX_THRESH: !!python/tuple [0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7] 14 | SNAPSHOT_INFIX: pascal3d 15 | BBOX_REG: True 16 | SNAPSHOT_ITERS: 10000 17 | TEST: 18 | SCALES_BASE: !!python/tuple [0.25, 0.5, 1.0, 2.0] 19 | NUM_PER_OCTAVE: 5 20 | ASPECTS: !!python/tuple [3.0, 2.0, 1.0, 0.5, 0.25] 21 | NMS: 0.5 22 | ROI_THRESHOLD: 0.005 23 | ROI_NUM: 2000 24 | BBOX_REG: True 25 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/pascal3d_rpn_msr_vgg16.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: pascal3d 2 | IS_RPN: True 3 | IS_MULTISCALE: False 4 | NET_NAME: 'VGG16' 5 | TRAIN: 6 | SCALES_BASE: !!python/tuple [2.0] 7 | IMS_PER_BATCH: 1 8 | BATCH_SIZE: 128 9 | FG_THRESH: !!python/tuple [0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7] 10 | SNAPSHOT_INFIX: pascal3d 11 | BBOX_REG: False 12 | SUBCLS: False 13 | SNAPSHOT_ITERS: 10000 14 | RPN_ASPECTS: !!python/tuple [0.5, 1, 2] 15 | RPN_SCALES: !!python/tuple [8, 16, 32] 16 | TEST: 17 | SCALES_BASE: !!python/tuple [2.0] 18 | NMS: 0.5 19 | BBOX_REG: False 20 | SUBCLS: False 21 | RPN_PRE_NMS_TOP_N: 80000 22 | RPN_POST_NMS_TOP_N: 2000 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/pascal3d_rpn_vgg16.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: pascal3d 2 | IS_RPN: True 3 | NET_NAME: 'VGG16' 4 | TRAIN: 5 | SCALES_BASE: !!python/tuple [0.25, 0.5, 1.0, 2.0] 6 | NUM_PER_OCTAVE: 5 7 | ASPECTS: !!python/tuple [3.0, 2.0, 1.0, 0.5, 0.25] 8 | IMS_PER_BATCH: 1 9 | BATCH_SIZE: 128 10 | FG_FRACTION: 0.5 11 | FG_THRESH: !!python/tuple [0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7] 12 | BG_THRESH_HI: !!python/tuple [0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7] 13 | BG_THRESH_LO: !!python/tuple [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 14 | BBOX_THRESH: !!python/tuple [0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7] 15 | SNAPSHOT_INFIX: pascal3d 16 | BBOX_REG: True 17 | SNAPSHOT_ITERS: 10000 18 | TEST: 19 | SCALES_BASE: !!python/tuple [0.25, 0.5, 1.0, 2.0] 20 | NUM_PER_OCTAVE: 5 21 | ASPECTS: !!python/tuple [3.0, 2.0, 1.0, 0.5, 0.25] 22 | NMS: 0.5 23 | ROI_THRESHOLD: 0.001 24 | ROI_NUM: 2000 25 | BBOX_REG: True 26 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/pascal_rcnn.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: pascal2007 2 | IS_RPN: False 3 | IS_MULTISCALE: False 4 | IS_EXTRAPOLATING: False 5 | REGION_PROPOSAL: 'RPN' 6 | TRAIN: 7 | SCALES_BASE: !!python/tuple [1.0, 2.0] 8 | NUM_PER_OCTAVE: 4 9 | IMS_PER_BATCH: 2 10 | FG_FRACTION: 0.25 11 | FG_THRESH: !!python/tuple [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5] 12 | BG_THRESH_HI: !!python/tuple [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5] 13 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1] 14 | BBOX_THRESH: !!python/tuple [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5] 15 | ROI_THRESHOLD: 0.01 16 | SNAPSHOT_INFIX: pascal2007 17 | SNAPSHOT_ITERS: 10000 18 | TEST: 19 | SCALES_BASE: !!python/tuple [1.0, 2.0] 20 | NUM_PER_OCTAVE: 4 21 | NMS: 0.5 22 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/pascal_rcnn_original.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: pascal2007 2 | IS_RPN: False 3 | IS_MULTISCALE: False 4 | IS_EXTRAPOLATING: False 5 | REGION_PROPOSAL: 'RPN_VGG' 6 | TRAIN: 7 | SCALES_BASE: !!python/tuple [1.0, 2.0] 8 | NUM_PER_OCTAVE: 4 9 | IMS_PER_BATCH: 2 10 | FG_FRACTION: 0.25 11 | FG_THRESH: !!python/tuple [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5] 12 | BG_THRESH_HI: !!python/tuple [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5] 13 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1] 14 | BBOX_THRESH: !!python/tuple [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5] 15 | ROI_THRESHOLD: 0.01 16 | SNAPSHOT_INFIX: pascal2007 17 | SNAPSHOT_ITERS: 10000 18 | SUBCLS: False 19 | TEST: 20 | SCALES_BASE: !!python/tuple [1.0, 2.0] 21 | NUM_PER_OCTAVE: 4 22 | NMS: 0.5 23 | SUBCLS: False 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/pascal_rcnn_original_multiscale.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: pascal2007 2 | IS_RPN: False 3 | IS_MULTISCALE: True 4 | IS_EXTRAPOLATING: True 5 | REGION_PROPOSAL: 'RPN' 6 | TRAIN: 7 | SCALES_BASE: !!python/tuple [1.0, 2.0] 8 | NUM_PER_OCTAVE: 4 9 | IMS_PER_BATCH: 2 10 | FG_FRACTION: 0.25 11 | FG_THRESH: !!python/tuple [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5] 12 | BG_THRESH_HI: !!python/tuple [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5] 13 | BG_THRESH_LO: !!python/tuple [0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1, 0.1] 14 | BBOX_THRESH: !!python/tuple [0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5, 0.5] 15 | ROI_THRESHOLD: 0.01 16 | SNAPSHOT_INFIX: pascal2007 17 | SNAPSHOT_ITERS: 10000 18 | SUBCLS: False 19 | TEST: 20 | SCALES_BASE: !!python/tuple [1.0, 2.0] 21 | NUM_PER_OCTAVE: 4 22 | NMS: 0.5 23 | SUBCLS: False 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/pascal_rpn.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: pascal2007 2 | IS_RPN: True 3 | TRAIN: 4 | SCALES_BASE: !!python/tuple [0.25, 0.5, 1.0, 2.0] 5 | NUM_PER_OCTAVE: 5 6 | ASPECTS: !!python/tuple [3.0, 2.0, 1.0, 0.5, 0.25] 7 | IMS_PER_BATCH: 1 8 | BATCH_SIZE: 128 9 | FG_FRACTION: 0.5 10 | FG_THRESH: !!python/tuple [0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7] 11 | BG_THRESH_HI: !!python/tuple [0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7] 12 | BG_THRESH_LO: !!python/tuple [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 13 | BBOX_THRESH: !!python/tuple [0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7] 14 | SNAPSHOT_INFIX: pascal2007 15 | BBOX_REG: True 16 | SNAPSHOT_ITERS: 10000 17 | TEST: 18 | SCALES_BASE: !!python/tuple [0.25, 0.5, 1.0, 2.0] 19 | NUM_PER_OCTAVE: 5 20 | ASPECTS: !!python/tuple [3.0, 2.0, 1.0, 0.5, 0.25] 21 | NMS: 0.5 22 | ROI_THRESHOLD: 0.005 23 | ROI_NUM: 2000 24 | BBOX_REG: True 25 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/cfgs/pascal_rpn_vgg16.yml: -------------------------------------------------------------------------------- 1 | EXP_DIR: pascal2007 2 | IS_RPN: True 3 | NET_NAME: 'VGG16' 4 | SUBCLS_NAME: 'subcategory_exemplars' 5 | TRAIN: 6 | SCALES_BASE: !!python/tuple [0.25, 0.5, 1.0, 2.0] 7 | NUM_PER_OCTAVE: 5 8 | ASPECTS: !!python/tuple [3.0, 2.0, 1.0, 0.5, 0.25] 9 | IMS_PER_BATCH: 1 10 | BATCH_SIZE: 128 11 | FG_FRACTION: 0.5 12 | FG_THRESH: !!python/tuple [0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7] 13 | BG_THRESH_HI: !!python/tuple [0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7] 14 | BG_THRESH_LO: !!python/tuple [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] 15 | BBOX_THRESH: !!python/tuple [0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7, 0.7] 16 | SNAPSHOT_INFIX: pascal2007 17 | BBOX_REG: True 18 | SNAPSHOT_ITERS: 10000 19 | TEST: 20 | SCALES_BASE: !!python/tuple [0.25, 0.5, 1.0, 2.0] 21 | NUM_PER_OCTAVE: 5 22 | ASPECTS: !!python/tuple [3.0, 2.0, 1.0, 0.5, 0.25] 23 | NMS: 0.5 24 | ROI_THRESHOLD: 0.005 25 | ROI_NUM: 2000 26 | BBOX_REG: True 27 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/logs/.gitignore: -------------------------------------------------------------------------------- 1 | *.txt* 2 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/imagenet3d_caffenet_rcnn_original_edge_boxes.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/imagenet3d_caffenet_rcnn_original_edge_boxes.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/imagenet3d/solver_rcnn_original.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb imagenet3d_trainval \ 16 | --cfg experiments/cfgs/imagenet3d_rcnn_original_edge_boxes.yml \ 17 | --iters 160000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/CaffeNet/imagenet3d/test_rcnn_original.prototxt \ 21 | --net output/imagenet3d/imagenet3d_trainval/caffenet_fast_rcnn_original_imagenet3d_edge_boxes_iter_160000.caffemodel \ 22 | --imdb imagenet3d_test \ 23 | --cfg experiments/cfgs/imagenet3d_rcnn_original_edge_boxes.yml 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/imagenet3d_caffenet_rcnn_original_mcg.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/imagenet3d_caffenet_rcnn_original_mcg.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/imagenet3d/solver_rcnn_original.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb imagenet3d_trainval \ 16 | --cfg experiments/cfgs/imagenet3d_rcnn_original_mcg.yml \ 17 | --iters 160000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/CaffeNet/imagenet3d/test_rcnn_original.prototxt \ 21 | --net output/imagenet3d/imagenet3d_trainval/caffenet_fast_rcnn_original_imagenet3d_mcg_iter_160000.caffemodel \ 22 | --imdb imagenet3d_test \ 23 | --cfg experiments/cfgs/imagenet3d_rcnn_original_mcg.yml 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/imagenet3d_caffenet_rcnn_original_rpn.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/imagenet3d_caffenet_rcnn_original_rpn.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/imagenet3d/solver_rcnn_original.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb imagenet3d_trainval \ 16 | --cfg experiments/cfgs/imagenet3d_rcnn_original_rpn.yml \ 17 | --iters 160000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/CaffeNet/imagenet3d/test_rcnn_original.prototxt \ 21 | --net output/imagenet3d/imagenet3d_trainval/caffenet_fast_rcnn_original_imagenet3d_rpn_iter_160000.caffemodel \ 22 | --imdb imagenet3d_test \ 23 | --cfg experiments/cfgs/imagenet3d_rcnn_original_rpn.yml 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/imagenet3d_caffenet_rcnn_original_selective_search.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/imagenet3d_caffenet_rcnn_original_selective_search.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/imagenet3d/solver_rcnn_original.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb imagenet3d_trainval \ 16 | --cfg experiments/cfgs/imagenet3d_rcnn_original_selective_search.yml \ 17 | --iters 160000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/CaffeNet/imagenet3d/test_rcnn_original.prototxt \ 21 | --net output/imagenet3d/imagenet3d_trainval/caffenet_fast_rcnn_original_imagenet3d_selective_search_iter_160000.caffemodel \ 22 | --imdb imagenet3d_test \ 23 | --cfg experiments/cfgs/imagenet3d_rcnn_original_selective_search.yml 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/imagenet3d_caffenet_rcnn_view_edge_boxes.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/imagenet3d_caffenet_rcnn_view_edge_boxes.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/imagenet3d/solver_rcnn_view.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb imagenet3d_trainval \ 16 | --cfg experiments/cfgs/imagenet3d_rcnn_view_edge_boxes.yml \ 17 | --iters 160000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/CaffeNet/imagenet3d/test_rcnn_view.prototxt \ 21 | --net output/imagenet3d/imagenet3d_trainval/caffenet_fast_rcnn_view_imagenet3d_edge_boxes_iter_160000.caffemodel \ 22 | --imdb imagenet3d_test \ 23 | --cfg experiments/cfgs/imagenet3d_rcnn_view_edge_boxes.yml 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/imagenet3d_caffenet_rcnn_view_mcg.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/imagenet3d_caffenet_rcnn_view_mcg.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/imagenet3d/solver_rcnn_view.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb imagenet3d_trainval \ 16 | --cfg experiments/cfgs/imagenet3d_rcnn_view_mcg.yml \ 17 | --iters 160000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/CaffeNet/imagenet3d/test_rcnn_view.prototxt \ 21 | --net output/imagenet3d/imagenet3d_trainval/caffenet_fast_rcnn_view_imagenet3d_mcg_iter_160000.caffemodel \ 22 | --imdb imagenet3d_test \ 23 | --cfg experiments/cfgs/imagenet3d_rcnn_view_mcg.yml 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/imagenet3d_caffenet_rcnn_view_rpn.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/imagenet3d_caffenet_rcnn_view_rpn.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/imagenet3d/solver_rcnn_view.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb imagenet3d_trainval \ 16 | --cfg experiments/cfgs/imagenet3d_rcnn_view_rpn.yml \ 17 | --iters 160000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/CaffeNet/imagenet3d/test_rcnn_view.prototxt \ 21 | --net output/imagenet3d/imagenet3d_trainval/caffenet_fast_rcnn_view_imagenet3d_rpn_iter_160000.caffemodel \ 22 | --imdb imagenet3d_test \ 23 | --cfg experiments/cfgs/imagenet3d_rcnn_view_rpn.yml 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/imagenet3d_caffenet_rcnn_view_selective_search.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/imagenet3d_caffenet_rcnn_view_selective_search.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/imagenet3d/solver_rcnn_view.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb imagenet3d_trainval \ 16 | --cfg experiments/cfgs/imagenet3d_rcnn_view_selective_search.yml \ 17 | --iters 160000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/CaffeNet/imagenet3d/test_rcnn_view.prototxt \ 21 | --net output/imagenet3d/imagenet3d_trainval/caffenet_fast_rcnn_view_imagenet3d_selective_search_iter_160000.caffemodel \ 22 | --imdb imagenet3d_test \ 23 | --cfg experiments/cfgs/imagenet3d_rcnn_view_selective_search.yml 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/imagenet3d_caffenet_rcnn_view_selective_search_debug.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/imagenet3d_caffenet_rcnn_view_selective_search_debug.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | #time ./tools/train_net.py --gpu $1 \ 13 | # --solver models/CaffeNet/imagenet3d/solver_rcnn_view.prototxt \ 14 | # --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | # --imdb imagenet3d_debug \ 16 | # --cfg experiments/cfgs/imagenet3d_rcnn_view_selective_search.yml \ 17 | # --iters 200 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/CaffeNet/imagenet3d/test_rcnn_view.prototxt \ 21 | --net output/imagenet3d/imagenet3d_trainval/caffenet_fast_rcnn_view_imagenet3d_selective_search_iter_160000.caffemodel \ 22 | --imdb imagenet3d_debug \ 23 | --cfg experiments/cfgs/imagenet3d_rcnn_view_selective_search.yml 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/imagenet3d_caffenet_rpn_msr_test_1.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/imagenet3d_caffenet_rpn_msr_test_1.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/test_net.py --gpu $1 \ 13 | --def models/CaffeNet/imagenet3d/test_rpn_msr.prototxt \ 14 | --net output/imagenet3d/imagenet3d_trainval/caffenet_fast_rcnn_rpn_msr_imagenet3d_iter_160000.caffemodel \ 15 | --imdb imagenet3d_test_1 \ 16 | --cfg experiments/cfgs/imagenet3d_rpn_msr.yml 17 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/imagenet3d_caffenet_rpn_msr_test_2.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/imagenet3d_caffenet_rpn_msr_test_2.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/test_net.py --gpu $1 \ 13 | --def models/CaffeNet/imagenet3d/test_rpn_msr.prototxt \ 14 | --net output/imagenet3d/imagenet3d_trainval/caffenet_fast_rcnn_rpn_msr_imagenet3d_iter_160000.caffemodel \ 15 | --imdb imagenet3d_test_2 \ 16 | --cfg experiments/cfgs/imagenet3d_rpn_msr.yml 17 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/imagenet3d_caffenet_rpn_msr_test_train.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/imagenet3d_caffenet_rpn_msr_test_train.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/test_net.py --gpu $1 \ 13 | --def models/CaffeNet/imagenet3d/test_rpn_msr.prototxt \ 14 | --net output/imagenet3d/imagenet3d_trainval/caffenet_fast_rcnn_rpn_msr_imagenet3d_iter_160000.caffemodel \ 15 | --imdb imagenet3d_train \ 16 | --cfg experiments/cfgs/imagenet3d_rpn_msr.yml 17 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/imagenet3d_caffenet_rpn_msr_test_val.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/imagenet3d_caffenet_rpn_msr_test_val.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/test_net.py --gpu $1 \ 13 | --def models/CaffeNet/imagenet3d/test_rpn_msr.prototxt \ 14 | --net output/imagenet3d/imagenet3d_trainval/caffenet_fast_rcnn_rpn_msr_imagenet3d_iter_160000.caffemodel \ 15 | --imdb imagenet3d_val \ 16 | --cfg experiments/cfgs/imagenet3d_rpn_msr.yml 17 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/imagenet3d_caffenet_rpn_msr_train.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/imagenet3d_caffenet_rpn_msr_train.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/imagenet3d/solver_rpn_msr.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb imagenet3d_trainval \ 16 | --cfg experiments/cfgs/imagenet3d_rpn_msr.yml \ 17 | --iters 160000 18 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/imagenet3d_vgg16_rcnn_original_edge_boxes.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/imagenet3d_vgg16_rcnn_original_edge_boxes.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/VGG16/imagenet3d/solver_rcnn_original.prototxt \ 14 | --weights data/imagenet_models/VGG16.v2.caffemodel \ 15 | --imdb imagenet3d_trainval \ 16 | --cfg experiments/cfgs/imagenet3d_rcnn_original_edge_boxes.yml \ 17 | --iters 160000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/VGG16/imagenet3d/test_rcnn_original.prototxt \ 21 | --net output/imagenet3d/imagenet3d_trainval/vgg16_fast_rcnn_original_imagenet3d_edge_boxes_iter_160000.caffemodel \ 22 | --imdb imagenet3d_test \ 23 | --cfg experiments/cfgs/imagenet3d_rcnn_original_edge_boxes.yml 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/imagenet3d_vgg16_rcnn_original_mcg.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/imagenet3d_vgg16_rcnn_original_mcg.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/VGG16/imagenet3d/solver_rcnn_original.prototxt \ 14 | --weights data/imagenet_models/VGG16.v2.caffemodel \ 15 | --imdb imagenet3d_trainval \ 16 | --cfg experiments/cfgs/imagenet3d_rcnn_original_mcg.yml \ 17 | --iters 160000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/VGG16/imagenet3d/test_rcnn_original.prototxt \ 21 | --net output/imagenet3d/imagenet3d_trainval/vgg16_fast_rcnn_original_imagenet3d_mcg_iter_160000.caffemodel \ 22 | --imdb imagenet3d_test \ 23 | --cfg experiments/cfgs/imagenet3d_rcnn_original_mcg.yml 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/imagenet3d_vgg16_rcnn_original_rpn.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/imagenet3d_vgg16_rcnn_original_rpn.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/VGG16/imagenet3d/solver_rcnn_original.prototxt \ 14 | --weights data/imagenet_models/VGG16.v2.caffemodel \ 15 | --imdb imagenet3d_trainval \ 16 | --cfg experiments/cfgs/imagenet3d_rcnn_original_rpn_vgg16.yml \ 17 | --iters 160000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/VGG16/imagenet3d/test_rcnn_original.prototxt \ 21 | --net output/imagenet3d/imagenet3d_trainval/vgg16_fast_rcnn_original_imagenet3d_rpn_iter_160000.caffemodel \ 22 | --imdb imagenet3d_test \ 23 | --cfg experiments/cfgs/imagenet3d_rcnn_original_rpn_vgg16.yml 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/imagenet3d_vgg16_rcnn_original_selective_search.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/imagenet3d_vgg16_rcnn_original_selective_search.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/VGG16/imagenet3d/solver_rcnn_original.prototxt \ 14 | --weights data/imagenet_models/VGG16.v2.caffemodel \ 15 | --imdb imagenet3d_trainval \ 16 | --cfg experiments/cfgs/imagenet3d_rcnn_original_selective_search.yml \ 17 | --iters 160000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/VGG16/imagenet3d/test_rcnn_original.prototxt \ 21 | --net output/imagenet3d/imagenet3d_trainval/vgg16_fast_rcnn_original_imagenet3d_selective_search_iter_160000.caffemodel \ 22 | --imdb imagenet3d_test \ 23 | --cfg experiments/cfgs/imagenet3d_rcnn_original_selective_search.yml 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/imagenet3d_vgg16_rcnn_view_edge_boxes.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/imagenet3d_vgg16_rcnn_view_edge_boxes.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/VGG16/imagenet3d/solver_rcnn_view.prototxt \ 14 | --weights data/imagenet_models/VGG16.v2.caffemodel \ 15 | --imdb imagenet3d_trainval \ 16 | --cfg experiments/cfgs/imagenet3d_rcnn_view_edge_boxes.yml \ 17 | --iters 160000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/VGG16/imagenet3d/test_rcnn_view.prototxt \ 21 | --net output/imagenet3d/imagenet3d_trainval/vgg16_fast_rcnn_view_imagenet3d_edge_boxes_iter_160000.caffemodel \ 22 | --imdb imagenet3d_test \ 23 | --cfg experiments/cfgs/imagenet3d_rcnn_view_edge_boxes.yml 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/imagenet3d_vgg16_rcnn_view_mcg.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/imagenet3d_vgg16_rcnn_view_mcg.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/VGG16/imagenet3d/solver_rcnn_view.prototxt \ 14 | --weights data/imagenet_models/VGG16.v2.caffemodel \ 15 | --imdb imagenet3d_trainval \ 16 | --cfg experiments/cfgs/imagenet3d_rcnn_view_mcg.yml \ 17 | --iters 160000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/VGG16/imagenet3d/test_rcnn_view.prototxt \ 21 | --net output/imagenet3d/imagenet3d_trainval/vgg16_fast_rcnn_view_imagenet3d_mcg_iter_160000.caffemodel \ 22 | --imdb imagenet3d_test \ 23 | --cfg experiments/cfgs/imagenet3d_rcnn_view_mcg.yml 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/imagenet3d_vgg16_rcnn_view_rpn.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/imagenet3d_vgg16_rcnn_view_rpn.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/VGG16/imagenet3d/solver_rcnn_view.prototxt \ 14 | --weights data/imagenet_models/VGG16.v2.caffemodel \ 15 | --imdb imagenet3d_trainval \ 16 | --cfg experiments/cfgs/imagenet3d_rcnn_view_rpn_vgg16.yml \ 17 | --iters 160000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/VGG16/imagenet3d/test_rcnn_view.prototxt \ 21 | --net output/imagenet3d/imagenet3d_trainval/vgg16_fast_rcnn_view_imagenet3d_rpn_iter_160000.caffemodel \ 22 | --imdb imagenet3d_test \ 23 | --cfg experiments/cfgs/imagenet3d_rcnn_view_rpn_vgg16.yml 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/imagenet3d_vgg16_rcnn_view_selective_search.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/imagenet3d_vgg16_rcnn_view_selective_search.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/VGG16/imagenet3d/solver_rcnn_view.prototxt \ 14 | --weights data/imagenet_models/VGG16.v2.caffemodel \ 15 | --imdb imagenet3d_trainval \ 16 | --cfg experiments/cfgs/imagenet3d_rcnn_view_selective_search.yml \ 17 | --iters 160000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/VGG16/imagenet3d/test_rcnn_view.prototxt \ 21 | --net output/imagenet3d/imagenet3d_trainval/vgg16_fast_rcnn_view_imagenet3d_selective_search_iter_160000.caffemodel \ 22 | --imdb imagenet3d_test \ 23 | --cfg experiments/cfgs/imagenet3d_rcnn_view_selective_search.yml 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/imagenet3d_vgg16_rpn_msr_test_1.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/imagenet3d_vgg16_rpn_msr_test_1.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/test_net.py --gpu $1 \ 13 | --def models/VGG16/imagenet3d/test_rpn_msr.prototxt \ 14 | --net output/imagenet3d/imagenet3d_trainval/vgg16_fast_rcnn_rpn_msr_imagenet3d_iter_160000.caffemodel \ 15 | --imdb imagenet3d_test_1 \ 16 | --cfg experiments/cfgs/imagenet3d_rpn_msr.yml 17 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/imagenet3d_vgg16_rpn_msr_test_2.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/imagenet3d_vgg16_rpn_msr_test_2.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/test_net.py --gpu $1 \ 13 | --def models/VGG16/imagenet3d/test_rpn_msr.prototxt \ 14 | --net output/imagenet3d/imagenet3d_trainval/vgg16_fast_rcnn_rpn_msr_imagenet3d_iter_160000.caffemodel \ 15 | --imdb imagenet3d_test_2 \ 16 | --cfg experiments/cfgs/imagenet3d_rpn_msr.yml 17 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/imagenet3d_vgg16_rpn_msr_test_train.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/imagenet3d_vgg16_rpn_msr_test_train.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/test_net.py --gpu $1 \ 13 | --def models/VGG16/imagenet3d/test_rpn_msr.prototxt \ 14 | --net output/imagenet3d/imagenet3d_trainval/vgg16_fast_rcnn_rpn_msr_imagenet3d_iter_160000.caffemodel \ 15 | --imdb imagenet3d_train \ 16 | --cfg experiments/cfgs/imagenet3d_rpn_msr.yml 17 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/imagenet3d_vgg16_rpn_msr_test_val.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/imagenet3d_vgg16_rpn_msr_test_val.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/test_net.py --gpu $1 \ 13 | --def models/VGG16/imagenet3d/test_rpn_msr.prototxt \ 14 | --net output/imagenet3d/imagenet3d_trainval/vgg16_fast_rcnn_rpn_msr_imagenet3d_iter_160000.caffemodel \ 15 | --imdb imagenet3d_val \ 16 | --cfg experiments/cfgs/imagenet3d_rpn_msr.yml 17 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/imagenet3d_vgg16_rpn_msr_train.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/imagenet3d_vgg16_rpn_msr_train.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/VGG16/imagenet3d/solver_rpn_msr.prototxt \ 14 | --weights data/imagenet_models/VGG16.v2.caffemodel \ 15 | --imdb imagenet3d_trainval \ 16 | --cfg experiments/cfgs/imagenet3d_rpn_msr.yml \ 17 | --iters 160000 18 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_test_caffenet_rcnn_multiscale.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_test_caffenet_rcnn_multiscale.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/kitti_test/solver_rcnn_multiscale.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb kitti_trainval \ 16 | --cfg experiments/cfgs/kitti_rcnn_multiscale.yml 17 | 18 | time ./tools/test_net.py --gpu $1 \ 19 | --def models/CaffeNet/kitti_test/test_rcnn_multiscale.prototxt \ 20 | --net output/kitti/kitti_trainval/caffenet_fast_rcnn_multiscale_kitti_iter_40000.caffemodel \ 21 | --imdb kitti_test \ 22 | --cfg experiments/cfgs/kitti_rcnn_multiscale.yml 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_test_caffenet_rcnn_multiscale_6k8k.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_test_caffenet_rcnn_multiscale_6k8k.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/kitti_test/solver_rcnn_multiscale_6k8k.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb kitti_trainval \ 16 | --cfg experiments/cfgs/kitti_rcnn_multiscale_6k8k.yml \ 17 | --iters 80000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/CaffeNet/kitti_test/test_rcnn_multiscale.prototxt \ 21 | --net output/kitti/kitti_trainval/caffenet_fast_rcnn_multiscale_6k8k_kitti_iter_80000.caffemodel \ 22 | --imdb kitti_test \ 23 | --cfg experiments/cfgs/kitti_rcnn_multiscale_6k8k.yml 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_test_caffenet_rcnn_original_msr.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_test_caffenet_rcnn_original_msr_6k8k.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | #time ./tools/train_net.py --gpu $1 \ 13 | # --solver models/CaffeNet/kitti_test/solver_rcnn_original_msr_6k8k.prototxt \ 14 | # --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | # --imdb kitti_trainval \ 16 | # --cfg experiments/cfgs/kitti_rcnn_original_msr.yml \ 17 | # --iters 80000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/CaffeNet/kitti_test/test_rcnn_original.prototxt \ 21 | --net output/kitti/kitti_trainval/caffenet_fast_rcnn_original_msr_6k8k_kitti_iter_80000.caffemodel \ 22 | --imdb kitti_test \ 23 | --cfg experiments/cfgs/kitti_rcnn_original_msr.yml 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_test_caffenet_rpn.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_test_caffenet_rpn.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/kitti_test/solver_rpn.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb kitti_trainval \ 16 | --cfg experiments/cfgs/kitti_rpn.yml \ 17 | --iters 40000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/CaffeNet/kitti_test/test_rpn.prototxt \ 21 | --net output/kitti/kitti_trainval/caffenet_fast_rcnn_rpn_kitti_iter_40000.caffemodel \ 22 | --imdb kitti_trainval \ 23 | --cfg experiments/cfgs/kitti_rpn.yml 24 | 25 | time ./tools/test_net.py --gpu $1 \ 26 | --def models/CaffeNet/kitti_test/test_rpn.prototxt \ 27 | --net output/kitti/kitti_trainval/caffenet_fast_rcnn_rpn_kitti_iter_40000.caffemodel \ 28 | --imdb kitti_test \ 29 | --cfg experiments/cfgs/kitti_rpn.yml 30 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_test_caffenet_rpn_6k8k.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_test_caffenet_rpn_6k8k.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/kitti_test/solver_rpn_6k8k.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb kitti_trainval \ 16 | --cfg experiments/cfgs/kitti_rpn.yml \ 17 | --iters 80000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/CaffeNet/kitti_test/test_rpn.prototxt \ 21 | --net output/kitti/kitti_trainval/caffenet_fast_rcnn_rpn_6k8k_kitti_iter_80000.caffemodel \ 22 | --imdb kitti_trainval \ 23 | --cfg experiments/cfgs/kitti_rpn.yml 24 | 25 | time ./tools/test_net.py --gpu $1 \ 26 | --def models/CaffeNet/kitti_test/test_rpn.prototxt \ 27 | --net output/kitti/kitti_trainval/caffenet_fast_rcnn_rpn_6k8k_kitti_iter_80000.caffemodel \ 28 | --imdb kitti_test \ 29 | --cfg experiments/cfgs/kitti_rpn.yml 30 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_test_caffenet_rpn_msr_6k8k.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_test_caffenet_rpn_msr_6k8k.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | #time ./tools/train_net.py --gpu $1 \ 13 | # --solver models/CaffeNet/kitti_test/solver_rpn_msr_6k8k.prototxt \ 14 | # --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | # --imdb kitti_trainval \ 16 | # --cfg experiments/cfgs/kitti_rpn_msr.yml \ 17 | # --iters 80000 18 | 19 | #time ./tools/test_net.py --gpu $1 \ 20 | # --def models/CaffeNet/kitti_test/test_rpn_msr.prototxt \ 21 | # --net output/kitti/kitti_trainval/caffenet_fast_rcnn_rpn_msr_6k8k_kitti_iter_80000.caffemodel \ 22 | # --imdb kitti_trainval \ 23 | # --cfg experiments/cfgs/kitti_rpn_msr.yml 24 | 25 | time ./tools/test_net.py --gpu $1 \ 26 | --def models/CaffeNet/kitti_test/test_rpn_msr.prototxt \ 27 | --net output/kitti/kitti_trainval/caffenet_fast_rcnn_rpn_msr_6k8k_kitti_iter_80000.caffemodel \ 28 | --imdb kitti_test \ 29 | --cfg experiments/cfgs/kitti_rpn_msr.yml 30 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_test_googlenet_rcnn.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_test_google_rcnn.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/GoogleNet/kitti_test/solver_rcnn.prototxt \ 14 | --weights data/imagenet_models/bvlc_googlenet.caffemodel \ 15 | --imdb kitti_trainval \ 16 | --cfg experiments/cfgs/kitti_rcnn_googlenet.yml \ 17 | --iters 80000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/GoogleNet/kitti_test/test_rcnn.prototxt \ 21 | --net output/kitti/kitti_trainval/googlenet_fast_rcnn_kitti_iter_80000.caffemodel \ 22 | --imdb kitti_test \ 23 | --cfg experiments/cfgs/kitti_rcnn_googlenet.yml 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_test_vgg16_rcnn_multiscale_6k8k.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_test_vgg16_rcnn_multiscale_6k8k.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/VGG16/kitti_test/solver_rcnn_multiscale_6k8k.prototxt \ 14 | --weights data/imagenet_models/VGG16.v2.caffemodel \ 15 | --imdb kitti_trainval \ 16 | --cfg experiments/cfgs/kitti_rcnn_vgg16_multiscale_6k8k.yml \ 17 | --iters 80000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/VGG16/kitti_test/test_rcnn_multiscale.prototxt \ 21 | --net output/kitti/kitti_trainval/vgg16_fast_rcnn_multiscale_6k8k_kitti_iter_80000.caffemodel \ 22 | --imdb kitti_test \ 23 | --cfg experiments/cfgs/kitti_rcnn_vgg16_multiscale_6k8k.yml 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_tracking_test_caffenet_rpn.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_tracking_test_caffenet_rpn.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/kitti_tracking_test/solver_rpn.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb kitti_tracking_training_trainval \ 16 | --cfg experiments/cfgs/kitti_rpn.yml \ 17 | --iters 40000 18 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_tracking_val_caffenet_rpn.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_tracking_val_caffenet_rpn.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/kitti_tracking_val/solver_rpn.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb kitti_tracking_training_train \ 16 | --cfg experiments/cfgs/kitti_rpn.yml \ 17 | --iters 40000 18 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_val_caffenet_rcnn.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_val_caffenet_rcnn.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/kitti_val/solver_rcnn.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb kitti_train \ 16 | --cfg experiments/cfgs/kitti_rcnn.yml 17 | 18 | time ./tools/test_net.py --gpu $1 \ 19 | --def models/CaffeNet/kitti_val/test_rcnn.prototxt \ 20 | --net output/kitti/kitti_train/caffenet_fast_rcnn_kitti_iter_40000.caffemodel \ 21 | --imdb kitti_val \ 22 | --cfg experiments/cfgs/kitti_rcnn.yml 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_val_caffenet_rcnn_2d_multiscale.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_val_caffenet_rcnn_2d_multiscale.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/kitti_val/solver_rcnn_2d_multiscale.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb kitti_train \ 16 | --cfg experiments/cfgs/kitti_rcnn_2d_multiscale.yml 17 | 18 | time ./tools/test_net.py --gpu $1 \ 19 | --def models/CaffeNet/kitti_val/test_rcnn_multiscale.prototxt \ 20 | --net output/kitti/kitti_train/caffenet_fast_rcnn_2d_multiscale_kitti_iter_40000.caffemodel \ 21 | --imdb kitti_val \ 22 | --cfg experiments/cfgs/kitti_rcnn_2d_multiscale.yml 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_val_caffenet_rcnn_fix.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_val_caffenet_rcnn_fix.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/kitti_val/solver_rcnn_fix.prototxt \ 14 | --weights output/kitti/kitti_train/caffenet_fast_rcnn_rpn_kitti_iter_40000.caffemodel \ 15 | --imdb kitti_train \ 16 | --cfg experiments/cfgs/kitti_rcnn_fix.yml 17 | 18 | time ./tools/test_net.py --gpu $1 \ 19 | --def models/CaffeNet/kitti_val/test_rcnn_fix.prototxt \ 20 | --net output/kitti/kitti_train/caffenet_fast_rcnn_fix_kitti_iter_40000.caffemodel \ 21 | --imdb kitti_val \ 22 | --cfg experiments/cfgs/kitti_rcnn_fix.yml 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_val_caffenet_rcnn_msr.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_val_caffenet_rcnn_msr.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/kitti_val/solver_rcnn_msr.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb kitti_train \ 16 | --cfg experiments/cfgs/kitti_rcnn_msr.yml 17 | 18 | time ./tools/test_net.py --gpu $1 \ 19 | --def models/CaffeNet/kitti_val/test_rcnn.prototxt \ 20 | --net output/kitti/kitti_train/caffenet_fast_rcnn_msr_kitti_iter_40000.caffemodel \ 21 | --imdb kitti_val \ 22 | --cfg experiments/cfgs/kitti_rcnn_msr.yml 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_val_caffenet_rcnn_msr_fix.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_val_caffenet_rcnn_msr_fix.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/kitti_val/solver_rcnn_msr_fix.prototxt \ 14 | --weights output/kitti/kitti_train/caffenet_fast_rcnn_rpn_msr_fix_kitti_iter_40000.caffemodel \ 15 | --imdb kitti_train \ 16 | --cfg experiments/cfgs/kitti_rcnn_msr_fix.yml 17 | 18 | time ./tools/test_net.py --gpu $1 \ 19 | --def models/CaffeNet/kitti_val/test_rcnn.prototxt \ 20 | --net output/kitti/kitti_train/caffenet_fast_rcnn_msr_fix_kitti_iter_40000.caffemodel \ 21 | --imdb kitti_val \ 22 | --cfg experiments/cfgs/kitti_rcnn_msr_fix.yml 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_val_caffenet_rcnn_msr_multiscale.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_val_caffenet_rcnn_msr_multiscale.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/kitti_val/solver_rcnn_msr_multiscale.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb kitti_train \ 16 | --cfg experiments/cfgs/kitti_rcnn_msr_multiscale.yml 17 | 18 | time ./tools/test_net.py --gpu $1 \ 19 | --def models/CaffeNet/kitti_val/test_rcnn_multiscale.prototxt \ 20 | --net output/kitti/kitti_train/caffenet_fast_rcnn_msr_multiscale_kitti_iter_40000.caffemodel \ 21 | --imdb kitti_val \ 22 | --cfg experiments/cfgs/kitti_rcnn_msr_multiscale.yml 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_val_caffenet_rcnn_msr_multiscale_fix.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_val_caffenet_rcnn_msr_multiscale_fix.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/kitti_val/solver_rcnn_msr_multiscale_fix.prototxt \ 14 | --weights output/kitti/kitti_train/caffenet_fast_rcnn_rpn_msr_multiscale_fix_kitti_iter_40000.caffemodel \ 15 | --imdb kitti_train \ 16 | --cfg experiments/cfgs/kitti_rcnn_msr_multiscale_fix.yml 17 | 18 | time ./tools/test_net.py --gpu $1 \ 19 | --def models/CaffeNet/kitti_val/test_rcnn_multiscale.prototxt \ 20 | --net output/kitti/kitti_train/caffenet_fast_rcnn_msr_multiscale_fix_kitti_iter_40000.caffemodel \ 21 | --imdb kitti_val \ 22 | --cfg experiments/cfgs/kitti_rcnn_msr_multiscale_fix.yml 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_val_caffenet_rcnn_multiscale.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_val_caffenet_rcnn_multiscale.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/kitti_val/solver_rcnn_multiscale.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb kitti_train \ 16 | --cfg experiments/cfgs/kitti_rcnn_multiscale.yml 17 | 18 | time ./tools/test_net.py --gpu $1 \ 19 | --def models/CaffeNet/kitti_val/test_rcnn_multiscale.prototxt \ 20 | --net output/kitti/kitti_train/caffenet_fast_rcnn_multiscale_kitti_iter_40000.caffemodel \ 21 | --imdb kitti_val \ 22 | --cfg experiments/cfgs/kitti_rcnn_multiscale.yml 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_val_caffenet_rcnn_noextra.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_val_caffenet_rcnn_noextra.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/kitti_val/solver_rcnn_noextra.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb kitti_train \ 16 | --cfg experiments/cfgs/kitti_rcnn_noextra.yml 17 | 18 | time ./tools/test_net.py --gpu $1 \ 19 | --def models/CaffeNet/kitti_val/test_rcnn.prototxt \ 20 | --net output/kitti/kitti_train/caffenet_fast_rcnn_noextra_kitti_iter_40000.caffemodel \ 21 | --imdb kitti_val \ 22 | --cfg experiments/cfgs/kitti_rcnn_noextra.yml 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_val_caffenet_rcnn_original.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_val_caffenet_rcnn_original.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/kitti_val/solver_rcnn_original.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb kitti_train \ 16 | --cfg experiments/cfgs/kitti_rcnn_original.yml 17 | 18 | time ./tools/test_net.py --gpu $1 \ 19 | --def models/CaffeNet/kitti_val/test_rcnn_original.prototxt \ 20 | --net output/kitti/kitti_train/caffenet_fast_rcnn_original_kitti_iter_40000.caffemodel \ 21 | --imdb kitti_val \ 22 | --cfg experiments/cfgs/kitti_rcnn_original.yml 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_val_caffenet_rcnn_original_msr.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_val_caffenet_rcnn_original_msr.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/kitti_val/solver_rcnn_original_msr.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb kitti_train \ 16 | --cfg experiments/cfgs/kitti_rcnn_original_msr.yml 17 | 18 | time ./tools/test_net.py --gpu $1 \ 19 | --def models/CaffeNet/kitti_val/test_rcnn_original.prototxt \ 20 | --net output/kitti/kitti_train/caffenet_fast_rcnn_original_msr_kitti_iter_40000.caffemodel \ 21 | --imdb kitti_val \ 22 | --cfg experiments/cfgs/kitti_rcnn_original_msr.yml 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_val_caffenet_rcnn_original_multiscale.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_val_caffenet_rcnn_original_multiscale.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/kitti_val/solver_rcnn_original_multiscale.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb kitti_train \ 16 | --cfg experiments/cfgs/kitti_rcnn_original_multiscale.yml 17 | 18 | time ./tools/test_net.py --gpu $1 \ 19 | --def models/CaffeNet/kitti_val/test_rcnn_original_multiscale.prototxt \ 20 | --net output/kitti/kitti_train/caffenet_fast_rcnn_original_multiscale_kitti_iter_40000.caffemodel \ 21 | --imdb kitti_val \ 22 | --cfg experiments/cfgs/kitti_rcnn_original_multiscale.yml 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_val_caffenet_rpn.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_val_caffenet_rpn.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/kitti_val/solver_rpn.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb kitti_train \ 16 | --cfg experiments/cfgs/kitti_rpn.yml \ 17 | --iters 40000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/CaffeNet/kitti_val/test_rpn.prototxt \ 21 | --net output/kitti/kitti_train/caffenet_fast_rcnn_rpn_kitti_iter_40000.caffemodel \ 22 | --imdb kitti_val \ 23 | --cfg experiments/cfgs/kitti_rpn.yml 24 | 25 | time ./tools/test_net.py --gpu $1 \ 26 | --def models/CaffeNet/kitti_val/test_rpn.prototxt \ 27 | --net output/kitti/kitti_train/caffenet_fast_rcnn_rpn_kitti_iter_40000.caffemodel \ 28 | --imdb kitti_train \ 29 | --cfg experiments/cfgs/kitti_rpn.yml 30 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_val_caffenet_rpn_2d.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_val_caffenet_rpn_2d.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/kitti_val/solver_rpn_2d.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb kitti_train \ 16 | --cfg experiments/cfgs/kitti_rpn_2d.yml \ 17 | --iters 40000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/CaffeNet/kitti_val/test_rpn.prototxt \ 21 | --net output/kitti/kitti_train/caffenet_fast_rcnn_rpn_2d_kitti_iter_40000.caffemodel \ 22 | --imdb kitti_val \ 23 | --cfg experiments/cfgs/kitti_rpn_2d.yml 24 | 25 | time ./tools/test_net.py --gpu $1 \ 26 | --def models/CaffeNet/kitti_val/test_rpn.prototxt \ 27 | --net output/kitti/kitti_train/caffenet_fast_rcnn_rpn_2d_kitti_iter_40000.caffemodel \ 28 | --imdb kitti_train \ 29 | --cfg experiments/cfgs/kitti_rpn_2d.yml 30 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_val_caffenet_rpn_fix.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_val_caffenet_rpn_fix.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/kitti_val/solver_rpn_fix.prototxt \ 14 | --weights output/kitti/kitti_train/caffenet_fast_rcnn_kitti_iter_40000.caffemodel \ 15 | --imdb kitti_train \ 16 | --cfg experiments/cfgs/kitti_rpn_fix.yml \ 17 | --iters 40000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/CaffeNet/kitti_val/test_rpn_fix.prototxt \ 21 | --net output/kitti/kitti_train/caffenet_fast_rcnn_rpn_fix_kitti_iter_40000.caffemodel \ 22 | --imdb kitti_val \ 23 | --cfg experiments/cfgs/kitti_rpn_fix.yml 24 | 25 | time ./tools/test_net.py --gpu $1 \ 26 | --def models/CaffeNet/kitti_val/test_rpn_fix.prototxt \ 27 | --net output/kitti/kitti_train/caffenet_fast_rcnn_rpn_fix_kitti_iter_40000.caffemodel \ 28 | --imdb kitti_train \ 29 | --cfg experiments/cfgs/kitti_rpn_fix.yml 30 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_val_caffenet_rpn_msr.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_val_caffenet_rpn_msr.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/kitti_val/solver_rpn_msr.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb kitti_train \ 16 | --cfg experiments/cfgs/kitti_rpn_msr.yml \ 17 | --iters 40000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/CaffeNet/kitti_val/test_rpn_msr.prototxt \ 21 | --net output/kitti/kitti_train/caffenet_fast_rcnn_rpn_msr_kitti_iter_40000.caffemodel \ 22 | --imdb kitti_val \ 23 | --cfg experiments/cfgs/kitti_rpn_msr.yml 24 | 25 | time ./tools/test_net.py --gpu $1 \ 26 | --def models/CaffeNet/kitti_val/test_rpn_msr.prototxt \ 27 | --net output/kitti/kitti_train/caffenet_fast_rcnn_rpn_msr_kitti_iter_40000.caffemodel \ 28 | --imdb kitti_train \ 29 | --cfg experiments/cfgs/kitti_rpn_msr.yml 30 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_val_caffenet_rpn_msr_fix.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_val_caffenet_rpn_msr_fix.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/kitti_val/solver_rpn_msr_fix.prototxt \ 14 | --weights output/kitti/kitti_train/caffenet_fast_rcnn_msr_kitti_iter_40000.caffemodel \ 15 | --imdb kitti_train \ 16 | --cfg experiments/cfgs/kitti_rpn_msr.yml \ 17 | --iters 40000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/CaffeNet/kitti_val/test_rpn_msr.prototxt \ 21 | --net output/kitti/kitti_train/caffenet_fast_rcnn_rpn_msr_fix_kitti_iter_40000.caffemodel \ 22 | --imdb kitti_val \ 23 | --cfg experiments/cfgs/kitti_rpn_msr.yml 24 | 25 | time ./tools/test_net.py --gpu $1 \ 26 | --def models/CaffeNet/kitti_val/test_rpn_msr.prototxt \ 27 | --net output/kitti/kitti_train/caffenet_fast_rcnn_rpn_msr_fix_kitti_iter_40000.caffemodel \ 28 | --imdb kitti_train \ 29 | --cfg experiments/cfgs/kitti_rpn_msr.yml 30 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/kitti_val_googlenet_rcnn.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/kitti_val_google_rcnn.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/GoogleNet/kitti_val/solver_rcnn.prototxt \ 14 | --weights data/imagenet_models/bvlc_googlenet.caffemodel \ 15 | --imdb kitti_train \ 16 | --cfg experiments/cfgs/kitti_rcnn_googlenet.yml \ 17 | --iters 40000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/GoogleNet/kitti_val/test_rcnn.prototxt \ 21 | --net output/kitti/kitti_train/googlenet_fast_rcnn_kitti_iter_40000.caffemodel \ 22 | --imdb kitti_val \ 23 | --cfg experiments/cfgs/kitti_rcnn_googlenet.yml 24 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/mot_tracking_caffenet_rpn.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/mot_tracking_caffenet_rpn.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/mot_tracking_train/solver_rpn.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb mot_tracking_train_trainval \ 16 | --cfg experiments/cfgs/mot_rpn.yml \ 17 | --iters 80000 18 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/nissan_caffenet_combined.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/nissan_caffenet_combined.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | image_set="autonomy_log_2016-04-11-12-15-46" 13 | 14 | time ./tools/test_net.py --gpu $1 \ 15 | --def models/CaffeNet/kitti_test/test_rpn.prototxt \ 16 | --net output/kitti/kitti_trainval/caffenet_fast_rcnn_rpn_6k8k_kitti_iter_80000.caffemodel \ 17 | --imdb nissan_$image_set \ 18 | --cfg experiments/cfgs/nissan_rpn.yml 19 | 20 | # create an symbol link for the region proposal results 21 | ln -s $PWD/output/nissan/nissan_$image_set/caffenet_fast_rcnn_rpn_6k8k_kitti_iter_80000 data/NISSAN/region_proposals/RPN_6k8k/$image_set 22 | 23 | time ./tools/test_net.py --gpu $1 \ 24 | --def models/VGG16/kitti_test/test_rcnn_multiscale.prototxt \ 25 | --net output/kitti/kitti_trainval/vgg16_fast_rcnn_multiscale_6k8k_kitti_iter_80000.caffemodel \ 26 | --imdb nissan_$image_set \ 27 | --cfg experiments/cfgs/nissan_multiscale_6k8k.yml 28 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/nissan_caffenet_rcnn_multiscale_6k8k.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/nissan_caffenet_rcnn_multiscale_6k8k.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/test_net.py --gpu $1 \ 13 | --def models/CaffeNet/kitti_test/test_rcnn_multiscale.prototxt \ 14 | --net output/kitti/kitti_trainval/caffenet_fast_rcnn_multiscale_6k8k_kitti_iter_80000.caffemodel \ 15 | --imdb nissan_2015-10-21-16-25-12 \ 16 | --cfg experiments/cfgs/nissan_multiscale_6k8k.yml 17 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/nissan_caffenet_rpn_6k8k.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/nissan_caffenet_rpn_6k8k.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/test_net.py --gpu $1 \ 13 | --def models/CaffeNet/kitti_test/test_rpn.prototxt \ 14 | --net output/kitti/kitti_trainval/caffenet_fast_rcnn_rpn_6k8k_kitti_iter_80000.caffemodel \ 15 | --imdb nissan_2015-10-21-16-25-12 \ 16 | --cfg experiments/cfgs/nissan_rpn.yml 17 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/nthu_caffenet_rcnn_multiscale_6k8k.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/nthu_caffenet_rcnn_multiscale_6k8k.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/test_net.py --gpu $1 \ 13 | --def models/CaffeNet/kitti_test/test_rcnn_multiscale.prototxt \ 14 | --net data/3DVP_RCNN_models/caffenet_fast_rcnn_multiscale_6k8k_kitti_iter_80000.caffemodel \ 15 | --imdb nthu_370 \ 16 | --cfg experiments/cfgs/nthu_multiscale_6k8k.yml 17 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/nthu_caffenet_rpn_6k8k.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/nthu_caffenet_rpn_6k8k.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/test_net.py --gpu $1 \ 13 | --def models/CaffeNet/kitti_test/test_rpn.prototxt \ 14 | --net data/3DVP_RCNN_models/caffenet_fast_rcnn_rpn_6k8k_kitti_iter_80000.caffemodel \ 15 | --imdb nthu_370 \ 16 | --cfg experiments/cfgs/nthu_rpn.yml 17 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/pascal2007_caffenet_rcnn.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/pascal2007_caffenet_rcnn.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/pascal2007/solver_rcnn.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb voc_2007_trainval \ 16 | --cfg experiments/cfgs/pascal_rcnn.yml 17 | 18 | time ./tools/test_net.py --gpu $1 \ 19 | --def models/CaffeNet/pascal2007/test_rcnn.prototxt \ 20 | --net output/pascal2007/voc_2007_trainval/caffenet_fast_rcnn_pascal2007_iter_40000.caffemodel \ 21 | --imdb voc_2007_test \ 22 | --cfg experiments/cfgs/pascal_rcnn.yml 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/pascal2007_caffenet_rcnn_original.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/pascal2007_caffenet_rcnn_original.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/pascal2007/solver_rcnn_original.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb voc_2007_trainval \ 16 | --cfg experiments/cfgs/pascal_rcnn_original.yml 17 | 18 | time ./tools/test_net.py --gpu $1 \ 19 | --def models/CaffeNet/pascal2007/test_rcnn_original.prototxt \ 20 | --net output/pascal2007/voc_2007_trainval/caffenet_fast_rcnn_original_pascal2007_iter_40000.caffemodel \ 21 | --imdb voc_2007_test \ 22 | --cfg experiments/cfgs/pascal_rcnn_original.yml 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/pascal2007_caffenet_rpn.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/pascal2007_caffenet_rpn.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/CaffeNet/pascal2007/solver_rpn.prototxt \ 14 | --weights data/imagenet_models/CaffeNet.v2.caffemodel \ 15 | --imdb voc_2007_trainval \ 16 | --cfg experiments/cfgs/pascal_rpn.yml \ 17 | --iters 80000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/CaffeNet/pascal2007/test_rpn.prototxt \ 21 | --net output/pascal2007/voc_2007_trainval/caffenet_fast_rcnn_rpn_pascal2007_iter_80000.caffemodel \ 22 | --imdb voc_2007_test \ 23 | --cfg experiments/cfgs/pascal_rpn.yml 24 | 25 | time ./tools/test_net.py --gpu $1 \ 26 | --def models/CaffeNet/pascal2007/test_rpn.prototxt \ 27 | --net output/pascal2007/voc_2007_trainval/caffenet_fast_rcnn_rpn_pascal2007_iter_80000.caffemodel \ 28 | --imdb voc_2007_trainval \ 29 | --cfg experiments/cfgs/pascal_rpn.yml 30 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/pascal2007_vgg16_rcnn_original.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/pascal2007_vgg16_rcnn_original.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/VGG16/pascal2007/solver_rcnn_original.prototxt \ 14 | --weights data/imagenet_models/VGG16.v2.caffemodel \ 15 | --imdb voc_2007_trainval \ 16 | --cfg experiments/cfgs/pascal_rcnn_original.yml 17 | 18 | time ./tools/test_net.py --gpu $1 \ 19 | --def models/VGG16/pascal2007/test_rcnn_original.prototxt \ 20 | --net output/pascal2007/voc_2007_trainval/vgg16_fast_rcnn_original_pascal2007_iter_40000.caffemodel \ 21 | --imdb voc_2007_test \ 22 | --cfg experiments/cfgs/pascal_rcnn_original.yml 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/pascal2007_vgg16_rcnn_original_multiscale.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/pascal2007_vgg16_rcnn_original_multiscale.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/VGG16/pascal2007/solver_rcnn_original_multiscale.prototxt \ 14 | --weights data/imagenet_models/VGG16.v2.caffemodel \ 15 | --imdb voc_2007_trainval \ 16 | --cfg experiments/cfgs/pascal_rcnn_original_multiscale.yml 17 | 18 | time ./tools/test_net.py --gpu $1 \ 19 | --def models/VGG16/pascal2007/test_rcnn_original_multiscale.prototxt \ 20 | --net output/pascal2007/voc_2007_trainval/vgg16_fast_rcnn_original_multiscale_pascal2007_iter_40000.caffemodel \ 21 | --imdb voc_2007_test \ 22 | --cfg experiments/cfgs/pascal_rcnn_original_multiscale.yml 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/pascal2007_vgg16_rpn.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/pascal2007_vgg16_rpn.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/VGG16/pascal2007/solver_rpn.prototxt \ 14 | --weights data/imagenet_models/VGG16.v2.caffemodel \ 15 | --imdb voc_2007_trainval \ 16 | --cfg experiments/cfgs/pascal_rpn_vgg16.yml \ 17 | --iters 40000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/VGG16/pascal2007/test_rpn.prototxt \ 21 | --net output/pascal2007/voc_2007_trainval/vgg16_fast_rcnn_rpn_pascal2007_iter_40000.caffemodel \ 22 | --imdb voc_2007_test \ 23 | --cfg experiments/cfgs/pascal_rpn_vgg16.yml 24 | 25 | time ./tools/test_net.py --gpu $1 \ 26 | --def models/VGG16/pascal2007/test_rpn.prototxt \ 27 | --net output/pascal2007/voc_2007_trainval/vgg16_fast_rcnn_rpn_pascal2007_iter_40000.caffemodel \ 28 | --imdb voc_2007_trainval \ 29 | --cfg experiments/cfgs/pascal_rpn_vgg16.yml 30 | 31 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/pascal2007_vgg16_rpn_6k8k.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/pascal2007_vgg16_rpn_6k8k.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/VGG16/pascal2007/solver_rpn_6k8k.prototxt \ 14 | --weights data/imagenet_models/VGG16.v2.caffemodel \ 15 | --imdb voc_2007_trainval \ 16 | --cfg experiments/cfgs/pascal_rpn_vgg16.yml \ 17 | --iters 80000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/VGG16/pascal2007/test_rpn.prototxt \ 21 | --net output/pascal2007/voc_2007_trainval/vgg16_fast_rcnn_rpn_6k8k_pascal2007_iter_80000.caffemodel \ 22 | --imdb voc_2007_test \ 23 | --cfg experiments/cfgs/pascal_rpn_vgg16.yml 24 | 25 | time ./tools/test_net.py --gpu $1 \ 26 | --def models/VGG16/pascal2007/test_rpn.prototxt \ 27 | --net output/pascal2007/voc_2007_trainval/vgg16_fast_rcnn_rpn_6k8k_pascal2007_iter_80000.caffemodel \ 28 | --imdb voc_2007_trainval \ 29 | --cfg experiments/cfgs/pascal_rpn_vgg16.yml 30 | 31 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/pascal2007_vgg16_rpn_cls.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/pascal2007_vgg16_rpn_cls.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/VGG16/pascal2007/solver_rpn_cls.prototxt \ 14 | --weights data/imagenet_models/VGG16.v2.caffemodel \ 15 | --imdb voc_2007_trainval \ 16 | --cfg experiments/cfgs/pascal_rpn_cls_vgg16.yml \ 17 | --iters 40000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/VGG16/pascal2007/test_rpn_cls.prototxt \ 21 | --net output/pascal2007/voc_2007_trainval/vgg16_fast_rcnn_rpn_cls_pascal2007_iter_40000.caffemodel \ 22 | --imdb voc_2007_test \ 23 | --cfg experiments/cfgs/pascal_rpn_cls_vgg16.yml 24 | 25 | time ./tools/test_net.py --gpu $1 \ 26 | --def models/VGG16/pascal2007/test_rpn_cls.prototxt \ 27 | --net output/pascal2007/voc_2007_trainval/vgg16_fast_rcnn_rpn_cls_pascal2007_iter_40000.caffemodel \ 28 | --imdb voc_2007_trainval \ 29 | --cfg experiments/cfgs/pascal_rpn_cls_vgg16.yml 30 | 31 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/pascal3d_vgg16_rcnn.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/pascal3d_vgg16_rcnn.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/VGG16/pascal3d/solver_rcnn.prototxt \ 14 | --weights data/imagenet_models/VGG16.v2.caffemodel \ 15 | --imdb pascal3d_train \ 16 | --cfg experiments/cfgs/pascal3d_rcnn.yml 17 | 18 | time ./tools/test_net.py --gpu $1 \ 19 | --def models/VGG16/pascal3d/test_rcnn.prototxt \ 20 | --net output/pascal3d/pascal3d_train/vgg16_fast_rcnn_pascal3d_iter_40000.caffemodel \ 21 | --imdb pascal3d_val \ 22 | --cfg experiments/cfgs/pascal3d_rcnn.yml 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/pascal3d_vgg16_rcnn_multiscale.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/pascal3d_vgg16_rcnn_multiscale.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/VGG16/pascal3d/solver_rcnn_multiscale.prototxt \ 14 | --weights data/imagenet_models/VGG16.v2.caffemodel \ 15 | --imdb pascal3d_train \ 16 | --cfg experiments/cfgs/pascal3d_rcnn_multiscale.yml 17 | 18 | time ./tools/test_net.py --gpu $1 \ 19 | --def models/VGG16/pascal3d/test_rcnn_multiscale.prototxt \ 20 | --net output/pascal3d/pascal3d_train/vgg16_fast_rcnn_multiscale_pascal3d_iter_40000.caffemodel \ 21 | --imdb pascal3d_val \ 22 | --cfg experiments/cfgs/pascal3d_rcnn_multiscale.yml 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/pascal3d_vgg16_rcnn_original.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/pascal3d_vgg16_rcnn_original.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/VGG16/pascal3d/solver_rcnn_original.prototxt \ 14 | --weights data/imagenet_models/VGG16.v2.caffemodel \ 15 | --imdb pascal3d_train \ 16 | --cfg experiments/cfgs/pascal3d_rcnn_original.yml 17 | 18 | time ./tools/test_net.py --gpu $1 \ 19 | --def models/VGG16/pascal3d/test_rcnn_original.prototxt \ 20 | --net output/pascal3d/pascal3d_train/vgg16_fast_rcnn_original_pascal3d_iter_40000.caffemodel \ 21 | --imdb pascal3d_val \ 22 | --cfg experiments/cfgs/pascal3d_rcnn_original.yml 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/pascal3d_vgg16_rcnn_pose.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/pascal3d_vgg16_rcnn_pose.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/VGG16/pascal3d/solver_rcnn_pose.prototxt \ 14 | --weights data/imagenet_models/VGG16.v2.caffemodel \ 15 | --imdb pascal3d_train \ 16 | --cfg experiments/cfgs/pascal3d_rcnn_pose.yml 17 | 18 | time ./tools/test_net.py --gpu $1 \ 19 | --def models/VGG16/pascal3d/test_rcnn_pose.prototxt \ 20 | --net output/pascal3d/pascal3d_train/vgg16_fast_rcnn_pose_pascal3d_iter_40000.caffemodel \ 21 | --imdb pascal3d_val \ 22 | --cfg experiments/cfgs/pascal3d_rcnn_pose.yml 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/pascal3d_vgg16_rcnn_pose_multiscale.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/pascal3d_vgg16_rcnn_pose_multiscale.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/VGG16/pascal3d/solver_rcnn_pose_multiscale.prototxt \ 14 | --weights data/imagenet_models/VGG16.v2.caffemodel \ 15 | --imdb pascal3d_train \ 16 | --cfg experiments/cfgs/pascal3d_rcnn_pose_multiscale.yml 17 | 18 | time ./tools/test_net.py --gpu $1 \ 19 | --def models/VGG16/pascal3d/test_rcnn_pose_multiscale.prototxt \ 20 | --net output/pascal3d/pascal3d_train/vgg16_fast_rcnn_pose_multiscale_pascal3d_iter_40000.caffemodel \ 21 | --imdb pascal3d_val \ 22 | --cfg experiments/cfgs/pascal3d_rcnn_pose_multiscale.yml 23 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/pascal3d_vgg16_rpn.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/pascal3d_vgg16_rpn.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/VGG16/pascal3d/solver_rpn.prototxt \ 14 | --weights data/imagenet_models/VGG16.v2.caffemodel \ 15 | --imdb pascal3d_train \ 16 | --cfg experiments/cfgs/pascal3d_rpn_vgg16.yml \ 17 | --iters 40000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/VGG16/pascal3d/test_rpn.prototxt \ 21 | --net output/pascal3d/pascal3d_train/vgg16_fast_rcnn_rpn_pascal3d_iter_40000.caffemodel \ 22 | --imdb pascal3d_val \ 23 | --cfg experiments/cfgs/pascal3d_rpn_vgg16.yml 24 | 25 | time ./tools/test_net.py --gpu $1 \ 26 | --def models/VGG16/pascal3d/test_rpn.prototxt \ 27 | --net output/pascal3d/pascal3d_train/vgg16_fast_rcnn_rpn_pascal3d_iter_40000.caffemodel \ 28 | --imdb pascal3d_train \ 29 | --cfg experiments/cfgs/pascal3d_rpn_vgg16.yml 30 | 31 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/pascal3d_vgg16_rpn_6k8k.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/pascal3d_vgg16_rpn_6k8k.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/VGG16/pascal3d/solver_rpn_6k8k.prototxt \ 14 | --weights data/imagenet_models/VGG16.v2.caffemodel \ 15 | --imdb pascal3d_train \ 16 | --cfg experiments/cfgs/pascal3d_rpn_vgg16.yml \ 17 | --iters 80000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/VGG16/pascal3d/test_rpn.prototxt \ 21 | --net output/pascal3d/pascal3d_train/vgg16_fast_rcnn_rpn_6k8k_pascal3d_iter_80000.caffemodel \ 22 | --imdb pascal3d_val \ 23 | --cfg experiments/cfgs/pascal3d_rpn_vgg16.yml 24 | 25 | time ./tools/test_net.py --gpu $1 \ 26 | --def models/VGG16/pascal3d/test_rpn.prototxt \ 27 | --net output/pascal3d/pascal3d_train/vgg16_fast_rcnn_rpn_6k8k_pascal3d_iter_80000.caffemodel \ 28 | --imdb pascal3d_train \ 29 | --cfg experiments/cfgs/pascal3d_rpn_vgg16.yml 30 | 31 | -------------------------------------------------------------------------------- /fast-rcnn/experiments/scripts/pascal3d_vgg16_rpn_msr.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | set -x 4 | set -e 5 | 6 | export PYTHONUNBUFFERED="True" 7 | 8 | LOG="experiments/logs/pascal3d_vgg16_rpn_msr.txt.`date +'%Y-%m-%d_%H-%M-%S'`" 9 | exec &> >(tee -a "$LOG") 10 | echo Logging output to "$LOG" 11 | 12 | time ./tools/train_net.py --gpu $1 \ 13 | --solver models/VGG16/pascal3d/solver_rpn_msr.prototxt \ 14 | --weights data/imagenet_models/VGG16.v2.caffemodel \ 15 | --imdb pascal3d_train \ 16 | --cfg experiments/cfgs/pascal3d_rpn_msr_vgg16.yml \ 17 | --iters 40000 18 | 19 | time ./tools/test_net.py --gpu $1 \ 20 | --def models/VGG16/pascal3d/test_rpn_msr.prototxt \ 21 | --net output/pascal3d/pascal3d_train/vgg16_fast_rcnn_rpn_msr_pascal3d_iter_40000.caffemodel \ 22 | --imdb pascal3d_val \ 23 | --cfg experiments/cfgs/pascal3d_rpn_msr_vgg16.yml 24 | 25 | time ./tools/test_net.py --gpu $1 \ 26 | --def models/VGG16/pascal3d/test_rpn_msr.prototxt \ 27 | --net output/pascal3d/pascal3d_train/vgg16_fast_rcnn_rpn_msr_pascal3d_iter_40000.caffemodel \ 28 | --imdb pascal3d_train \ 29 | --cfg experiments/cfgs/pascal3d_rpn_msr_vgg16.yml 30 | 31 | -------------------------------------------------------------------------------- /fast-rcnn/lib/Makefile: -------------------------------------------------------------------------------- 1 | all: 2 | python setup.py build_ext --inplace 3 | rm -rf build 4 | -------------------------------------------------------------------------------- /fast-rcnn/lib/datasets/VOCdevkit-matlab-wrapper/get_voc_opts.m: -------------------------------------------------------------------------------- 1 | function VOCopts = get_voc_opts(path) 2 | 3 | tmp = pwd; 4 | cd(path); 5 | try 6 | addpath('VOCcode'); 7 | VOCinit; 8 | catch 9 | rmpath('VOCcode'); 10 | cd(tmp); 11 | error(sprintf('VOCcode directory not found under %s', path)); 12 | end 13 | rmpath('VOCcode'); 14 | cd(tmp); 15 | -------------------------------------------------------------------------------- /fast-rcnn/lib/datasets/VOCdevkit-matlab-wrapper/xVOCap.m: -------------------------------------------------------------------------------- 1 | function ap = xVOCap(rec,prec) 2 | % From the PASCAL VOC 2011 devkit 3 | 4 | mrec=[0 ; rec ; 1]; 5 | mpre=[0 ; prec ; 0]; 6 | for i=numel(mpre)-1:-1:1 7 | mpre(i)=max(mpre(i),mpre(i+1)); 8 | end 9 | i=find(mrec(2:end)~=mrec(1:end-1))+1; 10 | ap=sum((mrec(i)-mrec(i-1)).*mpre(i)); 11 | -------------------------------------------------------------------------------- /fast-rcnn/lib/fast_rcnn/__init__.py: -------------------------------------------------------------------------------- 1 | # -------------------------------------------------------- 2 | # Fast R-CNN 3 | # Copyright (c) 2015 Microsoft 4 | # Licensed under The MIT License [see LICENSE for details] 5 | # Written by Ross Girshick 6 | # -------------------------------------------------------- 7 | 8 | from . import config 9 | from . import train 10 | from . import test 11 | -------------------------------------------------------------------------------- /fast-rcnn/lib/fast_rcnn/nms_wrapper.py: -------------------------------------------------------------------------------- 1 | # -------------------------------------------------------- 2 | # Fast R-CNN 3 | # Copyright (c) 2015 Microsoft 4 | # Licensed under The MIT License [see LICENSE for details] 5 | # Written by Ross Girshick 6 | # -------------------------------------------------------- 7 | 8 | from fast_rcnn.config import cfg 9 | from nms.gpu_nms import gpu_nms 10 | from nms.cpu_nms import cpu_nms 11 | 12 | def nms(dets, thresh): 13 | """Dispatch to either CPU or GPU NMS implementations.""" 14 | 15 | if dets.shape[0] == 0: 16 | return [] 17 | if cfg.USE_GPU_NMS: 18 | return gpu_nms(dets, thresh, device_id=cfg.GPU_ID) 19 | else: 20 | return cpu_nms(dets, thresh) 21 | -------------------------------------------------------------------------------- /fast-rcnn/lib/gt_data_layer/__init__.py: -------------------------------------------------------------------------------- 1 | # -------------------------------------------------------- 2 | # Fast R-CNN 3 | # Copyright (c) 2015 Microsoft 4 | # Licensed under The MIT License [see LICENSE for details] 5 | # Written by Ross Girshick 6 | # -------------------------------------------------------- 7 | -------------------------------------------------------------------------------- /fast-rcnn/lib/nms/.gitignore: -------------------------------------------------------------------------------- 1 | *.c 2 | *.cpp 3 | *.so 4 | -------------------------------------------------------------------------------- /fast-rcnn/lib/nms/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/tanshen/SubCNN/35e7a86ec652ceadcefbc35bf5c24121624f1c1e/fast-rcnn/lib/nms/__init__.py -------------------------------------------------------------------------------- /fast-rcnn/lib/nms/gpu_nms.hpp: -------------------------------------------------------------------------------- 1 | void _nms(int* keep_out, int* num_out, const float* boxes_host, int boxes_num, 2 | int boxes_dim, float nms_overlap_thresh, int device_id); 3 | -------------------------------------------------------------------------------- /fast-rcnn/lib/roi_data_layer/__init__.py: -------------------------------------------------------------------------------- 1 | # -------------------------------------------------------- 2 | # Fast R-CNN 3 | # Copyright (c) 2015 Microsoft 4 | # Licensed under The MIT License [see LICENSE for details] 5 | # Written by Ross Girshick 6 | # -------------------------------------------------------- 7 | -------------------------------------------------------------------------------- /fast-rcnn/lib/roi_generating_layer/__init__.py: -------------------------------------------------------------------------------- 1 | # -------------------------------------------------------- 2 | # Fast R-CNN 3 | # Copyright (c) 2015 Microsoft 4 | # Licensed under The MIT License [see LICENSE for details] 5 | # Written by Ross Girshick 6 | # -------------------------------------------------------- 7 | -------------------------------------------------------------------------------- /fast-rcnn/lib/roi_patch_layer/__init__.py: -------------------------------------------------------------------------------- 1 | # -------------------------------------------------------- 2 | # Fast R-CNN 3 | # Copyright (c) 2015 Microsoft 4 | # Licensed under The MIT License [see LICENSE for details] 5 | # Written by Ross Girshick 6 | # -------------------------------------------------------- 7 | -------------------------------------------------------------------------------- /fast-rcnn/lib/roi_testing_layer/__init__.py: -------------------------------------------------------------------------------- 1 | # -------------------------------------------------------- 2 | # Fast R-CNN 3 | # Copyright (c) 2015 Microsoft 4 | # Licensed under The MIT License [see LICENSE for details] 5 | # Written by Ross Girshick 6 | # -------------------------------------------------------- 7 | -------------------------------------------------------------------------------- /fast-rcnn/lib/roi_visualizing_layer/__init__.py: -------------------------------------------------------------------------------- 1 | # -------------------------------------------------------- 2 | # Fast R-CNN 3 | # Copyright (c) 2015 Microsoft 4 | # Licensed under The MIT License [see LICENSE for details] 5 | # Written by Ross Girshick 6 | # -------------------------------------------------------- 7 | -------------------------------------------------------------------------------- /fast-rcnn/lib/rpn_msr/__init__.py: -------------------------------------------------------------------------------- 1 | # -------------------------------------------------------- 2 | # Fast R-CNN 3 | # Copyright (c) 2015 Microsoft 4 | # Licensed under The MIT License [see LICENSE for details] 5 | # Written by Ross Girshick and Sean Bell 6 | # -------------------------------------------------------- 7 | -------------------------------------------------------------------------------- /fast-rcnn/lib/utils/.gitignore: -------------------------------------------------------------------------------- 1 | *.c 2 | *.so 3 | -------------------------------------------------------------------------------- /fast-rcnn/lib/utils/__init__.py: -------------------------------------------------------------------------------- 1 | # -------------------------------------------------------- 2 | # Fast R-CNN 3 | # Copyright (c) 2015 Microsoft 4 | # Licensed under The MIT License [see LICENSE for details] 5 | # Written by Ross Girshick 6 | # -------------------------------------------------------- 7 | -------------------------------------------------------------------------------- /fast-rcnn/lib/utils/nms.py: -------------------------------------------------------------------------------- 1 | # -------------------------------------------------------- 2 | # Fast R-CNN 3 | # Copyright (c) 2015 Microsoft 4 | # Licensed under The MIT License [see LICENSE for details] 5 | # Written by Ross Girshick 6 | # -------------------------------------------------------- 7 | 8 | import numpy as np 9 | 10 | def nms(dets, thresh): 11 | x1 = dets[:, 0] 12 | y1 = dets[:, 1] 13 | x2 = dets[:, 2] 14 | y2 = dets[:, 3] 15 | scores = dets[:, 4] 16 | 17 | areas = (x2 - x1 + 1) * (y2 - y1 + 1) 18 | order = scores.argsort()[::-1] 19 | 20 | keep = [] 21 | while order.size > 0: 22 | i = order[0] 23 | keep.append(i) 24 | xx1 = np.maximum(x1[i], x1[order[1:]]) 25 | yy1 = np.maximum(y1[i], y1[order[1:]]) 26 | xx2 = np.minimum(x2[i], x2[order[1:]]) 27 | yy2 = np.minimum(y2[i], y2[order[1:]]) 28 | 29 | w = np.maximum(0.0, xx2 - xx1 + 1) 30 | h = np.maximum(0.0, yy2 - yy1 + 1) 31 | inter = w * h 32 | ovr = inter / (areas[i] + areas[order[1:]] - inter) 33 | 34 | inds = np.where(ovr <= thresh)[0] 35 | order = order[inds + 1] 36 | 37 | return keep 38 | -------------------------------------------------------------------------------- /fast-rcnn/lib/utils/timer.py: -------------------------------------------------------------------------------- 1 | # -------------------------------------------------------- 2 | # Fast R-CNN 3 | # Copyright (c) 2015 Microsoft 4 | # Licensed under The MIT License [see LICENSE for details] 5 | # Written by Ross Girshick 6 | # -------------------------------------------------------- 7 | 8 | import time 9 | 10 | class Timer(object): 11 | """A simple timer.""" 12 | def __init__(self): 13 | self.total_time = 0. 14 | self.calls = 0 15 | self.start_time = 0. 16 | self.diff = 0. 17 | self.average_time = 0. 18 | 19 | def tic(self): 20 | # using time.time instead of time.clock because time time.clock 21 | # does not normalize for multithreading 22 | self.start_time = time.time() 23 | 24 | def toc(self, average=True): 25 | self.diff = time.time() - self.start_time 26 | self.total_time += self.diff 27 | self.calls += 1 28 | self.average_time = self.total_time / self.calls 29 | if average: 30 | return self.average_time 31 | else: 32 | return self.diff 33 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/imagenet3d/solver_rcnn_original.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/imagenet3d/train_rcnn_original.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 120000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_original" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/imagenet3d/solver_rcnn_view.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/imagenet3d/train_rcnn_view.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 120000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_view" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/imagenet3d/solver_rpn_msr.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/imagenet3d/train_rpn_msr.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 120000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_rpn_msr" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_test/solver_rcnn_multiscale.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_test/train_rcnn_multiscale.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_multiscale" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_test/solver_rcnn_multiscale_6k8k.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_test/train_rcnn_multiscale.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 60000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_multiscale_6k8k" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_test/solver_rcnn_original_msr_6k8k.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_test/train_rcnn_original.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 60000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_original_msr_6k8k" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_test/solver_rpn.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_test/train_rpn.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_rpn" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_test/solver_rpn_6k8k.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_test/train_rpn.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 60000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_rpn_6k8k" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_test/solver_rpn_msr_6k8k.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_test/train_rpn_msr.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 60000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_rpn_msr_6k8k" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_tracking_test/solver_rcnn_multiscale.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_tracking_test/train_rcnn_multiscale.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 60000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_multiscale_trainval" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_tracking_test/solver_rpn.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_tracking_test/train_rpn.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_rpn_trainval" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_tracking_val/solver_rcnn_multiscale.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_tracking_val/train_rcnn_multiscale.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_multiscale" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_tracking_val/solver_rpn.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_tracking_val/train_rpn.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_rpn" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_val/solver_rcnn.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_val/train_rcnn.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_val/solver_rcnn_2d_multiscale.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_val/train_rcnn_multiscale.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_2d_multiscale" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_val/solver_rcnn_fix.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_val/train_rcnn_fix.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_fix" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_val/solver_rcnn_msr.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_val/train_rcnn.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_msr" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_val/solver_rcnn_msr_fix.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_val/train_rcnn_fix.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_msr_fix" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_val/solver_rcnn_msr_multiscale.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_val/train_rcnn_multiscale.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_msr_multiscale" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_val/solver_rcnn_msr_multiscale_fix.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_val/train_rcnn_multiscale_fix.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_msr_multiscale_fix" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_val/solver_rcnn_multiscale.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_val/train_rcnn_multiscale.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_multiscale" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_val/solver_rcnn_noextra.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_val/train_rcnn.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_noextra" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_val/solver_rcnn_original.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_val/train_rcnn_original.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_original" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_val/solver_rcnn_original_msr.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_val/train_rcnn_original.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_original_msr" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_val/solver_rcnn_original_multiscale.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_val/train_rcnn_original_multiscale.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_original_multiscale" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_val/solver_rpn.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_val/train_rpn.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_rpn" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_val/solver_rpn_2d.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_val/train_rpn.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_rpn_2d" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_val/solver_rpn_fix.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_val/train_rpn_fix.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_rpn_fix" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_val/solver_rpn_msr.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_val/train_rpn_msr.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_rpn_msr" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_val/solver_rpn_msr_fix.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_val/train_rpn_msr_fix.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_rpn_msr_fix" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/kitti_val/solver_rpn_msr_multiscale_fix.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/kitti_val/train_rpn_msr_fix.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_rpn_msr_multiscale_fix" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/mot_tracking_train/solver_rcnn_multiscale.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/mot_tracking_train/train_rcnn_multiscale.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_multiscale" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/mot_tracking_train/solver_rpn.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/mot_tracking_train/train_rpn.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 60000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_rpn" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/no_bbox_reg/solver.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/no_bbox_reg/train.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/pascal2007/solver_rcnn.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/pascal2007/train_rcnn.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/pascal2007/solver_rcnn_original.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/pascal2007/train_rcnn_original.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_original" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/pascal2007/solver_rpn.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/pascal2007/train_rpn.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 60000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn_rpn" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/piecewise/solver.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/piecewise/train.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/CaffeNet/solver.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/CaffeNet/train.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "caffenet_fast_rcnn" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/GoogleNet/kitti_test/solver_rcnn.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/GoogleNet/kitti_test/train_rcnn.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 60000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "googlenet_fast_rcnn" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/GoogleNet/kitti_val/solver_rcnn.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/GoogleNet/kitti_val/train_rcnn.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "googlenet_fast_rcnn" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/GoogleNet/quick_solver.prototxt: -------------------------------------------------------------------------------- 1 | net: "models/bvlc_googlenet/train_val.prototxt" 2 | test_iter: 1000 3 | test_interval: 4000 4 | test_initialization: false 5 | display: 40 6 | average_loss: 40 7 | base_lr: 0.01 8 | lr_policy: "poly" 9 | power: 0.5 10 | max_iter: 2400000 11 | momentum: 0.9 12 | weight_decay: 0.0002 13 | snapshot: 40000 14 | snapshot_prefix: "models/bvlc_googlenet/bvlc_googlenet_quick" 15 | solver_mode: GPU 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/GoogleNet/solver.prototxt: -------------------------------------------------------------------------------- 1 | net: "models/bvlc_googlenet/train_val.prototxt" 2 | test_iter: 1000 3 | test_interval: 4000 4 | test_initialization: false 5 | display: 40 6 | average_loss: 40 7 | base_lr: 0.01 8 | lr_policy: "step" 9 | stepsize: 320000 10 | gamma: 0.96 11 | max_iter: 10000000 12 | momentum: 0.9 13 | weight_decay: 0.0002 14 | snapshot: 40000 15 | snapshot_prefix: "models/bvlc_googlenet/bvlc_googlenet" 16 | solver_mode: GPU 17 | -------------------------------------------------------------------------------- /fast-rcnn/models/README.md: -------------------------------------------------------------------------------- 1 | Prototxt files that define models and solvers. 2 | 3 | Three models are defined, with some variations of each to support experiments 4 | in the paper. 5 | - Caffenet (model **S**) 6 | - VGG_CNN_M_1024 (model **M**) 7 | - VGG16 (model **L**) 8 | -------------------------------------------------------------------------------- /fast-rcnn/models/VGG16/fc_only/solver.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/VGG16/fc_only/train.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | # iter_size: 1 9 | momentum: 0.9 10 | weight_decay: 0.0005 11 | # We disable standard caffe solver snapshotting and implement our own snapshot 12 | # function 13 | snapshot: 0 14 | # We still use the snapshot prefix, though 15 | snapshot_prefix: "vgg16_fast_rcnn" 16 | #debug_info: true 17 | -------------------------------------------------------------------------------- /fast-rcnn/models/VGG16/imagenet3d/solver_rcnn_original.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/VGG16/imagenet3d/train_rcnn_original.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 120000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "vgg16_fast_rcnn_original" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/VGG16/imagenet3d/solver_rcnn_view.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/VGG16/imagenet3d/train_rcnn_view.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 120000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "vgg16_fast_rcnn_view" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/VGG16/imagenet3d/solver_rpn_msr.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/VGG16/imagenet3d/train_rpn_msr.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 120000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "vgg16_fast_rcnn_rpn_msr" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/VGG16/kitti_test/solver_rcnn_multiscale_6k8k.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/VGG16/kitti_test/train_rcnn_multiscale.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 60000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "vgg16_fast_rcnn_multiscale_6k8k" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/VGG16/kitti_tracking_test/solver_rcnn_multiscale.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/VGG16/kitti_tracking_test/train_rcnn_multiscale.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 60000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "vgg16_fast_rcnn_multiscale_trainval" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/VGG16/mot_tracking_test/solver_rcnn_multiscale.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/VGG16/mot_tracking_test/train_rcnn_multiscale.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 60000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "vgg16_fast_rcnn_multiscale" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/VGG16/no_bbox_reg/solver.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/VGG16/no_bbox_reg/train.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | # iter_size: 1 9 | momentum: 0.9 10 | weight_decay: 0.0005 11 | # We disable standard caffe solver snapshotting and implement our own snapshot 12 | # function 13 | snapshot: 0 14 | # We still use the snapshot prefix, though 15 | snapshot_prefix: "vgg16_fast_rcnn" 16 | #debug_info: true 17 | -------------------------------------------------------------------------------- /fast-rcnn/models/VGG16/pascal2007/solver_rcnn_original.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/VGG16/pascal2007/train_rcnn_original.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "vgg16_fast_rcnn_original" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/VGG16/pascal2007/solver_rcnn_original_multiscale.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/VGG16/pascal2007/train_rcnn_original_multiscale.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "vgg16_fast_rcnn_original_multiscale" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/VGG16/pascal2007/solver_rpn.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/VGG16/pascal2007/train_rpn.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "vgg16_fast_rcnn_rpn" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/VGG16/pascal2007/solver_rpn_6k8k.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/VGG16/pascal2007/train_rpn.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 60000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "vgg16_fast_rcnn_rpn_6k8k" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/VGG16/pascal2007/solver_rpn_cls.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/VGG16/pascal2007/train_rpn_cls.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "vgg16_fast_rcnn_rpn_cls" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/VGG16/pascal3d/solver_rcnn.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/VGG16/pascal3d/train_rcnn.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "vgg16_fast_rcnn" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/VGG16/pascal3d/solver_rcnn_multiscale.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/VGG16/pascal3d/train_rcnn_multiscale.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "vgg16_fast_rcnn_multiscale" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/VGG16/pascal3d/solver_rcnn_original.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/VGG16/pascal3d/train_rcnn_original.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "vgg16_fast_rcnn_original" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/VGG16/pascal3d/solver_rcnn_pose.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/VGG16/pascal3d/train_rcnn_pose.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "vgg16_fast_rcnn_pose" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/VGG16/pascal3d/solver_rcnn_pose_multiscale.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/VGG16/pascal3d/train_rcnn_pose_multiscale.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "vgg16_fast_rcnn_pose_multiscale" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/VGG16/pascal3d/solver_rpn.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/VGG16/pascal3d/train_rpn.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "vgg16_fast_rcnn_rpn" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/VGG16/pascal3d/solver_rpn_6k8k.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/VGG16/pascal3d/train_rpn.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 60000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "vgg16_fast_rcnn_rpn_6k8k" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/VGG16/pascal3d/solver_rpn_msr.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/VGG16/pascal3d/train_rpn_msr.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "vgg16_fast_rcnn_rpn_msr" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/VGG16/piecewise/solver.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/VGG16/piecewise/train.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | # iter_size: 1 9 | momentum: 0.9 10 | weight_decay: 0.0005 11 | # We disable standard caffe solver snapshotting and implement our own snapshot 12 | # function 13 | snapshot: 0 14 | # We still use the snapshot prefix, though 15 | snapshot_prefix: "vgg16_fast_rcnn" 16 | #debug_info: true 17 | -------------------------------------------------------------------------------- /fast-rcnn/models/VGG16/solver.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/VGG16/train.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | # iter_size: 1 9 | momentum: 0.9 10 | weight_decay: 0.0005 11 | # We disable standard caffe solver snapshotting and implement our own snapshot 12 | # function 13 | snapshot: 0 14 | # We still use the snapshot prefix, though 15 | snapshot_prefix: "vgg16_fast_rcnn" 16 | #debug_info: true 17 | -------------------------------------------------------------------------------- /fast-rcnn/models/VGG_CNN_M_1024/no_bbox_reg/solver.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/VGG_CNN_M_1024/no_bbox_reg/train.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "vgg_cnn_m_1024_fast_rcnn" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/VGG_CNN_M_1024/piecewise/solver.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/VGG_CNN_M_1024/piecewise/train.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "vgg_cnn_m_1024_fast_rcnn" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/models/VGG_CNN_M_1024/solver.prototxt: -------------------------------------------------------------------------------- 1 | train_net: "models/VGG_CNN_M_1024/train.prototxt" 2 | base_lr: 0.001 3 | lr_policy: "step" 4 | gamma: 0.1 5 | stepsize: 30000 6 | display: 20 7 | average_loss: 100 8 | momentum: 0.9 9 | weight_decay: 0.0005 10 | # We disable standard caffe solver snapshotting and implement our own snapshot 11 | # function 12 | snapshot: 0 13 | # We still use the snapshot prefix, though 14 | snapshot_prefix: "vgg_cnn_m_1024_fast_rcnn" 15 | #debug_info: true 16 | -------------------------------------------------------------------------------- /fast-rcnn/tools/README.md: -------------------------------------------------------------------------------- 1 | Tools for training, testing, and compressing Fast R-CNN networks. 2 | -------------------------------------------------------------------------------- /fast-rcnn/tools/_init_paths.py: -------------------------------------------------------------------------------- 1 | # -------------------------------------------------------- 2 | # Fast R-CNN 3 | # Copyright (c) 2015 Microsoft 4 | # Licensed under The MIT License [see LICENSE for details] 5 | # Written by Ross Girshick 6 | # -------------------------------------------------------- 7 | 8 | """Set up paths for Fast R-CNN.""" 9 | 10 | import os.path as osp 11 | import sys 12 | 13 | def add_path(path): 14 | if path not in sys.path: 15 | sys.path.insert(0, path) 16 | 17 | this_dir = osp.dirname(__file__) 18 | 19 | # Add caffe to PYTHONPATH 20 | caffe_path = osp.join(this_dir, '..', '..', 'caffe-fast-rcnn', 'python') 21 | add_path(caffe_path) 22 | 23 | # Add lib to PYTHONPATH 24 | lib_path = osp.join(this_dir, '..', 'lib') 25 | add_path(lib_path) 26 | --------------------------------------------------------------------------------