├── .gitignore ├── README.md ├── a_demos ├── camera_dahua_sdk.py ├── camera_huawei.py ├── camera_rtsp.py ├── class_demo.py ├── cv_cartoon.py ├── cv_contour.py ├── cv_image_polygon_cut.py ├── cv_svm_ocr_hand_written_digits.py ├── data │ ├── AirPassengers.csv │ ├── digits.png │ ├── economics.csv │ ├── excel_write.xlsx │ ├── file.txt │ ├── localhost.pem │ ├── midwest_filter.csv │ ├── mpg_ggplot2.csv │ ├── mtcars.csv │ ├── penguins.csv │ ├── test.xlsx │ └── to_excel.xlsx ├── dict_demo.py ├── file_rename.py ├── ftp_demo.py ├── function_demo.py ├── hashlib_demo.py ├── images │ ├── Canny.jpg │ ├── Warped.jpg │ ├── background.jpg │ ├── ball.gif │ ├── dog.jpg │ ├── dog.png │ ├── dog_cut.png │ ├── dog_cut2.png │ ├── gray_image.jpg │ ├── my_square_function.png │ ├── my_wiggly_animation.gif │ ├── notecard.png │ ├── obama.jpg │ ├── resized_image_400.jpg │ ├── rotation_bound_image_45.jpg │ ├── rotation_image_90.jpg │ ├── skeleton_Canny_image.jpg │ ├── skeleton_image.jpg │ └── translation_image.jpg ├── imutils_demo.py ├── imutils_perspective.py ├── io_file.py ├── json_requests.py ├── list_tuple_dict_set.py ├── logging_demo.py ├── loop_demo.py ├── matplotlib_demos.py ├── matplotlib_patches.py ├── matplotlib_plotting_tutorial.py ├── matplotlib_style_subplot.py ├── matplotlib_tips.py ├── numpy_fractal_Mandelbrot_set.py ├── operator_demo.py ├── pandas_excel_read_write.py ├── pil_demo.py ├── pil_image_cut.py ├── pil_image_polygon_cut.py ├── print_demo.py ├── private_variable.py ├── queue_thread_demo.py ├── sort_index.py ├── spider_image_baidu.py ├── string_demo.py ├── thread_demo.py ├── time_day_demo.py ├── try_demo.py └── typer_demo.py ├── dlib_face_recognition ├── blur_faces.py ├── digital_makeup.py ├── dlib_demo.py ├── face_recognition_demo.py ├── face_recognition_svm.py ├── face_recognition_video_demo.py ├── find_faces_in_batches.py ├── resources │ └── images │ │ ├── alex-lacamoire.png │ │ ├── biden.jpg │ │ ├── five_people.jpg │ │ ├── lin-manuel-miranda.png │ │ ├── obama.jpg │ │ ├── obama2.jpg │ │ ├── obama_and_biden.jpg │ │ ├── test_image.jpg │ │ ├── train_dir │ │ ├── ChenHe │ │ │ ├── 0.jpg │ │ │ ├── 1.jpg │ │ │ ├── 10.jpg │ │ │ ├── 11.jpg │ │ │ ├── 12.jpg │ │ │ ├── 13.jpg │ │ │ ├── 14.jpg │ │ │ ├── 15.jpg │ │ │ ├── 17.jpg │ │ │ ├── 18.jpg │ │ │ ├── 19.jpg │ │ │ ├── 2.jpg │ │ │ ├── 20.jpg │ │ │ ├── 21.jpg │ │ │ ├── 22.jpg │ │ │ ├── 23.jpg │ │ │ ├── 24.jpg │ │ │ ├── 25.jpg │ │ │ ├── 26.jpg │ │ │ ├── 27.jpg │ │ │ ├── 28.jpg │ │ │ ├── 29.jpg │ │ │ ├── 3.jpg │ │ │ ├── 30.jpg │ │ │ ├── 4.jpg │ │ │ ├── 5.jpg │ │ │ ├── 6.jpg │ │ │ ├── 7.jpg │ │ │ ├── 8.jpg │ │ │ └── 9.jpg │ │ ├── Jay │ │ │ ├── 0.jpg │ │ │ ├── 1.jpg │ │ │ ├── 10.jpg │ │ │ ├── 11.jpg │ │ │ ├── 12.jpg │ │ │ ├── 13.jpg │ │ │ ├── 14.jpg │ │ │ ├── 15.jpg │ │ │ ├── 16.jpg │ │ │ ├── 17.jpg │ │ │ ├── 18.jpg │ │ │ ├── 19.jpg │ │ │ ├── 2.jpg │ │ │ ├── 20.jpg │ │ │ ├── 22.jpg │ │ │ ├── 23.jpg │ │ │ ├── 24.jpg │ │ │ ├── 25.jpg │ │ │ ├── 26.jpg │ │ │ ├── 27.jpg │ │ │ ├── 29.jpg │ │ │ ├── 3.jpg │ │ │ ├── 30.jpg │ │ │ ├── 4.jpg │ │ │ ├── 5.jpg │ │ │ ├── 6.jpg │ │ │ ├── 7.jpg │ │ │ ├── 8.jpg │ │ │ └── 9.jpg │ │ └── KunLin │ │ │ ├── 0.jpg │ │ │ ├── 1.jpg │ │ │ ├── 10.jpg │ │ │ ├── 11.jpg │ │ │ ├── 12.jpg │ │ │ ├── 13.jpg │ │ │ ├── 14.jpg │ │ │ ├── 15.jpg │ │ │ ├── 16.jpg │ │ │ ├── 17.jpg │ │ │ ├── 19.jpg │ │ │ ├── 2.jpg │ │ │ ├── 20.jpg │ │ │ ├── 21.jpg │ │ │ ├── 23.jpg │ │ │ ├── 24.jpg │ │ │ ├── 25.jpg │ │ │ ├── 26.jpg │ │ │ ├── 27.jpg │ │ │ ├── 28.jpg │ │ │ ├── 3.jpg │ │ │ ├── 30.jpg │ │ │ ├── 4.jpg │ │ │ ├── 5.jpg │ │ │ ├── 6.jpg │ │ │ ├── 7.jpg │ │ │ ├── 8.jpg │ │ │ └── 9.jpg │ │ └── two_people.jpg └── sleep_detection.py ├── keras ├── demo_mnist.py └── demo_mnist_cnn.py ├── ppyolo ├── configs │ ├── cascade_rcnn │ │ ├── README.md │ │ ├── _base_ │ │ │ ├── cascade_fpn_reader.yml │ │ │ ├── cascade_mask_fpn_reader.yml │ │ │ ├── cascade_mask_rcnn_r50_fpn.yml │ │ │ ├── cascade_rcnn_r50_fpn.yml │ │ │ └── optimizer_1x.yml │ │ ├── cascade_mask_rcnn_r50_fpn_1x_coco.yml │ │ ├── cascade_mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml │ │ ├── cascade_mask_rcnn_r50_vd_fpn_ssld_2x_coco.yml │ │ ├── cascade_rcnn_r50_fpn_1x_coco.yml │ │ ├── cascade_rcnn_r50_vd_fpn_ssld_1x_coco.yml │ │ └── cascade_rcnn_r50_vd_fpn_ssld_2x_coco.yml │ ├── datasets │ │ ├── coco_detection.yml │ │ ├── coco_instance.yml │ │ ├── dota.yml │ │ ├── mot.yml │ │ ├── roadsign_voc.yml │ │ ├── voc.yml │ │ └── wider_face.yml │ ├── dcn │ │ ├── README.md │ │ ├── cascade_rcnn_dcn_r50_fpn_1x_coco.yml │ │ ├── cascade_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.yml │ │ ├── faster_rcnn_dcn_r101_vd_fpn_1x_coco.yml │ │ ├── faster_rcnn_dcn_r50_fpn_1x_coco.yml │ │ ├── faster_rcnn_dcn_r50_vd_fpn_1x_coco.yml │ │ ├── faster_rcnn_dcn_r50_vd_fpn_2x_coco.yml │ │ ├── faster_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.yml │ │ ├── mask_rcnn_dcn_r101_vd_fpn_1x_coco.yml │ │ ├── mask_rcnn_dcn_r50_fpn_1x_coco.yml │ │ ├── mask_rcnn_dcn_r50_vd_fpn_2x_coco.yml │ │ └── mask_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.yml │ ├── dota │ │ ├── README.md │ │ ├── _base_ │ │ │ ├── s2anet.yml │ │ │ ├── s2anet_optimizer_1x.yml │ │ │ └── s2anet_reader.yml │ │ ├── s2anet_1x_dota.yml │ │ └── s2anet_conv_1x_dota.yml │ ├── face_detection │ │ ├── README.md │ │ ├── _base_ │ │ │ ├── blazeface.yml │ │ │ ├── blazeface_fpn.yml │ │ │ ├── face_reader.yml │ │ │ └── optimizer_1000e.yml │ │ ├── blazeface_1000e.yml │ │ └── blazeface_fpn_ssh_1000e.yml │ ├── faster_rcnn │ │ ├── README.md │ │ ├── _base_ │ │ │ ├── faster_fpn_reader.yml │ │ │ ├── faster_rcnn_r50.yml │ │ │ ├── faster_rcnn_r50_fpn.yml │ │ │ ├── faster_reader.yml │ │ │ └── optimizer_1x.yml │ │ ├── faster_rcnn_r101_1x_coco.yml │ │ ├── faster_rcnn_r101_fpn_1x_coco.yml │ │ ├── faster_rcnn_r101_fpn_2x_coco.yml │ │ ├── faster_rcnn_r101_vd_fpn_1x_coco.yml │ │ ├── faster_rcnn_r101_vd_fpn_2x_coco.yml │ │ ├── faster_rcnn_r34_fpn_1x_coco.yml │ │ ├── faster_rcnn_r34_vd_fpn_1x_coco.yml │ │ ├── faster_rcnn_r50_1x_coco.yml │ │ ├── faster_rcnn_r50_fpn_1x_coco.yml │ │ ├── faster_rcnn_r50_fpn_2x_coco.yml │ │ ├── faster_rcnn_r50_vd_1x_coco.yml │ │ ├── faster_rcnn_r50_vd_fpn_1x_coco.yml │ │ ├── faster_rcnn_r50_vd_fpn_2x_coco.yml │ │ ├── faster_rcnn_r50_vd_fpn_ssld_1x_coco.yml │ │ ├── faster_rcnn_r50_vd_fpn_ssld_2x_coco.yml │ │ ├── faster_rcnn_x101_vd_64x4d_fpn_1x_coco.yml │ │ └── faster_rcnn_x101_vd_64x4d_fpn_2x_coco.yml │ ├── fcos │ │ ├── README.md │ │ ├── _base_ │ │ │ ├── fcos_r50_fpn.yml │ │ │ ├── fcos_reader.yml │ │ │ └── optimizer_1x.yml │ │ ├── fcos_dcn_r50_fpn_1x_coco.yml │ │ ├── fcos_r50_fpn_1x_coco.yml │ │ └── fcos_r50_fpn_multiscale_2x_coco.yml │ ├── gn │ │ ├── README.md │ │ ├── cascade_mask_rcnn_r50_fpn_gn_2x_coco.yml │ │ ├── cascade_rcnn_r50_fpn_gn_2x_coco.yml │ │ ├── faster_rcnn_r50_fpn_gn_2x_coco.yml │ │ └── mask_rcnn_r50_fpn_gn_2x_coco.yml │ ├── hrnet │ │ ├── README.md │ │ ├── _base_ │ │ │ └── faster_rcnn_hrnetv2p_w18.yml │ │ ├── faster_rcnn_hrnetv2p_w18_1x_coco.yml │ │ └── faster_rcnn_hrnetv2p_w18_2x_coco.yml │ ├── keypoint │ │ ├── README.md │ │ ├── football_keypoint.gif │ │ ├── higherhrnet │ │ │ ├── higherhrnet_hrnet_w32_512.yml │ │ │ ├── higherhrnet_hrnet_w32_512_swahr.yml │ │ │ └── higherhrnet_hrnet_w32_640.yml │ │ └── hrnet │ │ │ ├── hrnet_w32_256x192.yml │ │ │ └── hrnet_w32_384x288.yml │ ├── mask_rcnn │ │ ├── README.md │ │ ├── _base_ │ │ │ ├── mask_fpn_reader.yml │ │ │ ├── mask_rcnn_r50.yml │ │ │ ├── mask_rcnn_r50_fpn.yml │ │ │ ├── mask_reader.yml │ │ │ └── optimizer_1x.yml │ │ ├── mask_rcnn_r101_fpn_1x_coco.yml │ │ ├── mask_rcnn_r101_vd_fpn_1x_coco.yml │ │ ├── mask_rcnn_r50_1x_coco.yml │ │ ├── mask_rcnn_r50_2x_coco.yml │ │ ├── mask_rcnn_r50_fpn_1x_coco.yml │ │ ├── mask_rcnn_r50_fpn_2x_coco.yml │ │ ├── mask_rcnn_r50_vd_fpn_1x_coco.yml │ │ ├── mask_rcnn_r50_vd_fpn_2x_coco.yml │ │ ├── mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml │ │ ├── mask_rcnn_r50_vd_fpn_ssld_2x_coco.yml │ │ ├── mask_rcnn_x101_vd_64x4d_fpn_1x_coco.yml │ │ └── mask_rcnn_x101_vd_64x4d_fpn_2x_coco.yml │ ├── mot │ │ ├── README.md │ │ ├── README_cn.md │ │ ├── deepsort │ │ │ ├── README.md │ │ │ ├── README_cn.md │ │ │ ├── _base_ │ │ │ │ ├── deepsort_reader_1088x608.yml │ │ │ │ └── deepsort_yolov3_darknet53_pcb_pyramid_r101.yml │ │ │ └── deepsort_pcb_pyramid_r101.yml │ │ ├── fairmot │ │ │ ├── README.md │ │ │ ├── README_cn.md │ │ │ ├── _base_ │ │ │ │ ├── fairmot_dla34.yml │ │ │ │ ├── fairmot_reader_1088x608.yml │ │ │ │ └── optimizer_30e.yml │ │ │ └── fairmot_dla34_30e_1088x608.yml │ │ └── jde │ │ │ ├── README.md │ │ │ ├── README_cn.md │ │ │ ├── _base_ │ │ │ ├── jde_darknet53.yml │ │ │ ├── jde_reader_1088x608.yml │ │ │ ├── jde_reader_576x320.yml │ │ │ ├── jde_reader_864x480.yml │ │ │ ├── optimizer_30e.yml │ │ │ └── optimizer_60e.yml │ │ │ ├── jde_darknet53_30e_1088x608.yml │ │ │ ├── jde_darknet53_30e_576x320.yml │ │ │ └── jde_darknet53_30e_864x480.yml │ ├── pedestrian │ │ ├── README.md │ │ ├── README_cn.md │ │ ├── demo │ │ │ ├── 001.png │ │ │ ├── 002.png │ │ │ ├── 003.png │ │ │ └── 004.png │ │ └── pedestrian_yolov3_darknet.yml │ ├── ppyolo │ │ ├── README.md │ │ ├── README_cn.md │ │ ├── _base_ │ │ │ ├── optimizer_1x.yml │ │ │ ├── optimizer_2x.yml │ │ │ ├── optimizer_365e.yml │ │ │ ├── optimizer_650e.yml │ │ │ ├── ppyolo_mbv3_large.yml │ │ │ ├── ppyolo_mbv3_small.yml │ │ │ ├── ppyolo_r18vd.yml │ │ │ ├── ppyolo_r50vd_dcn.yml │ │ │ ├── ppyolo_reader.yml │ │ │ ├── ppyolo_tiny.yml │ │ │ ├── ppyolo_tiny_reader.yml │ │ │ ├── ppyolov2_r50vd_dcn.yml │ │ │ └── ppyolov2_reader.yml │ │ ├── ppyolo_mbv3_large_coco.yml │ │ ├── ppyolo_mbv3_small_coco.yml │ │ ├── ppyolo_r18vd_coco.yml │ │ ├── ppyolo_r50vd_dcn_1x_coco.yml │ │ ├── ppyolo_r50vd_dcn_1x_minicoco.yml │ │ ├── ppyolo_r50vd_dcn_2x_coco.yml │ │ ├── ppyolo_r50vd_dcn_voc.yml │ │ ├── ppyolo_test.yml │ │ ├── ppyolo_tiny_650e_coco.yml │ │ ├── ppyolov2_r101vd_dcn_365e_coco.yml │ │ ├── ppyolov2_r50vd_dcn_365e_coco.yml │ │ └── ppyolov2_r50vd_dcn_voc.yml │ ├── rcnn_enhance │ │ ├── README.md │ │ ├── _base_ │ │ │ ├── faster_rcnn_enhance.yml │ │ │ ├── faster_rcnn_enhance_reader.yml │ │ │ └── optimizer_3x.yml │ │ └── faster_rcnn_enhance_3x_coco.yml │ ├── res2net │ │ ├── README.md │ │ ├── faster_rcnn_res2net50_vb_26w_4s_fpn_1x_coco.yml │ │ ├── mask_rcnn_res2net50_vb_26w_4s_fpn_2x_coco.yml │ │ └── mask_rcnn_res2net50_vd_26w_4s_fpn_2x_coco.yml │ ├── runtime.yml │ ├── slim │ │ ├── README.md │ │ ├── distill │ │ │ ├── README.md │ │ │ └── yolov3_mobilenet_v1_coco_distill.yml │ │ ├── extensions │ │ │ └── yolov3_mobilenet_v1_coco_distill_prune.yml │ │ ├── prune │ │ │ ├── ppyolo_mbv3_large_prune_fpgm.yml │ │ │ ├── ppyolo_r50vd_prune_fpgm.yml │ │ │ ├── yolov3_darknet_prune_fpgm.yml │ │ │ ├── yolov3_prune_fpgm.yml │ │ │ └── yolov3_prune_l1_norm.yml │ │ └── quant │ │ │ ├── mask_rcnn_r50_fpn_1x_qat.yml │ │ │ ├── ppyolo_mbv3_large_qat.yml │ │ │ ├── ppyolo_r50vd_qat_pact.yml │ │ │ ├── ppyolov2_r50vd_dcn_qat.yml │ │ │ ├── ssd_mobilenet_v1_qat.yml │ │ │ ├── yolov3_darknet_qat.yml │ │ │ ├── yolov3_mobilenet_v1_qat.yml │ │ │ └── yolov3_mobilenet_v3_qat.yml │ ├── solov2 │ │ ├── README.md │ │ ├── _base_ │ │ │ ├── optimizer_1x.yml │ │ │ ├── solov2_r50_fpn.yml │ │ │ └── solov2_reader.yml │ │ ├── solov2_r50_fpn_1x_coco.yml │ │ └── solov2_r50_fpn_3x_coco.yml │ ├── ssd │ │ ├── README.md │ │ ├── _base_ │ │ │ ├── optimizer_120e.yml │ │ │ ├── optimizer_1700e.yml │ │ │ ├── optimizer_240e.yml │ │ │ ├── ssd_mobilenet_reader.yml │ │ │ ├── ssd_mobilenet_v1_300.yml │ │ │ ├── ssd_reader.yml │ │ │ ├── ssd_vgg16_300.yml │ │ │ ├── ssdlite300_reader.yml │ │ │ ├── ssdlite320_reader.yml │ │ │ ├── ssdlite_ghostnet_320.yml │ │ │ ├── ssdlite_mobilenet_v1_300.yml │ │ │ ├── ssdlite_mobilenet_v3_large_320.yml │ │ │ └── ssdlite_mobilenet_v3_small_320.yml │ │ ├── ssd_mobilenet_v1_300_120e_voc.yml │ │ ├── ssd_vgg16_300_240e_voc.yml │ │ ├── ssdlite_ghostnet_320_coco.yml │ │ ├── ssdlite_mobilenet_v1_300_coco.yml │ │ ├── ssdlite_mobilenet_v3_large_320_coco.yml │ │ └── ssdlite_mobilenet_v3_small_320_coco.yml │ ├── ttfnet │ │ ├── README.md │ │ ├── _base_ │ │ │ ├── optimizer_10x.yml │ │ │ ├── optimizer_1x.yml │ │ │ ├── optimizer_20x.yml │ │ │ ├── pafnet.yml │ │ │ ├── pafnet_lite.yml │ │ │ ├── pafnet_lite_reader.yml │ │ │ ├── pafnet_reader.yml │ │ │ ├── ttfnet_darknet53.yml │ │ │ └── ttfnet_reader.yml │ │ ├── pafnet_10x_coco.yml │ │ ├── pafnet_lite_mobilenet_v3_20x_coco.yml │ │ └── ttfnet_darknet53_1x_coco.yml │ ├── vehicle │ │ ├── README.md │ │ ├── README_cn.md │ │ ├── demo │ │ │ ├── 001.jpeg │ │ │ ├── 003.png │ │ │ ├── 004.png │ │ │ └── 005.png │ │ └── vehicle_yolov3_darknet.yml │ └── yolov3 │ │ ├── README.md │ │ ├── _base_ │ │ ├── optimizer_270e.yml │ │ ├── optimizer_40e.yml │ │ ├── yolov3_darknet53.yml │ │ ├── yolov3_mobilenet_v1.yml │ │ ├── yolov3_mobilenet_v3_large.yml │ │ ├── yolov3_mobilenet_v3_small.yml │ │ ├── yolov3_r34.yml │ │ ├── yolov3_r50vd_dcn.yml │ │ └── yolov3_reader.yml │ │ ├── yolov3_darknet53_270e_coco.yml │ │ ├── yolov3_darknet53_270e_voc.yml │ │ ├── yolov3_mobilenet_v1_270e_coco.yml │ │ ├── yolov3_mobilenet_v1_270e_voc.yml │ │ ├── yolov3_mobilenet_v1_roadsign.yml │ │ ├── yolov3_mobilenet_v1_ssld_270e_coco.yml │ │ ├── yolov3_mobilenet_v1_ssld_270e_voc.yml │ │ ├── yolov3_mobilenet_v3_large_270e_coco.yml │ │ ├── yolov3_mobilenet_v3_large_270e_voc.yml │ │ ├── yolov3_mobilenet_v3_large_ssld_270e_voc.yml │ │ ├── yolov3_r34_270e_coco.yml │ │ └── yolov3_r50vd_dcn_270e_coco.yml ├── infer.py ├── paddle_detector.py ├── ppdet │ ├── __init__.py │ ├── core │ │ ├── __init__.py │ │ ├── config │ │ │ ├── __init__.py │ │ │ ├── schema.py │ │ │ └── yaml_helpers.py │ │ └── workspace.py │ ├── data │ │ ├── __init__.py │ │ ├── reader.py │ │ ├── shm_utils.py │ │ ├── source │ │ │ ├── __init__.py │ │ │ ├── category.py │ │ │ ├── coco.py │ │ │ ├── dataset.py │ │ │ ├── keypoint_coco.py │ │ │ ├── mot.py │ │ │ ├── voc.py │ │ │ └── widerface.py │ │ └── transform │ │ │ ├── __init__.py │ │ │ ├── autoaugment_utils.py │ │ │ ├── batch_operators.py │ │ │ ├── gridmask_utils.py │ │ │ ├── keypoint_operators.py │ │ │ ├── mot_operators.py │ │ │ ├── op_helper.py │ │ │ └── operators.py │ ├── engine │ │ ├── __init__.py │ │ ├── callbacks.py │ │ ├── env.py │ │ ├── export_utils.py │ │ ├── tracker.py │ │ └── trainer.py │ ├── ext_op │ │ ├── README.md │ │ ├── rbox_iou_op.cc │ │ ├── rbox_iou_op.cu │ │ ├── setup.py │ │ └── test.py │ ├── metrics │ │ ├── __init__.py │ │ ├── coco_utils.py │ │ ├── json_results.py │ │ ├── keypoint_metrics.py │ │ ├── map_utils.py │ │ ├── metrics.py │ │ ├── mot_eval_utils.py │ │ ├── mot_metrics.py │ │ └── widerface_utils.py │ ├── model_zoo │ │ ├── .gitignore │ │ ├── __init__.py │ │ ├── model_zoo.py │ │ └── tests │ │ │ ├── __init__.py │ │ │ ├── test_get_model.py │ │ │ └── test_list_model.py │ ├── modeling │ │ ├── __init__.py │ │ ├── architectures │ │ │ ├── __init__.py │ │ │ ├── blazeface.py │ │ │ ├── cascade_rcnn.py │ │ │ ├── centernet.py │ │ │ ├── deepsort.py │ │ │ ├── fairmot.py │ │ │ ├── faster_rcnn.py │ │ │ ├── fcos.py │ │ │ ├── jde.py │ │ │ ├── keypoint_hrhrnet.py │ │ │ ├── keypoint_hrnet.py │ │ │ ├── mask_rcnn.py │ │ │ ├── meta_arch.py │ │ │ ├── s2anet.py │ │ │ ├── solov2.py │ │ │ ├── ssd.py │ │ │ ├── ttfnet.py │ │ │ └── yolo.py │ │ ├── backbones │ │ │ ├── __init__.py │ │ │ ├── blazenet.py │ │ │ ├── darknet.py │ │ │ ├── dla.py │ │ │ ├── ghostnet.py │ │ │ ├── hrnet.py │ │ │ ├── mobilenet_v1.py │ │ │ ├── mobilenet_v3.py │ │ │ ├── name_adapter.py │ │ │ ├── res2net.py │ │ │ ├── resnet.py │ │ │ ├── senet.py │ │ │ └── vgg.py │ │ ├── bbox_utils.py │ │ ├── heads │ │ │ ├── __init__.py │ │ │ ├── bbox_head.py │ │ │ ├── cascade_head.py │ │ │ ├── centernet_head.py │ │ │ ├── face_head.py │ │ │ ├── fcos_head.py │ │ │ ├── keypoint_hrhrnet_head.py │ │ │ ├── mask_head.py │ │ │ ├── roi_extractor.py │ │ │ ├── s2anet_head.py │ │ │ ├── solov2_head.py │ │ │ ├── ssd_head.py │ │ │ ├── ttf_head.py │ │ │ └── yolo_head.py │ │ ├── keypoint_utils.py │ │ ├── layers.py │ │ ├── losses │ │ │ ├── __init__.py │ │ │ ├── ctfocal_loss.py │ │ │ ├── fairmot_loss.py │ │ │ ├── fcos_loss.py │ │ │ ├── iou_aware_loss.py │ │ │ ├── iou_loss.py │ │ │ ├── jde_loss.py │ │ │ ├── keypoint_loss.py │ │ │ ├── solov2_loss.py │ │ │ ├── ssd_loss.py │ │ │ └── yolo_loss.py │ │ ├── mot │ │ │ ├── __init__.py │ │ │ ├── matching │ │ │ │ ├── __init__.py │ │ │ │ ├── deepsort_matching.py │ │ │ │ └── jde_matching.py │ │ │ ├── motion │ │ │ │ ├── __init__.py │ │ │ │ └── kalman_filter.py │ │ │ ├── tracker │ │ │ │ ├── __init__.py │ │ │ │ ├── base_jde_tracker.py │ │ │ │ ├── base_sde_tracker.py │ │ │ │ ├── deepsort_tracker.py │ │ │ │ └── jde_tracker.py │ │ │ ├── utils.py │ │ │ └── visualization.py │ │ ├── necks │ │ │ ├── __init__.py │ │ │ ├── blazeface_fpn.py │ │ │ ├── centernet_fpn.py │ │ │ ├── fpn.py │ │ │ ├── hrfpn.py │ │ │ ├── ttf_fpn.py │ │ │ └── yolo_fpn.py │ │ ├── ops.py │ │ ├── post_process.py │ │ ├── proposal_generator │ │ │ ├── __init__.py │ │ │ ├── anchor_generator.py │ │ │ ├── proposal_generator.py │ │ │ ├── rpn_head.py │ │ │ ├── target.py │ │ │ └── target_layer.py │ │ ├── reid │ │ │ ├── __init__.py │ │ │ ├── fairmot_embedding_head.py │ │ │ ├── jde_embedding_head.py │ │ │ ├── pyramidal_embedding.py │ │ │ └── resnet.py │ │ ├── shape_spec.py │ │ └── tests │ │ │ ├── __init__.py │ │ │ ├── test_architectures.py │ │ │ ├── test_base.py │ │ │ ├── test_ops.py │ │ │ └── test_yolov3_loss.py │ ├── optimizer.py │ ├── slim │ │ ├── __init__.py │ │ ├── distill.py │ │ ├── prune.py │ │ └── quant.py │ └── utils │ │ ├── __init__.py │ │ ├── check.py │ │ ├── checkpoint.py │ │ ├── cli.py │ │ ├── colormap.py │ │ ├── download.py │ │ ├── logger.py │ │ ├── stats.py │ │ ├── visualizer.py │ │ └── voc_utils.py ├── resources │ ├── images │ │ ├── 000000014439.jpg │ │ ├── 000000087038.jpg │ │ └── 000000570688.jpg │ └── runs │ │ ├── 000000014439.jpg │ │ ├── 000000087038.jpg │ │ └── 000000570688.jpg ├── tools │ ├── anchor_cluster.py │ ├── eval.py │ ├── eval_mot.py │ ├── export_model.py │ ├── infer_mot.py │ └── x2coco.py └── train.py ├── pytorch ├── fast_reid │ ├── configs │ │ ├── Base-AGW.yml │ │ ├── Base-MGN.yml │ │ ├── Base-SBS.yml │ │ ├── Base-bagtricks.yml │ │ ├── DukeMTMC │ │ │ ├── AGW_R101-ibn.yml │ │ │ ├── AGW_R50-ibn.yml │ │ │ ├── AGW_R50.yml │ │ │ ├── AGW_S50.yml │ │ │ ├── bagtricks_R101-ibn.yml │ │ │ ├── bagtricks_R50-ibn.yml │ │ │ ├── bagtricks_R50.yml │ │ │ ├── bagtricks_S50.yml │ │ │ ├── mgn_R50-ibn.yml │ │ │ ├── sbs_R101-ibn.yml │ │ │ ├── sbs_R50-ibn.yml │ │ │ ├── sbs_R50.yml │ │ │ └── sbs_S50.yml │ │ ├── MSMT17 │ │ │ ├── AGW_R101-ibn.yml │ │ │ ├── AGW_R50-ibn.yml │ │ │ ├── AGW_R50.yml │ │ │ ├── AGW_S50.yml │ │ │ ├── bagtricks_R101-ibn.yml │ │ │ ├── bagtricks_R50-ibn.yml │ │ │ ├── bagtricks_R50.yml │ │ │ ├── bagtricks_S50.yml │ │ │ ├── mgn_R50-ibn.yml │ │ │ ├── sbs_R101-ibn.yml │ │ │ ├── sbs_R50-ibn.yml │ │ │ ├── sbs_R50.yml │ │ │ └── sbs_S50.yml │ │ ├── Market1501 │ │ │ ├── AGW_R101-ibn.yml │ │ │ ├── AGW_R50-ibn.yml │ │ │ ├── AGW_R50.yml │ │ │ ├── AGW_S50.yml │ │ │ ├── bagtricks_R101-ibn.yml │ │ │ ├── bagtricks_R50-ibn.yml │ │ │ ├── bagtricks_R50.yml │ │ │ ├── bagtricks_S50.yml │ │ │ ├── bagtricks_vit.yml │ │ │ ├── mgn_R50-ibn.yml │ │ │ ├── sbs_R101-ibn.yml │ │ │ ├── sbs_R50-ibn.yml │ │ │ ├── sbs_R50.yml │ │ │ └── sbs_S50.yml │ │ ├── VERIWild │ │ │ └── bagtricks_R50-ibn.yml │ │ ├── VeRi │ │ │ └── sbs_R50-ibn.yml │ │ └── VehicleID │ │ │ └── bagtricks_R50-ibn.yml │ ├── fastreid │ │ ├── __init__.py │ │ ├── config │ │ │ ├── __init__.py │ │ │ ├── config.py │ │ │ └── defaults.py │ │ ├── data │ │ │ ├── __init__.py │ │ │ ├── build.py │ │ │ ├── common.py │ │ │ ├── data_utils.py │ │ │ ├── datasets │ │ │ │ ├── AirportALERT.py │ │ │ │ ├── __init__.py │ │ │ │ ├── bases.py │ │ │ │ ├── caviara.py │ │ │ │ ├── cuhk03.py │ │ │ │ ├── cuhk_sysu.py │ │ │ │ ├── dukemtmcreid.py │ │ │ │ ├── grid.py │ │ │ │ ├── iLIDS.py │ │ │ │ ├── lpw.py │ │ │ │ ├── market1501.py │ │ │ │ ├── msmt17.py │ │ │ │ ├── pes3d.py │ │ │ │ ├── pku.py │ │ │ │ ├── prai.py │ │ │ │ ├── prid.py │ │ │ │ ├── saivt.py │ │ │ │ ├── sensereid.py │ │ │ │ ├── shinpuhkan.py │ │ │ │ ├── sysu_mm.py │ │ │ │ ├── thermalworld.py │ │ │ │ ├── vehicleid.py │ │ │ │ ├── veri.py │ │ │ │ ├── veriwild.py │ │ │ │ ├── viper.py │ │ │ │ └── wildtracker.py │ │ │ ├── samplers │ │ │ │ ├── __init__.py │ │ │ │ ├── data_sampler.py │ │ │ │ ├── imbalance_sampler.py │ │ │ │ └── triplet_sampler.py │ │ │ └── transforms │ │ │ │ ├── __init__.py │ │ │ │ ├── autoaugment.py │ │ │ │ ├── build.py │ │ │ │ ├── functional.py │ │ │ │ └── transforms.py │ │ ├── engine │ │ │ ├── __init__.py │ │ │ ├── defaults.py │ │ │ ├── hooks.py │ │ │ ├── launch.py │ │ │ └── train_loop.py │ │ ├── evaluation │ │ │ ├── __init__.py │ │ │ ├── clas_evaluator.py │ │ │ ├── evaluator.py │ │ │ ├── query_expansion.py │ │ │ ├── rank.py │ │ │ ├── rank_cylib │ │ │ │ ├── Makefile │ │ │ │ ├── __init__.py │ │ │ │ ├── rank_cy.pyx │ │ │ │ ├── roc_cy.pyx │ │ │ │ ├── setup.py │ │ │ │ └── test_cython.py │ │ │ ├── reid_evaluation.py │ │ │ ├── rerank.py │ │ │ ├── roc.py │ │ │ └── testing.py │ │ ├── layers │ │ │ ├── __init__.py │ │ │ ├── activation.py │ │ │ ├── any_softmax.py │ │ │ ├── batch_norm.py │ │ │ ├── context_block.py │ │ │ ├── drop.py │ │ │ ├── frn.py │ │ │ ├── gather_layer.py │ │ │ ├── helpers.py │ │ │ ├── non_local.py │ │ │ ├── pooling.py │ │ │ ├── se_layer.py │ │ │ ├── splat.py │ │ │ └── weight_init.py │ │ ├── modeling │ │ │ ├── __init__.py │ │ │ ├── backbones │ │ │ │ ├── __init__.py │ │ │ │ ├── build.py │ │ │ │ ├── mobilenet.py │ │ │ │ ├── osnet.py │ │ │ │ ├── regnet │ │ │ │ │ ├── __init__.py │ │ │ │ │ ├── config.py │ │ │ │ │ ├── effnet.py │ │ │ │ │ ├── effnet │ │ │ │ │ │ ├── EN-B0_dds_8gpu.yaml │ │ │ │ │ │ ├── EN-B1_dds_8gpu.yaml │ │ │ │ │ │ ├── EN-B2_dds_8gpu.yaml │ │ │ │ │ │ ├── EN-B3_dds_8gpu.yaml │ │ │ │ │ │ ├── EN-B4_dds_8gpu.yaml │ │ │ │ │ │ └── EN-B5_dds_8gpu.yaml │ │ │ │ │ ├── regnet.py │ │ │ │ │ ├── regnetx │ │ │ │ │ │ ├── RegNetX-1.6GF_dds_8gpu.yaml │ │ │ │ │ │ ├── RegNetX-12GF_dds_8gpu.yaml │ │ │ │ │ │ ├── RegNetX-16GF_dds_8gpu.yaml │ │ │ │ │ │ ├── RegNetX-200MF_dds_8gpu.yaml │ │ │ │ │ │ ├── RegNetX-3.2GF_dds_8gpu.yaml │ │ │ │ │ │ ├── RegNetX-32GF_dds_8gpu.yaml │ │ │ │ │ │ ├── RegNetX-4.0GF_dds_8gpu.yaml │ │ │ │ │ │ ├── RegNetX-400MF_dds_8gpu.yaml │ │ │ │ │ │ ├── RegNetX-6.4GF_dds_8gpu.yaml │ │ │ │ │ │ ├── RegNetX-600MF_dds_8gpu.yaml │ │ │ │ │ │ ├── RegNetX-8.0GF_dds_8gpu.yaml │ │ │ │ │ │ └── RegNetX-800MF_dds_8gpu.yaml │ │ │ │ │ └── regnety │ │ │ │ │ │ ├── RegNetY-1.6GF_dds_8gpu.yaml │ │ │ │ │ │ ├── RegNetY-12GF_dds_8gpu.yaml │ │ │ │ │ │ ├── RegNetY-16GF_dds_8gpu.yaml │ │ │ │ │ │ ├── RegNetY-200MF_dds_8gpu.yaml │ │ │ │ │ │ ├── RegNetY-3.2GF_dds_8gpu.yaml │ │ │ │ │ │ ├── RegNetY-32GF_dds_8gpu.yaml │ │ │ │ │ │ ├── RegNetY-4.0GF_dds_8gpu.yaml │ │ │ │ │ │ ├── RegNetY-400MF_dds_8gpu.yaml │ │ │ │ │ │ ├── RegNetY-6.4GF_dds_8gpu.yaml │ │ │ │ │ │ ├── RegNetY-600MF_dds_8gpu.yaml │ │ │ │ │ │ ├── RegNetY-8.0GF_dds_8gpu.yaml │ │ │ │ │ │ └── RegNetY-800MF_dds_8gpu.yaml │ │ │ │ ├── repvgg.py │ │ │ │ ├── resnest.py │ │ │ │ ├── resnet.py │ │ │ │ ├── resnext.py │ │ │ │ ├── shufflenet.py │ │ │ │ └── vision_transformer.py │ │ │ ├── heads │ │ │ │ ├── __init__.py │ │ │ │ ├── build.py │ │ │ │ ├── clas_head.py │ │ │ │ └── embedding_head.py │ │ │ ├── losses │ │ │ │ ├── __init__.py │ │ │ │ ├── circle_loss.py │ │ │ │ ├── cross_entroy_loss.py │ │ │ │ ├── focal_loss.py │ │ │ │ ├── triplet_loss.py │ │ │ │ └── utils.py │ │ │ └── meta_arch │ │ │ │ ├── __init__.py │ │ │ │ ├── baseline.py │ │ │ │ ├── build.py │ │ │ │ ├── distiller.py │ │ │ │ ├── mgn.py │ │ │ │ └── moco.py │ │ ├── solver │ │ │ ├── __init__.py │ │ │ ├── build.py │ │ │ ├── lr_scheduler.py │ │ │ └── optim │ │ │ │ ├── __init__.py │ │ │ │ ├── lamb.py │ │ │ │ ├── radam.py │ │ │ │ └── swa.py │ │ └── utils │ │ │ ├── __init__.py │ │ │ ├── checkpoint.py │ │ │ ├── collect_env.py │ │ │ ├── comm.py │ │ │ ├── compute_dist.py │ │ │ ├── env.py │ │ │ ├── events.py │ │ │ ├── faiss_utils.py │ │ │ ├── file_io.py │ │ │ ├── history_buffer.py │ │ │ ├── logger.py │ │ │ ├── precision_bn.py │ │ │ ├── registry.py │ │ │ ├── summary.py │ │ │ ├── timer.py │ │ │ └── visualizer.py │ ├── images │ │ ├── cap.jpg │ │ ├── cap2.jpg │ │ ├── car1_1.jpg │ │ ├── car1_2.jpg │ │ ├── car1_3.jpg │ │ ├── car2_1.jpg │ │ ├── car2_2.jpg │ │ ├── car2_3.jpg │ │ ├── car3_1.jpg │ │ ├── car3_2.jpg │ │ ├── car3_3.jpg │ │ ├── car3_4.jpg │ │ ├── car3_5.jpg │ │ ├── car3_6.jpg │ │ ├── car4_1.jpg │ │ ├── car4_2.jpg │ │ └── car4_3.jpg │ └── predictor.py ├── images │ └── world.jpg └── pytorch_common_code.py ├── sklearn ├── Supervised_learning │ ├── Cross_Decomposition │ │ ├── ex_compare_cross_decomposition.py │ │ └── ex_pcr_vs_pls.py │ ├── Linear_Models │ │ ├── ex01_ordinary_least_squares.py │ │ ├── ex02_ridge_regression_classification.py │ │ ├── ex03_lasso.py │ │ ├── ex04_multi_task_lasso.py │ │ ├── ex05_elastic_net.py │ │ ├── ex08_lars_lasso.py │ │ ├── ex09_omp.py │ │ ├── ex10_bayesian_regression.py │ │ ├── ex11_logistic_regression.py │ │ ├── ex12_generalized_linear_regression.py │ │ ├── ex16_robustness_regression.py │ │ └── ex17_polynomial_regression.py │ ├── Linear_Quadratic_Discriminant_Analysis │ │ ├── ex01_pca_lda.py │ │ ├── ex04_comparison_of_lda.py │ │ └── ex_linear_quadratic_discriminant_analysis.py │ ├── Naive_Bayes │ │ └── ex_gaussian_naive_bayes.py │ ├── Nearest_Neighbors │ │ ├── ex_multioutput_face_completion.py │ │ ├── ex_nca_dim_reduction.py │ │ └── ex_nearest_neighbors_regression.py │ ├── Stochastic_Gradient_Descent │ │ ├── ex01_sgd_classifier.py │ │ └── ex03_sgd_sparse_data.py │ ├── Support_Vector_Machines │ │ ├── ex01_svc.py │ │ ├── ex02_svr.py │ │ ├── ex06_kernel_svm.py │ │ └── ex_svm.py │ ├── ex_plot_bias_variance.py │ ├── ex_plot_label_propagation_digits.py │ ├── ex_plot_label_propagation_digits_active_learning.py │ ├── ex_plot_mlp_alpha.py │ ├── ex_plot_mnist_filters.py │ ├── ex_plot_multi_layer_perceptron.py │ └── ex_plot_voting_regressor.py ├── dataset │ └── breast_cancer.csv ├── demo_ann.py └── examples │ ├── Cross_Decomposition │ ├── ex_compare_cross_decomposition.py │ └── ex_pcr_vs_pls.py │ ├── Linear_Models │ ├── ex01_ordinary_least_squares.py │ ├── ex02_ridge_regression_classification.py │ ├── ex03_lasso.py │ ├── ex04_multi_task_lasso.py │ ├── ex05_elastic_net.py │ ├── ex08_lars_lasso.py │ ├── ex09_omp.py │ ├── ex10_bayesian_regression.py │ ├── ex11_logistic_regression.py │ ├── ex12_generalized_linear_regression.py │ ├── ex16_robustness_regression.py │ └── ex17_polynomial_regression.py │ ├── Linear_Quadratic_Discriminant_Analysis │ ├── ex01_pca_lda.py │ ├── ex04_comparison_of_lda.py │ └── ex_linear_quadratic_discriminant_analysis.py │ ├── Naive_Bayes │ └── ex_gaussian_naive_bayes.py │ ├── Nearest_Neighbors │ ├── ex_multioutput_face_completion.py │ ├── ex_nca_dim_reduction.py │ └── ex_nearest_neighbors_regression.py │ ├── Stochastic_Gradient_Descent │ ├── ex01_sgd_classifier.py │ └── ex03_sgd_sparse_data.py │ ├── Support_Vector_Machines │ ├── ex01_svc.py │ ├── ex02_svr.py │ ├── ex06_kernel_svm.py │ └── ex_svm.py │ ├── ex_common_pitfalls_recommended_practices.py │ ├── ex_model_dump_load.py │ ├── ex_plot_bias_variance.py │ ├── ex_plot_coin_segmentation.py │ ├── ex_plot_coin_ward_segmentation.py │ ├── ex_plot_color_quantization.py │ ├── ex_plot_cv_predict.py │ ├── ex_plot_digits_agglomeration.py │ ├── ex_plot_digits_classification.py │ ├── ex_plot_digits_kde_sampling.py │ ├── ex_plot_face_recognition.py │ ├── ex_plot_faces_decomposition.py │ ├── ex_plot_gmm_covariances.py │ ├── ex_plot_image_denoising.py │ ├── ex_plot_incremental_pca.py │ ├── ex_plot_kde_1d.py │ ├── ex_plot_kmeans_assumptions.py │ ├── ex_plot_kmeans_digits.py │ ├── ex_plot_label_binarization_encoding.py │ ├── ex_plot_label_propagation_digits.py │ ├── ex_plot_label_propagation_digits_active_learning.py │ ├── ex_plot_learning_curve.py │ ├── ex_plot_mean_shift.py │ ├── ex_plot_mini_batch_kmeans.py │ ├── ex_plot_mlp_alpha.py │ ├── ex_plot_mnist_filters.py │ ├── ex_plot_multi_layer_perceptron.py │ ├── ex_plot_pca_vs_lda.py │ ├── ex_plot_rbm_logistic_classification.py │ ├── ex_plot_segmentation_toy.py │ ├── ex_plot_species_distribution_modeling.py │ ├── ex_plot_species_kde.py │ ├── ex_plot_underfitting_overfitting.py │ ├── ex_plot_validation_curve.py │ └── ex_plot_voting_regressor.py ├── yolov4 ├── config │ ├── coco.cfg │ ├── coco.data │ ├── coco.names │ ├── forklift.cfg │ ├── forklift.data │ ├── forklift.names │ ├── helmet.cfg │ ├── helmet.data │ └── helmet.names ├── demo_video2image.py ├── demo_voc_label.py ├── images │ ├── _dog.jpg │ ├── _image_01.jpg │ ├── _image_02.jpg │ ├── _image_03.jpg │ ├── _image_04.jpg │ ├── _image_05.jpg │ ├── bird.jpg │ ├── cat.jpg │ ├── dog.jpg │ ├── dog_yolov4_darknet_dll.jpg │ ├── image_01.jpg │ ├── image_02.jpg │ ├── image_03.jpg │ ├── image_04.jpg │ ├── image_05.jpg │ ├── person.jpg │ ├── person_yolov4_darknet_dll.jpg │ ├── xiyou.jpg │ └── xiyou_yolov4_darknet_dll.jpg ├── yolov4_darknet_dll │ ├── darknet.py │ ├── darknet_forklift_trace.py │ ├── darknet_images.py │ ├── darknet_video.py │ ├── yolov4_darknet_api.py │ └── yolov4_darknet_dll.py └── yolov4_opencv.py └── yolov5 ├── capure_screen_detector.py ├── data ├── GlobalWheat2020.yaml ├── SKU-110K.yaml ├── VisDrone.yaml ├── argoverse_hd.yaml ├── coco.yaml ├── coco128.yaml ├── hyp.finetune.yaml ├── hyp.finetune_objects365.yaml ├── hyp.scratch.yaml ├── images │ ├── bus.jpg │ ├── game_1.jpg │ ├── game_2.jpg │ ├── image_01.jpg │ ├── image_02.jpg │ ├── image_03.jpg │ ├── image_04.jpg │ ├── image_05.jpg │ ├── rubbish.jpg │ └── zidane.jpg ├── my_yolo.yaml ├── objects365.yaml ├── scripts │ ├── download_weights.sh │ ├── get_argoverse_hd.sh │ ├── get_coco.sh │ ├── get_coco128.sh │ └── get_voc.sh └── voc.yaml ├── deep_sort ├── configs │ └── deep_sort.yaml ├── deep_sort │ ├── README.md │ ├── __init__.py │ ├── deep │ │ ├── __init__.py │ │ ├── checkpoint │ │ │ ├── .gitkeep │ │ │ └── ckpt.t7 │ │ ├── evaluate.py │ │ ├── feature_extractor.py │ │ ├── model.py │ │ ├── original_model.py │ │ ├── test.py │ │ ├── train.jpg │ │ └── train.py │ ├── deep_reid.py │ ├── deep_sort.py │ └── sort │ │ ├── __init__.py │ │ ├── detection.py │ │ ├── iou_matching.py │ │ ├── kalman_filter.py │ │ ├── linear_assignment.py │ │ ├── nn_matching.py │ │ ├── preprocessing.py │ │ ├── track.py │ │ └── tracker.py └── utils │ ├── __init__.py │ ├── asserts.py │ ├── draw.py │ ├── evaluation.py │ ├── io.py │ ├── json_logger.py │ ├── log.py │ ├── parser.py │ └── tools.py ├── head_detector.py ├── models ├── __init__.py ├── common.py ├── experimental.py ├── export.py ├── hub │ ├── anchors.yaml │ ├── yolov3-spp.yaml │ ├── yolov3-tiny.yaml │ ├── yolov3.yaml │ ├── yolov5-fpn.yaml │ ├── yolov5-p2.yaml │ ├── yolov5-p6.yaml │ ├── yolov5-p7.yaml │ ├── yolov5-panet.yaml │ ├── yolov5l6.yaml │ ├── yolov5m6.yaml │ ├── yolov5s-transformer.yaml │ ├── yolov5s6.yaml │ └── yolov5x6.yaml ├── my_yolo.yaml ├── yolo.py ├── yolov5l.yaml ├── yolov5m.yaml ├── yolov5s.yaml └── yolov5x.yaml ├── rubbish_detector.py ├── runs ├── detect │ └── exp │ │ ├── bus.jpg │ │ ├── game_1.jpg │ │ ├── game_2.jpg │ │ ├── image_01.jpg │ │ ├── image_02.jpg │ │ ├── image_03.jpg │ │ ├── image_04.jpg │ │ ├── image_05.jpg │ │ └── zidane.jpg └── train │ └── exp │ ├── F1_curve.png │ ├── PR_curve.png │ ├── P_curve.png │ ├── R_curve.png │ ├── confusion_matrix.png │ ├── events.out.tfevents.1624293729.Taosy.7980.0 │ ├── hyp.yaml │ ├── labels.jpg │ ├── labels_correlogram.jpg │ ├── opt.yaml │ ├── results.png │ ├── results.txt │ ├── test_batch0_labels.jpg │ ├── test_batch0_pred.jpg │ ├── test_batch1_labels.jpg │ ├── test_batch1_pred.jpg │ ├── test_batch2_labels.jpg │ ├── test_batch2_pred.jpg │ ├── train_batch0.jpg │ ├── train_batch1.jpg │ └── train_batch2.jpg ├── test.py ├── track_stopped_car.py ├── tracker_anti_running_car.py ├── traffic_abnormal.py ├── train.py ├── utils ├── __init__.py ├── activations.py ├── autoanchor.py ├── aws │ ├── __init__.py │ ├── mime.sh │ ├── resume.py │ └── userdata.sh ├── datasets.py ├── flask_rest_api │ ├── README.md │ ├── example_request.py │ └── restapi.py ├── general.py ├── google_app_engine │ ├── Dockerfile │ ├── additional_requirements.txt │ └── app.yaml ├── google_utils.py ├── loss.py ├── metrics.py ├── plots.py ├── torch_utils.py └── wandb_logging │ ├── __init__.py │ ├── log_dataset.py │ └── wandb_utils.py ├── yolov5_detector.py └── yolov5_tracker.py /a_demos/data/digits.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/a_demos/data/digits.png -------------------------------------------------------------------------------- /a_demos/data/excel_write.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/a_demos/data/excel_write.xlsx -------------------------------------------------------------------------------- /a_demos/data/file.txt: -------------------------------------------------------------------------------- 1 | Zhihu : https://www.zhihu.com/people/1105936347 2 | Github: https://github.com/AFei19911012 -------------------------------------------------------------------------------- /a_demos/data/test.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/a_demos/data/test.xlsx -------------------------------------------------------------------------------- /a_demos/data/to_excel.xlsx: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/a_demos/data/to_excel.xlsx -------------------------------------------------------------------------------- /a_demos/ftp_demo.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | Created on 2021/5/30 9:56 4 | Filename : ftp_demo.py 5 | Author : Taosy.W 6 | Zhihu : https://www.zhihu.com/people/1105936347 7 | Github : https://github.com/AFei19911012 8 | Description: 9 | """ 10 | # Source: 11 | # ======================================================= 12 | from ftplib import FTP 13 | 14 | 15 | def main(host='192.168.3.250', port=21, user='', passwd='', start_dir=''): 16 | ftp = FTP() 17 | ftp.connect(host=host, port=port) 18 | ftp.login(user=user, passwd=passwd) 19 | ftp.cwd(start_dir) 20 | L = ftp.nlst() 21 | print(L) 22 | 23 | 24 | if __name__ == '__main__': 25 | main() 26 | -------------------------------------------------------------------------------- /a_demos/images/Canny.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/a_demos/images/Canny.jpg -------------------------------------------------------------------------------- /a_demos/images/Warped.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/a_demos/images/Warped.jpg -------------------------------------------------------------------------------- /a_demos/images/background.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/a_demos/images/background.jpg -------------------------------------------------------------------------------- /a_demos/images/ball.gif: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/a_demos/images/ball.gif -------------------------------------------------------------------------------- /a_demos/images/dog.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/a_demos/images/dog.jpg -------------------------------------------------------------------------------- /a_demos/images/dog.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/a_demos/images/dog.png -------------------------------------------------------------------------------- /a_demos/images/dog_cut.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/a_demos/images/dog_cut.png -------------------------------------------------------------------------------- /a_demos/images/dog_cut2.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/a_demos/images/dog_cut2.png -------------------------------------------------------------------------------- /a_demos/images/gray_image.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/a_demos/images/gray_image.jpg -------------------------------------------------------------------------------- /a_demos/images/my_square_function.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/a_demos/images/my_square_function.png -------------------------------------------------------------------------------- /a_demos/images/my_wiggly_animation.gif: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/a_demos/images/my_wiggly_animation.gif -------------------------------------------------------------------------------- /a_demos/images/notecard.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/a_demos/images/notecard.png -------------------------------------------------------------------------------- /a_demos/images/obama.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/a_demos/images/obama.jpg -------------------------------------------------------------------------------- /a_demos/images/resized_image_400.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/a_demos/images/resized_image_400.jpg -------------------------------------------------------------------------------- /a_demos/images/rotation_bound_image_45.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/a_demos/images/rotation_bound_image_45.jpg -------------------------------------------------------------------------------- /a_demos/images/rotation_image_90.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/a_demos/images/rotation_image_90.jpg -------------------------------------------------------------------------------- /a_demos/images/skeleton_Canny_image.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/a_demos/images/skeleton_Canny_image.jpg -------------------------------------------------------------------------------- /a_demos/images/skeleton_image.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/a_demos/images/skeleton_image.jpg -------------------------------------------------------------------------------- /a_demos/images/translation_image.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/a_demos/images/translation_image.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/alex-lacamoire.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/alex-lacamoire.png -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/biden.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/biden.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/five_people.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/five_people.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/lin-manuel-miranda.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/lin-manuel-miranda.png -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/obama.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/obama.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/obama2.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/obama2.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/obama_and_biden.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/obama_and_biden.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/test_image.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/test_image.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/0.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/0.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/1.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/1.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/10.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/10.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/11.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/11.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/12.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/12.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/13.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/13.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/14.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/14.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/15.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/15.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/17.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/17.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/18.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/18.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/19.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/19.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/2.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/2.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/20.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/20.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/21.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/21.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/22.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/22.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/23.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/23.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/24.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/24.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/25.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/25.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/26.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/26.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/27.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/27.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/28.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/28.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/29.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/29.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/3.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/3.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/30.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/30.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/4.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/4.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/5.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/5.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/6.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/6.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/7.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/7.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/8.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/8.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/ChenHe/9.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/ChenHe/9.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/0.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/0.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/1.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/1.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/10.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/10.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/11.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/11.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/12.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/12.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/13.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/13.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/14.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/14.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/15.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/15.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/16.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/16.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/17.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/17.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/18.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/18.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/19.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/19.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/2.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/2.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/20.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/20.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/22.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/22.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/23.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/23.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/24.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/24.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/25.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/25.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/26.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/26.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/27.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/27.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/29.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/29.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/3.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/3.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/30.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/30.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/4.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/4.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/5.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/5.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/6.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/6.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/7.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/7.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/8.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/8.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/Jay/9.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/Jay/9.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/0.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/0.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/1.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/1.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/10.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/10.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/11.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/11.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/12.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/12.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/13.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/13.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/14.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/14.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/15.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/15.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/16.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/16.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/17.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/17.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/19.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/19.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/2.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/2.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/20.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/20.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/21.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/21.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/23.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/23.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/24.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/24.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/25.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/25.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/26.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/26.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/27.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/27.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/28.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/28.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/3.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/3.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/30.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/30.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/4.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/4.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/5.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/5.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/6.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/6.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/7.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/7.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/8.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/8.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/train_dir/KunLin/9.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/train_dir/KunLin/9.jpg -------------------------------------------------------------------------------- /dlib_face_recognition/resources/images/two_people.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/dlib_face_recognition/resources/images/two_people.jpg -------------------------------------------------------------------------------- /ppyolo/configs/cascade_rcnn/_base_/optimizer_1x.yml: -------------------------------------------------------------------------------- 1 | epoch: 12 2 | 3 | LearningRate: 4 | base_lr: 0.01 5 | schedulers: 6 | - !PiecewiseDecay 7 | gamma: 0.1 8 | milestones: [8, 11] 9 | - !LinearWarmup 10 | start_factor: 0.001 11 | steps: 1000 12 | 13 | OptimizerBuilder: 14 | optimizer: 15 | momentum: 0.9 16 | type: Momentum 17 | regularizer: 18 | factor: 0.0001 19 | type: L2 20 | -------------------------------------------------------------------------------- /ppyolo/configs/cascade_rcnn/cascade_mask_rcnn_r50_fpn_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_instance.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_1x.yml', 5 | '_base_/cascade_mask_rcnn_r50_fpn.yml', 6 | '_base_/cascade_mask_fpn_reader.yml', 7 | ] 8 | weights: output/cascade_mask_rcnn_r50_fpn_1x_coco/model_final 9 | -------------------------------------------------------------------------------- /ppyolo/configs/cascade_rcnn/cascade_mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_instance.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_1x.yml', 5 | '_base_/cascade_mask_rcnn_r50_fpn.yml', 6 | '_base_/cascade_mask_fpn_reader.yml', 7 | ] 8 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_ssld_v2_pretrained.pdparams 9 | weights: output/cascade_mask_rcnn_r50_vd_fpn_ssld_1x_coco/model_final 10 | 11 | ResNet: 12 | depth: 50 13 | variant: d 14 | norm_type: bn 15 | freeze_at: 0 16 | return_idx: [0,1,2,3] 17 | num_stages: 4 18 | lr_mult_list: [0.05, 0.05, 0.1, 0.15] 19 | -------------------------------------------------------------------------------- /ppyolo/configs/cascade_rcnn/cascade_rcnn_r50_fpn_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_1x.yml', 5 | '_base_/cascade_rcnn_r50_fpn.yml', 6 | '_base_/cascade_fpn_reader.yml', 7 | ] 8 | weights: output/cascade_rcnn_r50_fpn_1x_coco/model_final 9 | -------------------------------------------------------------------------------- /ppyolo/configs/cascade_rcnn/cascade_rcnn_r50_vd_fpn_ssld_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_1x.yml', 5 | '_base_/cascade_rcnn_r50_fpn.yml', 6 | '_base_/cascade_fpn_reader.yml', 7 | ] 8 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_ssld_v2_pretrained.pdparams 9 | weights: output/cascade_rcnn_r50_vd_fpn_ssld_1x_coco/model_final 10 | 11 | ResNet: 12 | depth: 50 13 | variant: d 14 | norm_type: bn 15 | freeze_at: 0 16 | return_idx: [0,1,2,3] 17 | num_stages: 4 18 | lr_mult_list: [0.05, 0.05, 0.1, 0.15] 19 | -------------------------------------------------------------------------------- /ppyolo/configs/datasets/coco_detection.yml: -------------------------------------------------------------------------------- 1 | metric: COCO 2 | num_classes: 80 3 | 4 | TrainDataset: 5 | !COCODataSet 6 | image_dir: train2017 7 | anno_path: annotations/instances_train2017.json 8 | dataset_dir: dataset/coco 9 | data_fields: ['image', 'gt_bbox', 'gt_class', 'is_crowd'] 10 | 11 | EvalDataset: 12 | !COCODataSet 13 | image_dir: val2017 14 | anno_path: annotations/instances_val2017.json 15 | dataset_dir: dataset/coco 16 | 17 | TestDataset: 18 | !ImageFolder 19 | anno_path: annotations/instances_val2017.json 20 | -------------------------------------------------------------------------------- /ppyolo/configs/datasets/coco_instance.yml: -------------------------------------------------------------------------------- 1 | metric: COCO 2 | num_classes: 80 3 | 4 | TrainDataset: 5 | !COCODataSet 6 | image_dir: train2017 7 | anno_path: annotations/instances_train2017.json 8 | dataset_dir: dataset/coco 9 | data_fields: ['image', 'gt_bbox', 'gt_class', 'gt_poly', 'is_crowd'] 10 | 11 | EvalDataset: 12 | !COCODataSet 13 | image_dir: val2017 14 | anno_path: annotations/instances_val2017.json 15 | dataset_dir: dataset/coco 16 | 17 | TestDataset: 18 | !ImageFolder 19 | anno_path: annotations/instances_val2017.json 20 | -------------------------------------------------------------------------------- /ppyolo/configs/datasets/dota.yml: -------------------------------------------------------------------------------- 1 | metric: COCO 2 | num_classes: 15 3 | 4 | TrainDataset: 5 | !COCODataSet 6 | image_dir: trainval_split/images 7 | anno_path: trainval_split/s2anet_trainval_paddle_coco.json 8 | dataset_dir: dataset/DOTA_1024_s2anet 9 | data_fields: ['image', 'gt_bbox', 'gt_class', 'is_crowd', 'gt_rbox'] 10 | 11 | EvalDataset: 12 | !COCODataSet 13 | image_dir: trainval_split/images 14 | anno_path: trainval_split/s2anet_trainval_paddle_coco.json 15 | dataset_dir: dataset/DOTA_1024_s2anet/ 16 | 17 | TestDataset: 18 | !ImageFolder 19 | anno_path: trainval_split/s2anet_trainval_paddle_coco.json 20 | dataset_dir: dataset/DOTA_1024_s2anet/ 21 | -------------------------------------------------------------------------------- /ppyolo/configs/datasets/roadsign_voc.yml: -------------------------------------------------------------------------------- 1 | metric: VOC 2 | map_type: integral 3 | num_classes: 4 4 | 5 | TrainDataset: 6 | !VOCDataSet 7 | dataset_dir: D:\MyPrograms\DataSet\roadsign_voc 8 | anno_path: train.txt 9 | label_list: label_list.txt 10 | data_fields: ['image', 'gt_bbox', 'gt_class', 'difficult'] 11 | 12 | EvalDataset: 13 | !VOCDataSet 14 | dataset_dir: D:\MyPrograms\DataSet\roadsign_voc 15 | anno_path: valid.txt 16 | label_list: label_list.txt 17 | data_fields: ['image', 'gt_bbox', 'gt_class', 'difficult'] 18 | 19 | TestDataset: 20 | !ImageFolder 21 | anno_path: D:\MyPrograms\DataSet\roadsign_voc/label_list.txt 22 | -------------------------------------------------------------------------------- /ppyolo/configs/datasets/voc.yml: -------------------------------------------------------------------------------- 1 | metric: VOC 2 | map_type: 11point 3 | num_classes: 20 4 | 5 | TrainDataset: 6 | !VOCDataSet 7 | dataset_dir: dataset/voc 8 | anno_path: trainval.txt 9 | label_list: label_list.txt 10 | data_fields: ['image', 'gt_bbox', 'gt_class', 'difficult'] 11 | 12 | EvalDataset: 13 | !VOCDataSet 14 | dataset_dir: dataset/voc 15 | anno_path: test.txt 16 | label_list: label_list.txt 17 | data_fields: ['image', 'gt_bbox', 'gt_class', 'difficult'] 18 | 19 | TestDataset: 20 | !ImageFolder 21 | anno_path: dataset/voc/label_list.txt 22 | -------------------------------------------------------------------------------- /ppyolo/configs/datasets/wider_face.yml: -------------------------------------------------------------------------------- 1 | metric: WiderFace 2 | num_classes: 1 3 | 4 | TrainDataset: 5 | !WIDERFaceDataSet 6 | dataset_dir: dataset/wider_face 7 | anno_path: wider_face_split/wider_face_train_bbx_gt.txt 8 | image_dir: WIDER_train/images 9 | data_fields: ['image', 'gt_bbox', 'gt_class'] 10 | 11 | EvalDataset: 12 | !WIDERFaceDataSet 13 | dataset_dir: dataset/wider_face 14 | anno_path: wider_face_split/wider_face_val_bbx_gt.txt 15 | image_dir: WIDER_val/images 16 | data_fields: ['image'] 17 | 18 | TestDataset: 19 | !ImageFolder 20 | use_default_label: true 21 | -------------------------------------------------------------------------------- /ppyolo/configs/dcn/cascade_rcnn_dcn_r50_fpn_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | '../cascade_rcnn/_base_/optimizer_1x.yml', 5 | '../cascade_rcnn/_base_/cascade_rcnn_r50_fpn.yml', 6 | '../cascade_rcnn/_base_/cascade_fpn_reader.yml', 7 | ] 8 | weights: output/cascade_rcnn_dcn_r50_fpn_1x_coco/model_final 9 | 10 | ResNet: 11 | depth: 50 12 | norm_type: bn 13 | freeze_at: 0 14 | return_idx: [0,1,2,3] 15 | num_stages: 4 16 | dcn_v2_stages: [1,2,3] 17 | -------------------------------------------------------------------------------- /ppyolo/configs/dcn/cascade_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'cascade_rcnn_dcn_r50_fpn_1x_coco.yml', 3 | ] 4 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNeXt101_vd_64x4d_pretrained.pdparams 5 | weights: output/cascade_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco/model_final 6 | 7 | ResNet: 8 | depth: 101 9 | groups: 64 10 | base_width: 4 11 | variant: d 12 | norm_type: bn 13 | freeze_at: 0 14 | return_idx: [0,1,2,3] 15 | num_stages: 4 16 | dcn_v2_stages: [1,2,3] 17 | -------------------------------------------------------------------------------- /ppyolo/configs/dcn/faster_rcnn_dcn_r101_vd_fpn_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'faster_rcnn_dcn_r50_fpn_1x_coco.yml', 3 | ] 4 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet101_vd_pretrained.pdparams 5 | weights: output/faster_rcnn_dcn_r101_vd_fpn_1x_coco/model_final 6 | 7 | ResNet: 8 | # index 0 stands for res2 9 | depth: 101 10 | variant: d 11 | norm_type: bn 12 | freeze_at: 0 13 | return_idx: [0,1,2,3] 14 | num_stages: 4 15 | dcn_v2_stages: [1,2,3] 16 | -------------------------------------------------------------------------------- /ppyolo/configs/dcn/faster_rcnn_dcn_r50_fpn_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | '../faster_rcnn/_base_/optimizer_1x.yml', 5 | '../faster_rcnn/_base_/faster_rcnn_r50_fpn.yml', 6 | '../faster_rcnn/_base_/faster_fpn_reader.yml', 7 | ] 8 | weights: output/faster_rcnn_dcn_r50_fpn_1x_coco/model_final 9 | 10 | ResNet: 11 | depth: 50 12 | norm_type: bn 13 | freeze_at: 0 14 | return_idx: [0,1,2,3] 15 | num_stages: 4 16 | dcn_v2_stages: [1,2,3] 17 | -------------------------------------------------------------------------------- /ppyolo/configs/dcn/faster_rcnn_dcn_r50_vd_fpn_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'faster_rcnn_dcn_r50_fpn_1x_coco.yml', 3 | ] 4 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_pretrained.pdparams 5 | weights: output/faster_rcnn_dcn_r50_vd_fpn_2x_coco/model_final 6 | 7 | ResNet: 8 | # index 0 stands for res2 9 | depth: 50 10 | variant: d 11 | norm_type: bn 12 | freeze_at: 0 13 | return_idx: [0,1,2,3] 14 | num_stages: 4 15 | dcn_v2_stages: [1,2,3] 16 | -------------------------------------------------------------------------------- /ppyolo/configs/dcn/faster_rcnn_dcn_r50_vd_fpn_2x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'faster_rcnn_dcn_r50_fpn_1x_coco.yml', 3 | ] 4 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_pretrained.pdparams 5 | weights: output/faster_rcnn_dcn_r50_vd_fpn_2x_coco/model_final 6 | 7 | ResNet: 8 | # index 0 stands for res2 9 | depth: 50 10 | variant: d 11 | norm_type: bn 12 | freeze_at: 0 13 | return_idx: [0,1,2,3] 14 | num_stages: 4 15 | dcn_v2_stages: [1,2,3] 16 | 17 | epoch: 24 18 | LearningRate: 19 | base_lr: 0.01 20 | schedulers: 21 | - !PiecewiseDecay 22 | gamma: 0.1 23 | milestones: [16, 22] 24 | - !LinearWarmup 25 | start_factor: 0.1 26 | steps: 1000 27 | -------------------------------------------------------------------------------- /ppyolo/configs/dcn/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'faster_rcnn_dcn_r50_fpn_1x_coco.yml', 3 | ] 4 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNeXt101_vd_64x4d_pretrained.pdparams 5 | weights: output/faster_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco/model_final 6 | 7 | ResNet: 8 | # for ResNeXt: groups, base_width, base_channels 9 | depth: 101 10 | groups: 64 11 | base_width: 4 12 | variant: d 13 | norm_type: bn 14 | freeze_at: 0 15 | return_idx: [0,1,2,3] 16 | num_stages: 4 17 | dcn_v2_stages: [1,2,3] 18 | -------------------------------------------------------------------------------- /ppyolo/configs/dcn/mask_rcnn_dcn_r101_vd_fpn_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'mask_rcnn_dcn_r50_fpn_1x_coco.yml', 3 | ] 4 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet101_vd_pretrained.pdparams 5 | weights: output/mask_rcnn_dcn_r101_vd_fpn_1x_coco/model_final 6 | 7 | ResNet: 8 | # index 0 stands for res2 9 | depth: 101 10 | variant: d 11 | norm_type: bn 12 | freeze_at: 0 13 | return_idx: [0,1,2,3] 14 | num_stages: 4 15 | dcn_v2_stages: [1,2,3] 16 | -------------------------------------------------------------------------------- /ppyolo/configs/dcn/mask_rcnn_dcn_r50_fpn_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_instance.yml', 3 | '../runtime.yml', 4 | '../mask_rcnn/_base_/optimizer_1x.yml', 5 | '../mask_rcnn/_base_/mask_rcnn_r50_fpn.yml', 6 | '../mask_rcnn/_base_/mask_fpn_reader.yml', 7 | ] 8 | weights: output/mask_rcnn_dcn_r50_fpn_1x_coco/model_final 9 | 10 | ResNet: 11 | depth: 50 12 | norm_type: bn 13 | freeze_at: 0 14 | return_idx: [0,1,2,3] 15 | num_stages: 4 16 | dcn_v2_stages: [1,2,3] 17 | -------------------------------------------------------------------------------- /ppyolo/configs/dcn/mask_rcnn_dcn_r50_vd_fpn_2x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'mask_rcnn_dcn_r50_fpn_1x_coco.yml', 3 | ] 4 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_pretrained.pdparams 5 | weights: output/mask_rcnn_dcn_r50_vd_fpn_2x_coco/model_final 6 | 7 | ResNet: 8 | # index 0 stands for res2 9 | depth: 50 10 | variant: d 11 | norm_type: bn 12 | freeze_at: 0 13 | return_idx: [0,1,2,3] 14 | num_stages: 4 15 | dcn_v2_stages: [1,2,3] 16 | 17 | epoch: 24 18 | LearningRate: 19 | base_lr: 0.01 20 | schedulers: 21 | - !PiecewiseDecay 22 | gamma: 0.1 23 | milestones: [16, 22] 24 | - !LinearWarmup 25 | start_factor: 0.1 26 | steps: 1000 27 | -------------------------------------------------------------------------------- /ppyolo/configs/dcn/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'mask_rcnn_dcn_r50_fpn_1x_coco.yml', 3 | ] 4 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNeXt101_vd_64x4d_pretrained.pdparams 5 | weights: output/mask_rcnn_dcn_x101_vd_64x4d_fpn_1x_coco/model_final 6 | 7 | ResNet: 8 | # for ResNeXt: groups, base_width, base_channels 9 | depth: 101 10 | variant: d 11 | groups: 64 12 | base_width: 4 13 | norm_type: bn 14 | freeze_at: 0 15 | return_idx: [0,1,2,3] 16 | num_stages: 4 17 | dcn_v2_stages: [1,2,3] 18 | -------------------------------------------------------------------------------- /ppyolo/configs/dota/_base_/s2anet_optimizer_1x.yml: -------------------------------------------------------------------------------- 1 | epoch: 12 2 | 3 | LearningRate: 4 | base_lr: 0.01 5 | schedulers: 6 | - !PiecewiseDecay 7 | gamma: 0.1 8 | milestones: [7, 10] 9 | - !LinearWarmup 10 | start_factor: 0.3333333333333333 11 | steps: 500 12 | 13 | OptimizerBuilder: 14 | optimizer: 15 | momentum: 0.9 16 | type: Momentum 17 | regularizer: 18 | factor: 0.0001 19 | type: L2 20 | clip_grad_by_norm: 35 21 | -------------------------------------------------------------------------------- /ppyolo/configs/dota/s2anet_1x_dota.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/dota.yml', 3 | '../runtime.yml', 4 | '_base_/s2anet_optimizer_1x.yml', 5 | '_base_/s2anet.yml', 6 | '_base_/s2anet_reader.yml', 7 | ] 8 | weights: output/s2anet_1x_dota/model_final 9 | -------------------------------------------------------------------------------- /ppyolo/configs/dota/s2anet_conv_1x_dota.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/dota.yml', 3 | '../runtime.yml', 4 | '_base_/s2anet_optimizer_1x.yml', 5 | '_base_/s2anet.yml', 6 | '_base_/s2anet_reader.yml', 7 | ] 8 | weights: output/s2anet_1x_dota/model_final 9 | 10 | S2ANetHead: 11 | anchor_strides: [8, 16, 32, 64, 128] 12 | anchor_scales: [4] 13 | anchor_ratios: [1.0] 14 | anchor_assign: RBoxAssigner 15 | stacked_convs: 2 16 | feat_in: 256 17 | feat_out: 256 18 | num_classes: 15 19 | align_conv_type: 'Conv' # AlignConv Conv 20 | align_conv_size: 3 21 | use_sigmoid_cls: True 22 | -------------------------------------------------------------------------------- /ppyolo/configs/face_detection/_base_/optimizer_1000e.yml: -------------------------------------------------------------------------------- 1 | epoch: 1000 2 | 3 | LearningRate: 4 | base_lr: 0.001 5 | schedulers: 6 | - !PiecewiseDecay 7 | gamma: 0.1 8 | milestones: 9 | - 333 10 | - 800 11 | - !LinearWarmup 12 | start_factor: 0.3333333333333333 13 | steps: 500 14 | 15 | OptimizerBuilder: 16 | optimizer: 17 | momentum: 0.0 18 | type: RMSProp 19 | regularizer: 20 | factor: 0.0005 21 | type: L2 22 | -------------------------------------------------------------------------------- /ppyolo/configs/face_detection/blazeface_1000e.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/wider_face.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_1000e.yml', 5 | '_base_/blazeface.yml', 6 | '_base_/face_reader.yml', 7 | ] 8 | weights: output/blazeface_1000e/model_final 9 | multi_scale_eval: True 10 | -------------------------------------------------------------------------------- /ppyolo/configs/face_detection/blazeface_fpn_ssh_1000e.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/wider_face.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_1000e.yml', 5 | '_base_/blazeface_fpn.yml', 6 | '_base_/face_reader.yml', 7 | ] 8 | weights: output/blazeface_fpn_ssh_1000e/model_final 9 | multi_scale_eval: True 10 | -------------------------------------------------------------------------------- /ppyolo/configs/faster_rcnn/_base_/optimizer_1x.yml: -------------------------------------------------------------------------------- 1 | epoch: 12 2 | 3 | LearningRate: 4 | base_lr: 0.01 5 | schedulers: 6 | - !PiecewiseDecay 7 | gamma: 0.1 8 | milestones: [8, 11] 9 | - !LinearWarmup 10 | start_factor: 0.1 11 | steps: 1000 12 | 13 | OptimizerBuilder: 14 | optimizer: 15 | momentum: 0.9 16 | type: Momentum 17 | regularizer: 18 | factor: 0.0001 19 | type: L2 20 | -------------------------------------------------------------------------------- /ppyolo/configs/faster_rcnn/faster_rcnn_r101_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'faster_rcnn_r50_1x_coco.yml', 3 | ] 4 | 5 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet101_pretrained.pdparams 6 | weights: output/faster_rcnn_r101_1x_coco/model_final 7 | 8 | ResNet: 9 | # index 0 stands for res2 10 | depth: 101 11 | norm_type: bn 12 | freeze_at: 0 13 | return_idx: [2] 14 | num_stages: 3 15 | -------------------------------------------------------------------------------- /ppyolo/configs/faster_rcnn/faster_rcnn_r101_fpn_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'faster_rcnn_r50_fpn_1x_coco.yml', 3 | ] 4 | 5 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet101_pretrained.pdparams 6 | weights: output/faster_rcnn_r101_fpn_1x_coco/model_final 7 | 8 | ResNet: 9 | # index 0 stands for res2 10 | depth: 101 11 | norm_type: bn 12 | freeze_at: 0 13 | return_idx: [0,1,2,3] 14 | num_stages: 4 15 | -------------------------------------------------------------------------------- /ppyolo/configs/faster_rcnn/faster_rcnn_r101_fpn_2x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'faster_rcnn_r50_fpn_1x_coco.yml', 3 | ] 4 | 5 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet101_pretrained.pdparams 6 | weights: output/faster_rcnn_r101_fpn_2x_coco/model_final 7 | 8 | ResNet: 9 | # index 0 stands for res2 10 | depth: 101 11 | norm_type: bn 12 | freeze_at: 0 13 | return_idx: [0,1,2,3] 14 | num_stages: 4 15 | 16 | epoch: 24 17 | LearningRate: 18 | base_lr: 0.01 19 | schedulers: 20 | - !PiecewiseDecay 21 | gamma: 0.1 22 | milestones: [16, 22] 23 | - !LinearWarmup 24 | start_factor: 0.1 25 | steps: 1000 26 | -------------------------------------------------------------------------------- /ppyolo/configs/faster_rcnn/faster_rcnn_r101_vd_fpn_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'faster_rcnn_r50_fpn_1x_coco.yml', 3 | ] 4 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet101_vd_pretrained.pdparams 5 | weights: output/faster_rcnn_r101_vd_fpn_1x_coco/model_final 6 | 7 | ResNet: 8 | # index 0 stands for res2 9 | depth: 101 10 | variant: d 11 | norm_type: bn 12 | freeze_at: 0 13 | return_idx: [0,1,2,3] 14 | num_stages: 4 15 | -------------------------------------------------------------------------------- /ppyolo/configs/faster_rcnn/faster_rcnn_r101_vd_fpn_2x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'faster_rcnn_r50_fpn_1x_coco.yml', 3 | ] 4 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet101_vd_pretrained.pdparams 5 | weights: output/faster_rcnn_r101_vd_fpn_2x_coco/model_final 6 | 7 | ResNet: 8 | # index 0 stands for res2 9 | depth: 101 10 | variant: d 11 | norm_type: bn 12 | freeze_at: 0 13 | return_idx: [0,1,2,3] 14 | num_stages: 4 15 | 16 | epoch: 24 17 | LearningRate: 18 | base_lr: 0.01 19 | schedulers: 20 | - !PiecewiseDecay 21 | gamma: 0.1 22 | milestones: [16, 22] 23 | - !LinearWarmup 24 | start_factor: 0.1 25 | steps: 1000 26 | -------------------------------------------------------------------------------- /ppyolo/configs/faster_rcnn/faster_rcnn_r34_fpn_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'faster_rcnn_r50_fpn_1x_coco.yml', 3 | ] 4 | 5 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet34_pretrained.pdparams 6 | weights: output/faster_rcnn_r34_fpn_1x_coco/model_final 7 | 8 | ResNet: 9 | # index 0 stands for res2 10 | depth: 34 11 | norm_type: bn 12 | freeze_at: 0 13 | return_idx: [0,1,2,3] 14 | num_stages: 4 15 | -------------------------------------------------------------------------------- /ppyolo/configs/faster_rcnn/faster_rcnn_r34_vd_fpn_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'faster_rcnn_r50_fpn_1x_coco.yml', 3 | ] 4 | 5 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet34_vd_pretrained.pdparams 6 | weights: output/faster_rcnn_r34_vd_fpn_1x_coco/model_final 7 | 8 | ResNet: 9 | # index 0 stands for res2 10 | depth: 34 11 | variant: d 12 | norm_type: bn 13 | freeze_at: 0 14 | return_idx: [0,1,2,3] 15 | num_stages: 4 16 | -------------------------------------------------------------------------------- /ppyolo/configs/faster_rcnn/faster_rcnn_r50_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_1x.yml', 5 | '_base_/faster_rcnn_r50.yml', 6 | '_base_/faster_reader.yml', 7 | ] 8 | weights: output/faster_rcnn_r50_1x_coco/model_final 9 | -------------------------------------------------------------------------------- /ppyolo/configs/faster_rcnn/faster_rcnn_r50_fpn_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_1x.yml', 5 | '_base_/faster_rcnn_r50_fpn.yml', 6 | '_base_/faster_fpn_reader.yml', 7 | ] 8 | weights: output/faster_rcnn_r50_fpn_1x_coco/model_final 9 | -------------------------------------------------------------------------------- /ppyolo/configs/faster_rcnn/faster_rcnn_r50_fpn_2x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'faster_rcnn_r50_fpn_1x_coco.yml', 3 | ] 4 | weights: output/faster_rcnn_r50_fpn_2x_coco/model_final 5 | 6 | epoch: 24 7 | LearningRate: 8 | base_lr: 0.01 9 | schedulers: 10 | - !PiecewiseDecay 11 | gamma: 0.1 12 | milestones: [16, 22] 13 | - !LinearWarmup 14 | start_factor: 0.1 15 | steps: 1000 16 | -------------------------------------------------------------------------------- /ppyolo/configs/faster_rcnn/faster_rcnn_r50_vd_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'faster_rcnn_r50_1x_coco.yml', 3 | ] 4 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_pretrained.pdparams 5 | weights: output/faster_rcnn_r50_vd_1x_coco/model_final 6 | 7 | ResNet: 8 | # index 0 stands for res2 9 | depth: 50 10 | variant: d 11 | norm_type: bn 12 | freeze_at: 0 13 | return_idx: [2] 14 | num_stages: 3 15 | -------------------------------------------------------------------------------- /ppyolo/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'faster_rcnn_r50_fpn_1x_coco.yml', 3 | ] 4 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_pretrained.pdparams 5 | weights: output/faster_rcnn_r50_vd_fpn_1x_coco/model_final 6 | 7 | ResNet: 8 | # index 0 stands for res2 9 | depth: 50 10 | variant: d 11 | norm_type: bn 12 | freeze_at: 0 13 | return_idx: [0,1,2,3] 14 | num_stages: 4 15 | -------------------------------------------------------------------------------- /ppyolo/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_2x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'faster_rcnn_r50_fpn_1x_coco.yml', 3 | ] 4 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_pretrained.pdparams 5 | weights: output/faster_rcnn_r50_vd_fpn_2x_coco/model_final 6 | 7 | ResNet: 8 | # index 0 stands for res2 9 | depth: 50 10 | variant: d 11 | norm_type: bn 12 | freeze_at: 0 13 | return_idx: [0,1,2,3] 14 | num_stages: 4 15 | 16 | epoch: 24 17 | LearningRate: 18 | base_lr: 0.01 19 | schedulers: 20 | - !PiecewiseDecay 21 | gamma: 0.1 22 | milestones: [16, 22] 23 | - !LinearWarmup 24 | start_factor: 0.1 25 | steps: 1000 26 | -------------------------------------------------------------------------------- /ppyolo/configs/faster_rcnn/faster_rcnn_r50_vd_fpn_ssld_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_1x.yml', 5 | '_base_/faster_rcnn_r50_fpn.yml', 6 | '_base_/faster_fpn_reader.yml', 7 | ] 8 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_ssld_v2_pretrained.pdparams 9 | weights: output/faster_rcnn_r50_vd_fpn_ssld_1x_coco/model_final 10 | 11 | ResNet: 12 | depth: 50 13 | variant: d 14 | norm_type: bn 15 | freeze_at: 0 16 | return_idx: [0,1,2,3] 17 | num_stages: 4 18 | lr_mult_list: [0.05, 0.05, 0.1, 0.15] 19 | 20 | epoch: 12 21 | LearningRate: 22 | base_lr: 0.01 23 | schedulers: 24 | - !PiecewiseDecay 25 | gamma: 0.1 26 | milestones: [8, 11] 27 | - !LinearWarmup 28 | start_factor: 0.1 29 | steps: 1000 30 | -------------------------------------------------------------------------------- /ppyolo/configs/faster_rcnn/faster_rcnn_x101_vd_64x4d_fpn_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'faster_rcnn_r50_fpn_1x_coco.yml', 3 | ] 4 | 5 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNeXt101_vd_64x4d_pretrained.pdparams 6 | weights: output/faster_rcnn_x101_vd_64x4d_fpn_1x_coco/model_final 7 | 8 | ResNet: 9 | # for ResNeXt: groups, base_width, base_channels 10 | depth: 101 11 | groups: 64 12 | base_width: 4 13 | variant: d 14 | norm_type: bn 15 | freeze_at: 0 16 | return_idx: [0,1,2,3] 17 | num_stages: 4 18 | -------------------------------------------------------------------------------- /ppyolo/configs/faster_rcnn/faster_rcnn_x101_vd_64x4d_fpn_2x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'faster_rcnn_r50_fpn_1x_coco.yml', 3 | ] 4 | 5 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNeXt101_vd_64x4d_pretrained.pdparams 6 | weights: output/faster_rcnn_x101_vd_64x4d_fpn_2x_coco/model_final 7 | 8 | ResNet: 9 | # for ResNeXt: groups, base_width, base_channels 10 | depth: 101 11 | groups: 64 12 | base_width: 4 13 | variant: d 14 | norm_type: bn 15 | freeze_at: 0 16 | return_idx: [0,1,2,3] 17 | num_stages: 4 18 | 19 | epoch: 24 20 | LearningRate: 21 | base_lr: 0.01 22 | schedulers: 23 | - !PiecewiseDecay 24 | gamma: 0.1 25 | milestones: [16, 22] 26 | - !LinearWarmup 27 | start_factor: 0.1 28 | steps: 1000 29 | -------------------------------------------------------------------------------- /ppyolo/configs/fcos/_base_/optimizer_1x.yml: -------------------------------------------------------------------------------- 1 | epoch: 12 2 | 3 | LearningRate: 4 | base_lr: 0.01 5 | schedulers: 6 | - !PiecewiseDecay 7 | gamma: 0.1 8 | milestones: [8, 11] 9 | - !LinearWarmup 10 | start_factor: 0.3333333333333333 11 | steps: 500 12 | 13 | OptimizerBuilder: 14 | optimizer: 15 | momentum: 0.9 16 | type: Momentum 17 | regularizer: 18 | factor: 0.0001 19 | type: L2 20 | -------------------------------------------------------------------------------- /ppyolo/configs/fcos/fcos_dcn_r50_fpn_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | '_base_/fcos_r50_fpn.yml', 5 | '_base_/optimizer_1x.yml', 6 | '_base_/fcos_reader.yml', 7 | ] 8 | 9 | weights: output/fcos_dcn_r50_fpn_1x_coco/model_final 10 | 11 | ResNet: 12 | depth: 50 13 | norm_type: bn 14 | freeze_at: 0 15 | return_idx: [1,2,3] 16 | num_stages: 4 17 | dcn_v2_stages: [1,2,3] 18 | 19 | FCOSHead: 20 | fcos_feat: 21 | name: FCOSFeat 22 | feat_in: 256 23 | feat_out: 256 24 | num_convs: 4 25 | norm_type: "gn" 26 | use_dcn: true 27 | num_classes: 80 28 | fpn_stride: [8, 16, 32, 64, 128] 29 | prior_prob: 0.01 30 | fcos_loss: FCOSLoss 31 | norm_reg_targets: true 32 | centerness_on_reg: true 33 | -------------------------------------------------------------------------------- /ppyolo/configs/fcos/fcos_r50_fpn_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | '_base_/fcos_r50_fpn.yml', 5 | '_base_/optimizer_1x.yml', 6 | '_base_/fcos_reader.yml', 7 | ] 8 | 9 | weights: output/fcos_r50_fpn_1x_coco/model_final 10 | -------------------------------------------------------------------------------- /ppyolo/configs/hrnet/faster_rcnn_hrnetv2p_w18_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | './_base_/faster_rcnn_hrnetv2p_w18.yml', 4 | '../faster_rcnn/_base_/optimizer_1x.yml', 5 | '../faster_rcnn/_base_/faster_fpn_reader.yml', 6 | '../runtime.yml', 7 | ] 8 | 9 | weights: output/faster_rcnn_hrnetv2p_w18_1x_coco/model_final 10 | epoch: 12 11 | 12 | LearningRate: 13 | base_lr: 0.02 14 | schedulers: 15 | - !PiecewiseDecay 16 | gamma: 0.1 17 | milestones: [8, 11] 18 | - !LinearWarmup 19 | start_factor: 0.1 20 | steps: 1000 21 | 22 | TrainReader: 23 | batch_size: 2 24 | -------------------------------------------------------------------------------- /ppyolo/configs/hrnet/faster_rcnn_hrnetv2p_w18_2x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | './_base_/faster_rcnn_hrnetv2p_w18.yml', 4 | '../faster_rcnn/_base_/optimizer_1x.yml', 5 | '../faster_rcnn/_base_/faster_fpn_reader.yml', 6 | '../runtime.yml', 7 | ] 8 | 9 | weights: output/faster_rcnn_hrnetv2p_w18_2x_coco/model_final 10 | epoch: 24 11 | 12 | LearningRate: 13 | base_lr: 0.02 14 | schedulers: 15 | - !PiecewiseDecay 16 | gamma: 0.1 17 | milestones: [16, 22] 18 | - !LinearWarmup 19 | start_factor: 0.1 20 | steps: 1000 21 | 22 | TrainReader: 23 | batch_size: 2 24 | -------------------------------------------------------------------------------- /ppyolo/configs/keypoint/football_keypoint.gif: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/ppyolo/configs/keypoint/football_keypoint.gif -------------------------------------------------------------------------------- /ppyolo/configs/mask_rcnn/_base_/optimizer_1x.yml: -------------------------------------------------------------------------------- 1 | epoch: 12 2 | 3 | LearningRate: 4 | base_lr: 0.01 5 | schedulers: 6 | - !PiecewiseDecay 7 | gamma: 0.1 8 | milestones: [8, 11] 9 | - !LinearWarmup 10 | start_factor: 0.001 11 | steps: 1000 12 | 13 | OptimizerBuilder: 14 | optimizer: 15 | momentum: 0.9 16 | type: Momentum 17 | regularizer: 18 | factor: 0.0001 19 | type: L2 20 | -------------------------------------------------------------------------------- /ppyolo/configs/mask_rcnn/mask_rcnn_r101_fpn_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'mask_rcnn_r50_fpn_1x_coco.yml', 3 | ] 4 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet101_pretrained.pdparams 5 | weights: output/mask_rcnn_r101_fpn_1x_coco/model_final 6 | 7 | ResNet: 8 | # index 0 stands for res2 9 | depth: 101 10 | norm_type: bn 11 | freeze_at: 0 12 | return_idx: [0,1,2,3] 13 | num_stages: 4 14 | -------------------------------------------------------------------------------- /ppyolo/configs/mask_rcnn/mask_rcnn_r101_vd_fpn_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'mask_rcnn_r50_fpn_1x_coco.yml', 3 | ] 4 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet101_vd_pretrained.pdparams 5 | weights: output/mask_rcnn_r101_vd_fpn_1x_coco/model_final 6 | 7 | ResNet: 8 | # index 0 stands for res2 9 | depth: 101 10 | variant: d 11 | norm_type: bn 12 | freeze_at: 0 13 | return_idx: [0,1,2,3] 14 | num_stages: 4 15 | -------------------------------------------------------------------------------- /ppyolo/configs/mask_rcnn/mask_rcnn_r50_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_instance.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_1x.yml', 5 | '_base_/mask_rcnn_r50.yml', 6 | '_base_/mask_reader.yml', 7 | ] 8 | weights: output/mask_rcnn_r50_1x_coco/model_final 9 | -------------------------------------------------------------------------------- /ppyolo/configs/mask_rcnn/mask_rcnn_r50_2x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'mask_rcnn_r50_1x_coco.yml', 3 | ] 4 | weights: output/mask_rcnn_r50_2x_coco/model_final 5 | 6 | epoch: 24 7 | LearningRate: 8 | base_lr: 0.01 9 | schedulers: 10 | - !PiecewiseDecay 11 | gamma: 0.1 12 | milestones: [16, 22] 13 | - !LinearWarmup 14 | start_factor: 0.3333333333333333 15 | steps: 500 16 | -------------------------------------------------------------------------------- /ppyolo/configs/mask_rcnn/mask_rcnn_r50_fpn_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_instance.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_1x.yml', 5 | '_base_/mask_rcnn_r50_fpn.yml', 6 | '_base_/mask_fpn_reader.yml', 7 | ] 8 | weights: output/mask_rcnn_r50_fpn_1x_coco/model_final 9 | -------------------------------------------------------------------------------- /ppyolo/configs/mask_rcnn/mask_rcnn_r50_fpn_2x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'mask_rcnn_r50_fpn_1x_coco.yml', 3 | ] 4 | weights: output/mask_rcnn_r50_fpn_2x_coco/model_final 5 | 6 | epoch: 24 7 | LearningRate: 8 | base_lr: 0.01 9 | schedulers: 10 | - !PiecewiseDecay 11 | gamma: 0.1 12 | milestones: [16, 22] 13 | - !LinearWarmup 14 | start_factor: 0.3333333333333333 15 | steps: 500 16 | -------------------------------------------------------------------------------- /ppyolo/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'mask_rcnn_r50_fpn_1x_coco.yml', 3 | ] 4 | 5 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_pretrained.pdparams 6 | weights: output/mask_rcnn_r50_vd_fpn_1x_coco/model_final 7 | 8 | ResNet: 9 | # index 0 stands for res2 10 | depth: 50 11 | variant: d 12 | norm_type: bn 13 | freeze_at: 0 14 | return_idx: [0,1,2,3] 15 | num_stages: 4 16 | -------------------------------------------------------------------------------- /ppyolo/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_2x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'mask_rcnn_r50_fpn_1x_coco.yml', 3 | ] 4 | 5 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_pretrained.pdparams 6 | weights: output/mask_rcnn_r50_vd_fpn_2x_coco/model_final 7 | 8 | ResNet: 9 | # index 0 stands for res2 10 | depth: 50 11 | variant: d 12 | norm_type: bn 13 | freeze_at: 0 14 | return_idx: [0,1,2,3] 15 | num_stages: 4 16 | 17 | epoch: 24 18 | LearningRate: 19 | base_lr: 0.01 20 | schedulers: 21 | - !PiecewiseDecay 22 | gamma: 0.1 23 | milestones: [16, 22] 24 | - !LinearWarmup 25 | start_factor: 0.3333333333333333 26 | steps: 500 27 | -------------------------------------------------------------------------------- /ppyolo/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_ssld_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_instance.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_1x.yml', 5 | '_base_/mask_rcnn_r50_fpn.yml', 6 | '_base_/mask_fpn_reader.yml', 7 | ] 8 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_ssld_v2_pretrained.pdparams 9 | weights: output/mask_rcnn_r50_vd_fpn_ssld_1x_coco/model_final 10 | 11 | ResNet: 12 | depth: 50 13 | variant: d 14 | norm_type: bn 15 | freeze_at: 0 16 | return_idx: [0,1,2,3] 17 | num_stages: 4 18 | lr_mult_list: [0.05, 0.05, 0.1, 0.15] 19 | 20 | epoch: 12 21 | LearningRate: 22 | base_lr: 0.01 23 | schedulers: 24 | - !PiecewiseDecay 25 | gamma: 0.1 26 | milestones: [8, 11] 27 | - !LinearWarmup 28 | start_factor: 0.1 29 | steps: 1000 30 | -------------------------------------------------------------------------------- /ppyolo/configs/mask_rcnn/mask_rcnn_r50_vd_fpn_ssld_2x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_instance.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_1x.yml', 5 | '_base_/mask_rcnn_r50_fpn.yml', 6 | '_base_/mask_fpn_reader.yml', 7 | ] 8 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet50_vd_ssld_v2_pretrained.pdparams 9 | weights: output/mask_rcnn_r50_vd_fpn_ssld_2x_coco/model_final 10 | 11 | ResNet: 12 | depth: 50 13 | variant: d 14 | norm_type: bn 15 | freeze_at: 0 16 | return_idx: [0,1,2,3] 17 | num_stages: 4 18 | lr_mult_list: [0.05, 0.05, 0.1, 0.15] 19 | 20 | epoch: 24 21 | LearningRate: 22 | base_lr: 0.01 23 | schedulers: 24 | - !PiecewiseDecay 25 | gamma: 0.1 26 | milestones: [12, 22] 27 | - !LinearWarmup 28 | start_factor: 0.1 29 | steps: 1000 30 | -------------------------------------------------------------------------------- /ppyolo/configs/mask_rcnn/mask_rcnn_x101_vd_64x4d_fpn_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'mask_rcnn_r50_fpn_1x_coco.yml', 3 | ] 4 | 5 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNeXt101_vd_64x4d_pretrained.pdparams 6 | weights: output/mask_rcnn_x101_vd_64x4d_fpn_1x_coco/model_final 7 | 8 | ResNet: 9 | # for ResNeXt: groups, base_width, base_channels 10 | depth: 101 11 | variant: d 12 | groups: 64 13 | base_width: 4 14 | norm_type: bn 15 | freeze_at: 0 16 | return_idx: [0,1,2,3] 17 | num_stages: 4 18 | 19 | epoch: 12 20 | LearningRate: 21 | base_lr: 0.01 22 | schedulers: 23 | - !PiecewiseDecay 24 | gamma: 0.1 25 | milestones: [8, 11] 26 | - !LinearWarmup 27 | start_factor: 0.1 28 | steps: 1000 29 | -------------------------------------------------------------------------------- /ppyolo/configs/mask_rcnn/mask_rcnn_x101_vd_64x4d_fpn_2x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | 'mask_rcnn_r50_fpn_1x_coco.yml', 3 | ] 4 | 5 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNeXt101_vd_64x4d_pretrained.pdparams 6 | weights: output/mask_rcnn_x101_vd_64x4d_fpn_2x_coco/model_final 7 | 8 | ResNet: 9 | # for ResNeXt: groups, base_width, base_channels 10 | depth: 101 11 | variant: d 12 | groups: 64 13 | base_width: 4 14 | norm_type: bn 15 | freeze_at: 0 16 | return_idx: [0,1,2,3] 17 | num_stages: 4 18 | 19 | epoch: 24 20 | LearningRate: 21 | base_lr: 0.01 22 | schedulers: 23 | - !PiecewiseDecay 24 | gamma: 0.1 25 | milestones: [16, 22] 26 | - !LinearWarmup 27 | start_factor: 0.1 28 | steps: 1000 29 | -------------------------------------------------------------------------------- /ppyolo/configs/mot/deepsort/deepsort_pcb_pyramid_r101.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../../datasets/mot.yml', 3 | '../../runtime.yml', 4 | '_base_/deepsort_yolov3_darknet53_pcb_pyramid_r101.yml', 5 | '_base_/deepsort_reader_1088x608.yml', 6 | ] 7 | 8 | metric: MOT 9 | 10 | EvalMOTDataset: 11 | !MOTImageFolder 12 | task: MOT16_train 13 | dataset_dir: dataset/mot 14 | data_root: MOT16/images/train 15 | keep_ori_im: True # set True if used in DeepSORT 16 | 17 | det_weights: None 18 | reid_weights: https://paddledet.bj.bcebos.com/models/mot/deepsort_pcb_pyramid_r101.pdparams 19 | 20 | DeepSORT: 21 | detector: None 22 | reid: PCBPyramid 23 | tracker: DeepSORTTracker 24 | -------------------------------------------------------------------------------- /ppyolo/configs/mot/fairmot/_base_/fairmot_dla34.yml: -------------------------------------------------------------------------------- 1 | architecture: FairMOT 2 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/fairmot_dla34_crowdhuman_pretrained.pdparams 3 | 4 | FairMOT: 5 | detector: CenterNet 6 | reid: FairMOTEmbeddingHead 7 | loss: FairMOTLoss 8 | tracker: JDETracker 9 | 10 | CenterNet: 11 | backbone: DLA 12 | neck: CenterNetDLAFPN 13 | head: CenterNetHead 14 | post_process: CenterNetPostProcess 15 | for_mot: True 16 | 17 | CenterNetPostProcess: 18 | for_mot: True 19 | 20 | JDETracker: 21 | conf_thres: 0.4 22 | tracked_thresh: 0.4 23 | metric_type: cosine 24 | -------------------------------------------------------------------------------- /ppyolo/configs/mot/fairmot/_base_/optimizer_30e.yml: -------------------------------------------------------------------------------- 1 | epoch: 30 2 | 3 | LearningRate: 4 | base_lr: 0.0004 5 | schedulers: 6 | - !PiecewiseDecay 7 | gamma: 0.1 8 | milestones: [20,] 9 | use_warmup: False 10 | 11 | OptimizerBuilder: 12 | optimizer: 13 | type: Adam 14 | regularizer: NULL 15 | -------------------------------------------------------------------------------- /ppyolo/configs/mot/fairmot/fairmot_dla34_30e_1088x608.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../../datasets/mot.yml', 3 | '../../runtime.yml', 4 | '_base_/optimizer_30e.yml', 5 | '_base_/fairmot_dla34.yml', 6 | '_base_/fairmot_reader_1088x608.yml', 7 | ] 8 | 9 | metric: MOT 10 | weights: output/fairmot_dla34_30e_1088x608/model_final 11 | -------------------------------------------------------------------------------- /ppyolo/configs/mot/jde/_base_/optimizer_30e.yml: -------------------------------------------------------------------------------- 1 | epoch: 30 2 | 3 | LearningRate: 4 | base_lr: 0.01 5 | schedulers: 6 | - !PiecewiseDecay 7 | gamma: 0.1 8 | milestones: [15, 22] 9 | use_warmup: True 10 | - !BurninWarmup 11 | steps: 1000 12 | 13 | OptimizerBuilder: 14 | optimizer: 15 | momentum: 0.9 16 | type: Momentum 17 | regularizer: 18 | factor: 0.0001 19 | type: L2 20 | -------------------------------------------------------------------------------- /ppyolo/configs/mot/jde/_base_/optimizer_60e.yml: -------------------------------------------------------------------------------- 1 | epoch: 60 2 | 3 | LearningRate: 4 | base_lr: 0.01 5 | schedulers: 6 | - !PiecewiseDecay 7 | gamma: 0.1 8 | milestones: [30, 44] 9 | use_warmup: True 10 | - !BurninWarmup 11 | steps: 1000 12 | 13 | OptimizerBuilder: 14 | optimizer: 15 | momentum: 0.9 16 | type: Momentum 17 | regularizer: 18 | factor: 0.0001 19 | type: L2 20 | -------------------------------------------------------------------------------- /ppyolo/configs/pedestrian/demo/001.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/ppyolo/configs/pedestrian/demo/001.png -------------------------------------------------------------------------------- /ppyolo/configs/pedestrian/demo/002.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/ppyolo/configs/pedestrian/demo/002.png -------------------------------------------------------------------------------- /ppyolo/configs/pedestrian/demo/003.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/ppyolo/configs/pedestrian/demo/003.png -------------------------------------------------------------------------------- /ppyolo/configs/pedestrian/demo/004.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/ppyolo/configs/pedestrian/demo/004.png -------------------------------------------------------------------------------- /ppyolo/configs/ppyolo/_base_/optimizer_1x.yml: -------------------------------------------------------------------------------- 1 | epoch: 405 2 | 3 | LearningRate: 4 | base_lr: 0.01 5 | schedulers: 6 | - !PiecewiseDecay 7 | gamma: 0.1 8 | milestones: 9 | - 243 10 | - 324 11 | - !LinearWarmup 12 | start_factor: 0. 13 | steps: 4000 14 | 15 | OptimizerBuilder: 16 | optimizer: 17 | momentum: 0.9 18 | type: Momentum 19 | regularizer: 20 | factor: 0.0005 21 | type: L2 22 | -------------------------------------------------------------------------------- /ppyolo/configs/ppyolo/_base_/optimizer_2x.yml: -------------------------------------------------------------------------------- 1 | epoch: 811 2 | 3 | LearningRate: 4 | base_lr: 0.01 5 | schedulers: 6 | - !PiecewiseDecay 7 | gamma: 0.1 8 | milestones: 9 | - 649 10 | - 730 11 | - !LinearWarmup 12 | start_factor: 0. 13 | steps: 4000 14 | 15 | OptimizerBuilder: 16 | optimizer: 17 | momentum: 0.9 18 | type: Momentum 19 | regularizer: 20 | factor: 0.0005 21 | type: L2 22 | -------------------------------------------------------------------------------- /ppyolo/configs/ppyolo/_base_/optimizer_365e.yml: -------------------------------------------------------------------------------- 1 | epoch: 365 2 | 3 | LearningRate: 4 | base_lr: 0.005 5 | schedulers: 6 | - !PiecewiseDecay 7 | gamma: 0.1 8 | milestones: 9 | - 243 10 | - !LinearWarmup 11 | start_factor: 0. 12 | steps: 4000 13 | 14 | OptimizerBuilder: 15 | clip_grad_by_norm: 35. 16 | optimizer: 17 | momentum: 0.9 18 | type: Momentum 19 | regularizer: 20 | factor: 0.0005 21 | type: L2 22 | -------------------------------------------------------------------------------- /ppyolo/configs/ppyolo/_base_/optimizer_650e.yml: -------------------------------------------------------------------------------- 1 | epoch: 650 2 | 3 | LearningRate: 4 | base_lr: 0.005 5 | schedulers: 6 | - !PiecewiseDecay 7 | gamma: 0.1 8 | milestones: 9 | - 430 10 | - 540 11 | - 610 12 | - !LinearWarmup 13 | start_factor: 0. 14 | steps: 4000 15 | 16 | OptimizerBuilder: 17 | optimizer: 18 | momentum: 0.9 19 | type: Momentum 20 | regularizer: 21 | factor: 0.0005 22 | type: L2 23 | -------------------------------------------------------------------------------- /ppyolo/configs/ppyolo/ppyolo_r50vd_dcn_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | './_base_/ppyolo_r50vd_dcn.yml', 5 | './_base_/optimizer_1x.yml', 6 | './_base_/ppyolo_reader.yml', 7 | ] 8 | 9 | snapshot_epoch: 16 10 | weights: resources/weights/ppyolo_r50vd_dcn_1x_coco.pdparams 11 | -------------------------------------------------------------------------------- /ppyolo/configs/ppyolo/ppyolo_r50vd_dcn_2x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | './_base_/ppyolo_r50vd_dcn.yml', 5 | './_base_/optimizer_2x.yml', 6 | './_base_/ppyolo_reader.yml', 7 | ] 8 | 9 | snapshot_epoch: 16 10 | weights: output/ppyolo_r50vd_dcn_2x_coco/model_final 11 | -------------------------------------------------------------------------------- /ppyolo/configs/ppyolo/ppyolo_test.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | './_base_/ppyolo_r50vd_dcn.yml', 5 | './_base_/optimizer_1x.yml', 6 | './_base_/ppyolo_reader.yml', 7 | ] 8 | 9 | snapshot_epoch: 16 10 | 11 | EvalDataset: 12 | !COCODataSet 13 | image_dir: test2017 14 | anno_path: annotations/image_info_test-dev2017.json 15 | dataset_dir: dataset/coco 16 | -------------------------------------------------------------------------------- /ppyolo/configs/ppyolo/ppyolo_tiny_650e_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | './_base_/ppyolo_tiny.yml', 5 | './_base_/optimizer_650e.yml', 6 | './_base_/ppyolo_tiny_reader.yml', 7 | ] 8 | 9 | snapshot_epoch: 1 10 | weights: output/ppyolo_tiny_650e_coco/model_final 11 | -------------------------------------------------------------------------------- /ppyolo/configs/ppyolo/ppyolov2_r101vd_dcn_365e_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | './_base_/ppyolov2_r50vd_dcn.yml', 5 | './_base_/optimizer_365e.yml', 6 | './_base_/ppyolov2_reader.yml', 7 | ] 8 | 9 | snapshot_epoch: 8 10 | weights: output/ppyolov2_r101vd_dcn_365e_coco/model_final 11 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/ResNet101_vd_ssld_pretrained.pdparams 12 | 13 | ResNet: 14 | depth: 101 15 | variant: d 16 | return_idx: [1, 2, 3] 17 | dcn_v2_stages: [3] 18 | freeze_at: -1 19 | freeze_norm: false 20 | norm_decay: 0. 21 | -------------------------------------------------------------------------------- /ppyolo/configs/ppyolo/ppyolov2_r50vd_dcn_365e_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | './_base_/ppyolov2_r50vd_dcn.yml', 5 | './_base_/optimizer_365e.yml', 6 | './_base_/ppyolov2_reader.yml', 7 | ] 8 | 9 | snapshot_epoch: 8 10 | weights: output/ppyolov2_r50vd_dcn_365e_coco/model_final 11 | -------------------------------------------------------------------------------- /ppyolo/configs/rcnn_enhance/_base_/optimizer_3x.yml: -------------------------------------------------------------------------------- 1 | epoch: 36 2 | 3 | LearningRate: 4 | base_lr: 0.02 5 | schedulers: 6 | - !PiecewiseDecay 7 | gamma: 0.1 8 | milestones: [24, 33] 9 | - !LinearWarmup 10 | start_factor: 0. 11 | steps: 1000 12 | 13 | OptimizerBuilder: 14 | optimizer: 15 | momentum: 0.9 16 | type: Momentum 17 | regularizer: 18 | factor: 0.0001 19 | type: L2 20 | -------------------------------------------------------------------------------- /ppyolo/configs/rcnn_enhance/faster_rcnn_enhance_3x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_3x.yml', 5 | '_base_/faster_rcnn_enhance.yml', 6 | '_base_/faster_rcnn_enhance_reader.yml', 7 | ] 8 | weights: output/faster_rcnn_enhance_r50_3x_coco/model_final 9 | -------------------------------------------------------------------------------- /ppyolo/configs/runtime.yml: -------------------------------------------------------------------------------- 1 | use_gpu: true 2 | log_iter: 20 3 | save_dir: output 4 | snapshot_epoch: 1 5 | -------------------------------------------------------------------------------- /ppyolo/configs/slim/distill/yolov3_mobilenet_v1_coco_distill.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../../yolov3/yolov3_r34_270e_coco.yml', 3 | ] 4 | 5 | pretrain_weights: https://paddledet.bj.bcebos.com/models/yolov3_r34_270e_coco.pdparams 6 | 7 | 8 | slim: Distill 9 | distill_loss: DistillYOLOv3Loss 10 | 11 | DistillYOLOv3Loss: 12 | weight: 1000 13 | -------------------------------------------------------------------------------- /ppyolo/configs/slim/prune/ppyolo_mbv3_large_prune_fpgm.yml: -------------------------------------------------------------------------------- 1 | pretrain_weights: https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams 2 | slim: Pruner 3 | 4 | Pruner: 5 | criterion: fpgm 6 | pruned_params: ['conv2d_62.w_0', 'conv2d_63.w_0', 'conv2d_64.w_0', 7 | 'conv2d_65.w_0', 'conv2d_66.w_0', 'conv2d_67.w_0'] 8 | pruned_ratios: [0.75, 0.75, 0.75, 0.75, 0.75, 0.75] 9 | print_params: True 10 | -------------------------------------------------------------------------------- /ppyolo/configs/slim/prune/ppyolo_r50vd_prune_fpgm.yml: -------------------------------------------------------------------------------- 1 | pretrain_weights: https://paddledet.bj.bcebos.com/models/ppyolo_r50vd_dcn_1x_coco.pdparams 2 | slim: Pruner 3 | 4 | Pruner: 5 | criterion: fpgm 6 | pruned_params: ['conv2d_56.w_0', 'conv2d_57.w_0', 'conv2d_58.w_0', 7 | 'conv2d_59.w_0', 'conv2d_60.w_0', 'conv2d_61.w_0', 8 | 'conv2d_63.w_0', 'conv2d_64.w_0', 'conv2d_65.w_0', 9 | 'conv2d_66.w_0', 'conv2d_67.w_0', 'conv2d_68.w_0', 10 | 'conv2d_70.w_0', 'conv2d_71.w_0', 'conv2d_72.w_0', 11 | 'conv2d_73.w_0', 'conv2d_74.w_0', 'conv2d_75.w_0'] 12 | pruned_ratios: [0.75,0.75,0.75,0.75,0.75,0.75,0.75,0.75,0.75,0.75,0.75,0.75,0.875,0.875,0.875,0.875,0.875,0.875] 13 | print_params: False 14 | -------------------------------------------------------------------------------- /ppyolo/configs/slim/prune/yolov3_darknet_prune_fpgm.yml: -------------------------------------------------------------------------------- 1 | pretrain_weights: https://paddledet.bj.bcebos.com/models/yolov3_darknet53_270e_coco.pdparams 2 | slim: Pruner 3 | 4 | Pruner: 5 | criterion: fpgm 6 | pruned_params: ['conv2d_52.w_0', 'conv2d_53.w_0', 'conv2d_54.w_0', 7 | 'conv2d_55.w_0', 'conv2d_56.w_0', 'conv2d_57.w_0', 8 | 'conv2d_59.w_0', 'conv2d_60.w_0', 'conv2d_61.w_0', 9 | 'conv2d_62.w_0', 'conv2d_63.w_0', 'conv2d_64.w_0', 10 | 'conv2d_66.w_0', 'conv2d_67.w_0', 'conv2d_68.w_0', 11 | 'conv2d_69.w_0', 'conv2d_70.w_0', 'conv2d_71.w_0'] 12 | pruned_ratios: [0.75,0.75,0.75,0.75,0.75,0.75,0.75,0.75,0.75,0.75,0.75,0.75,0.875,0.875,0.875,0.875,0.875,0.875] 13 | print_params: True 14 | -------------------------------------------------------------------------------- /ppyolo/configs/slim/prune/yolov3_prune_fpgm.yml: -------------------------------------------------------------------------------- 1 | # Weights of yolov3_mobilenet_v1_voc 2 | pretrain_weights: https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams 3 | slim: Pruner 4 | 5 | Pruner: 6 | criterion: fpgm 7 | pruned_params: ['conv2d_27.w_0', 'conv2d_28.w_0', 'conv2d_29.w_0', 8 | 'conv2d_30.w_0', 'conv2d_31.w_0', 'conv2d_32.w_0', 9 | 'conv2d_34.w_0', 'conv2d_35.w_0', 'conv2d_36.w_0', 10 | 'conv2d_37.w_0', 'conv2d_38.w_0', 'conv2d_39.w_0', 11 | 'conv2d_41.w_0', 'conv2d_42.w_0', 'conv2d_43.w_0', 12 | 'conv2d_44.w_0', 'conv2d_45.w_0', 'conv2d_46.w_0'] 13 | pruned_ratios: [0.1,0.2,0.2,0.2,0.2,0.1,0.2,0.3,0.3,0.3,0.2,0.1,0.3,0.4,0.4,0.4,0.4,0.3] 14 | print_params: False 15 | -------------------------------------------------------------------------------- /ppyolo/configs/slim/prune/yolov3_prune_l1_norm.yml: -------------------------------------------------------------------------------- 1 | # Weights of yolov3_mobilenet_v1_voc 2 | pretrain_weights: https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_voc.pdparams 3 | slim: Pruner 4 | 5 | Pruner: 6 | criterion: l1_norm 7 | pruned_params: ['conv2d_27.w_0', 'conv2d_28.w_0', 'conv2d_29.w_0', 8 | 'conv2d_30.w_0', 'conv2d_31.w_0', 'conv2d_32.w_0', 9 | 'conv2d_34.w_0', 'conv2d_35.w_0', 'conv2d_36.w_0', 10 | 'conv2d_37.w_0', 'conv2d_38.w_0', 'conv2d_39.w_0', 11 | 'conv2d_41.w_0', 'conv2d_42.w_0', 'conv2d_43.w_0', 12 | 'conv2d_44.w_0', 'conv2d_45.w_0', 'conv2d_46.w_0'] 13 | pruned_ratios: [0.1,0.2,0.2,0.2,0.2,0.1,0.2,0.3,0.3,0.3,0.2,0.1,0.3,0.4,0.4,0.4,0.4,0.3] 14 | print_params: False 15 | -------------------------------------------------------------------------------- /ppyolo/configs/slim/quant/mask_rcnn_r50_fpn_1x_qat.yml: -------------------------------------------------------------------------------- 1 | pretrain_weights: https://paddledet.bj.bcebos.com/models/mask_rcnn_r50_fpn_1x_coco.pdparams 2 | slim: QAT 3 | 4 | QAT: 5 | quant_config: { 6 | 'weight_quantize_type': 'channel_wise_abs_max', 'activation_quantize_type': 'moving_average_abs_max', 7 | 'weight_bits': 8, 'activation_bits': 8, 'dtype': 'int8', 'window_size': 10000, 'moving_rate': 0.9, 8 | 'quantizable_layer_type': ['Conv2D', 'Linear']} 9 | print_model: True 10 | 11 | 12 | epoch: 5 13 | 14 | LearningRate: 15 | base_lr: 0.001 16 | schedulers: 17 | - !PiecewiseDecay 18 | gamma: 0.1 19 | milestones: [3, 4] 20 | - !LinearWarmup 21 | start_factor: 0.001 22 | steps: 100 23 | -------------------------------------------------------------------------------- /ppyolo/configs/slim/quant/ppyolo_mbv3_large_qat.yml: -------------------------------------------------------------------------------- 1 | pretrain_weights: https://paddledet.bj.bcebos.com/models/ppyolo_mbv3_large_coco.pdparams 2 | slim: QAT 3 | 4 | QAT: 5 | quant_config: { 6 | 'weight_quantize_type': 'channel_wise_abs_max', 'activation_quantize_type': 'moving_average_abs_max', 7 | 'weight_bits': 8, 'activation_bits': 8, 'dtype': 'int8', 'window_size': 10000, 'moving_rate': 0.99, 8 | 'quantizable_layer_type': ['Conv2D', 'Linear']} 9 | print_model: True 10 | 11 | PPYOLOFPN: 12 | in_channels: [160, 368] 13 | coord_conv: true 14 | conv_block_num: 0 15 | spp: true 16 | drop_block: false 17 | -------------------------------------------------------------------------------- /ppyolo/configs/slim/quant/ssd_mobilenet_v1_qat.yml: -------------------------------------------------------------------------------- 1 | pretrain_weights: https://paddlemodels.bj.bcebos.com/object_detection/dygraph/ssd_mobilenet_v1_300_120e_voc.pdparams 2 | slim: QAT 3 | 4 | QAT: 5 | quant_config: { 6 | 'weight_quantize_type': 'channel_wise_abs_max', 'activation_quantize_type': 'moving_average_abs_max', 7 | 'weight_bits': 8, 'activation_bits': 8, 'dtype': 'int8', 'window_size': 10000, 'moving_rate': 0.9, 8 | 'quantizable_layer_type': ['Conv2D', 'Linear']} 9 | print_model: True 10 | -------------------------------------------------------------------------------- /ppyolo/configs/slim/quant/yolov3_mobilenet_v1_qat.yml: -------------------------------------------------------------------------------- 1 | # Weights of yolov3_mobilenet_v1_coco 2 | pretrain_weights: https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v1_270e_coco.pdparams 3 | slim: QAT 4 | 5 | QAT: 6 | quant_config: { 7 | 'weight_quantize_type': 'channel_wise_abs_max', 'activation_quantize_type': 'moving_average_abs_max', 8 | 'weight_bits': 8, 'activation_bits': 8, 'dtype': 'int8', 'window_size': 10000, 'moving_rate': 0.9, 9 | 'quantizable_layer_type': ['Conv2D', 'Linear']} 10 | print_model: True 11 | -------------------------------------------------------------------------------- /ppyolo/configs/slim/quant/yolov3_mobilenet_v3_qat.yml: -------------------------------------------------------------------------------- 1 | # Weights of yolov3_mobilenet_v3_coco 2 | pretrain_weights: https://paddledet.bj.bcebos.com/models/yolov3_mobilenet_v3_large_270e_coco.pdparams 3 | slim: QAT 4 | 5 | QAT: 6 | quant_config: { 7 | 'activation_preprocess_type': 'PACT', 8 | 'weight_quantize_type': 'channel_wise_abs_max', 'activation_quantize_type': 'moving_average_abs_max', 9 | 'weight_bits': 8, 'activation_bits': 8, 'dtype': 'int8', 'window_size': 10000, 'moving_rate': 0.9, 10 | 'quantizable_layer_type': ['Conv2D', 'Linear']} 11 | print_model: True 12 | 13 | epoch: 50 14 | LearningRate: 15 | base_lr: 0.0001 16 | schedulers: 17 | - !PiecewiseDecay 18 | gamma: 0.1 19 | milestones: 20 | - 35 21 | - 45 22 | - !LinearWarmup 23 | start_factor: 0. 24 | steps: 1000 25 | -------------------------------------------------------------------------------- /ppyolo/configs/solov2/_base_/optimizer_1x.yml: -------------------------------------------------------------------------------- 1 | epoch: 12 2 | 3 | LearningRate: 4 | base_lr: 0.01 5 | schedulers: 6 | - !PiecewiseDecay 7 | gamma: 0.1 8 | milestones: [8, 11] 9 | - !LinearWarmup 10 | start_factor: 0. 11 | steps: 1000 12 | 13 | OptimizerBuilder: 14 | optimizer: 15 | momentum: 0.9 16 | type: Momentum 17 | regularizer: 18 | factor: 0.0001 19 | type: L2 20 | -------------------------------------------------------------------------------- /ppyolo/configs/solov2/solov2_r50_fpn_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_instance.yml', 3 | '../runtime.yml', 4 | '_base_/solov2_r50_fpn.yml', 5 | '_base_/optimizer_1x.yml', 6 | '_base_/solov2_reader.yml', 7 | ] 8 | weights: output/solov2_r50_fpn_1x_coco/model_final 9 | -------------------------------------------------------------------------------- /ppyolo/configs/ssd/_base_/optimizer_120e.yml: -------------------------------------------------------------------------------- 1 | epoch: 120 2 | 3 | LearningRate: 4 | base_lr: 0.001 5 | schedulers: 6 | - !PiecewiseDecay 7 | milestones: [40, 60, 80, 100] 8 | gamma: [0.5, 0.5, 0.4, 0.1] 9 | use_warmup: false 10 | 11 | OptimizerBuilder: 12 | optimizer: 13 | momentum: 0.0 14 | type: RMSProp 15 | regularizer: 16 | factor: 0.00005 17 | type: L2 18 | -------------------------------------------------------------------------------- /ppyolo/configs/ssd/_base_/optimizer_1700e.yml: -------------------------------------------------------------------------------- 1 | epoch: 1700 2 | 3 | LearningRate: 4 | base_lr: 0.4 5 | schedulers: 6 | - !CosineDecay 7 | max_epochs: 1700 8 | - !LinearWarmup 9 | start_factor: 0.3333333333333333 10 | steps: 2000 11 | 12 | OptimizerBuilder: 13 | optimizer: 14 | momentum: 0.9 15 | type: Momentum 16 | regularizer: 17 | factor: 0.0005 18 | type: L2 19 | -------------------------------------------------------------------------------- /ppyolo/configs/ssd/_base_/optimizer_240e.yml: -------------------------------------------------------------------------------- 1 | epoch: 240 2 | 3 | LearningRate: 4 | base_lr: 0.001 5 | schedulers: 6 | - !PiecewiseDecay 7 | gamma: 0.1 8 | milestones: 9 | - 160 10 | - 200 11 | - !LinearWarmup 12 | start_factor: 0.3333333333333333 13 | steps: 500 14 | 15 | OptimizerBuilder: 16 | optimizer: 17 | momentum: 0.9 18 | type: Momentum 19 | regularizer: 20 | factor: 0.0005 21 | type: L2 22 | -------------------------------------------------------------------------------- /ppyolo/configs/ssd/ssd_mobilenet_v1_300_120e_voc.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/voc.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_120e.yml', 5 | '_base_/ssd_mobilenet_v1_300.yml', 6 | '_base_/ssd_mobilenet_reader.yml', 7 | ] 8 | weights: output/ssd_mobilenet_v1_300_120e_voc/model_final 9 | 10 | # set collate_batch to false because ground-truth info is needed 11 | # on voc dataset and should not collate data in batch when batch size 12 | # is larger than 1. 13 | EvalReader: 14 | collate_batch: false 15 | -------------------------------------------------------------------------------- /ppyolo/configs/ssd/ssd_vgg16_300_240e_voc.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/voc.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_240e.yml', 5 | '_base_/ssd_vgg16_300.yml', 6 | '_base_/ssd_reader.yml', 7 | ] 8 | weights: output/ssd_vgg16_300_240e_voc/model_final 9 | 10 | # set collate_batch to false because ground-truth info is needed 11 | # on voc dataset and should not collate data in batch when batch size 12 | # is larger than 1. 13 | EvalReader: 14 | collate_batch: false 15 | -------------------------------------------------------------------------------- /ppyolo/configs/ssd/ssdlite_ghostnet_320_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_1700e.yml', 5 | '_base_/ssdlite_ghostnet_320.yml', 6 | '_base_/ssdlite320_reader.yml', 7 | ] 8 | weights: output/ssdlite_ghostnet_320_coco/model_final 9 | 10 | epoch: 1700 11 | 12 | LearningRate: 13 | base_lr: 0.2 14 | schedulers: 15 | - !CosineDecay 16 | max_epochs: 1700 17 | - !LinearWarmup 18 | start_factor: 0.33333 19 | steps: 2000 20 | 21 | OptimizerBuilder: 22 | optimizer: 23 | momentum: 0.9 24 | type: Momentum 25 | regularizer: 26 | factor: 0.0005 27 | type: L2 28 | -------------------------------------------------------------------------------- /ppyolo/configs/ssd/ssdlite_mobilenet_v1_300_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_1700e.yml', 5 | '_base_/ssdlite_mobilenet_v1_300.yml', 6 | '_base_/ssdlite300_reader.yml', 7 | ] 8 | weights: output/ssdlite_mobilenet_v1_300_coco/model_final 9 | -------------------------------------------------------------------------------- /ppyolo/configs/ssd/ssdlite_mobilenet_v3_large_320_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_1700e.yml', 5 | '_base_/ssdlite_mobilenet_v3_large_320.yml', 6 | '_base_/ssdlite320_reader.yml', 7 | ] 8 | weights: output/ssdlite_mobilenet_v3_large_320_coco/model_final 9 | -------------------------------------------------------------------------------- /ppyolo/configs/ssd/ssdlite_mobilenet_v3_small_320_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_1700e.yml', 5 | '_base_/ssdlite_mobilenet_v3_small_320.yml', 6 | '_base_/ssdlite320_reader.yml', 7 | ] 8 | weights: output/ssdlite_mobilenet_v3_small_320_coco/model_final 9 | -------------------------------------------------------------------------------- /ppyolo/configs/ttfnet/_base_/optimizer_10x.yml: -------------------------------------------------------------------------------- 1 | epoch: 120 2 | 3 | LearningRate: 4 | base_lr: 0.015 5 | schedulers: 6 | - !PiecewiseDecay 7 | gamma: 0.1 8 | milestones: [80, 110] 9 | - !LinearWarmup 10 | start_factor: 0.2 11 | steps: 500 12 | 13 | OptimizerBuilder: 14 | optimizer: 15 | momentum: 0.9 16 | type: Momentum 17 | regularizer: 18 | factor: 0.0004 19 | type: L2 20 | -------------------------------------------------------------------------------- /ppyolo/configs/ttfnet/_base_/optimizer_1x.yml: -------------------------------------------------------------------------------- 1 | epoch: 12 2 | 3 | LearningRate: 4 | base_lr: 0.015 5 | schedulers: 6 | - !PiecewiseDecay 7 | gamma: 0.1 8 | milestones: [8, 11] 9 | - !LinearWarmup 10 | start_factor: 0.2 11 | steps: 500 12 | 13 | OptimizerBuilder: 14 | optimizer: 15 | momentum: 0.9 16 | type: Momentum 17 | regularizer: 18 | factor: 0.0004 19 | type: L2 20 | -------------------------------------------------------------------------------- /ppyolo/configs/ttfnet/_base_/optimizer_20x.yml: -------------------------------------------------------------------------------- 1 | epoch: 240 2 | 3 | LearningRate: 4 | base_lr: 0.015 5 | schedulers: 6 | - !PiecewiseDecay 7 | gamma: 0.1 8 | milestones: [160, 220] 9 | - !LinearWarmup 10 | start_factor: 0.2 11 | steps: 1000 12 | 13 | OptimizerBuilder: 14 | clip_grad_by_norm: 35 15 | optimizer: 16 | momentum: 0.9 17 | type: Momentum 18 | regularizer: 19 | factor: 0.0004 20 | type: L2 21 | -------------------------------------------------------------------------------- /ppyolo/configs/ttfnet/_base_/ttfnet_darknet53.yml: -------------------------------------------------------------------------------- 1 | architecture: TTFNet 2 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/DarkNet53_pretrained.pdparams 3 | 4 | TTFNet: 5 | backbone: DarkNet 6 | neck: TTFFPN 7 | ttf_head: TTFHead 8 | post_process: BBoxPostProcess 9 | 10 | DarkNet: 11 | depth: 53 12 | freeze_at: 0 13 | return_idx: [1, 2, 3, 4] 14 | norm_type: bn 15 | norm_decay: 0.0004 16 | 17 | TTFFPN: 18 | planes: [256, 128, 64] 19 | shortcut_num: [3, 2, 1] 20 | 21 | TTFHead: 22 | hm_loss: 23 | name: CTFocalLoss 24 | loss_weight: 1. 25 | wh_loss: 26 | name: GIoULoss 27 | loss_weight: 5. 28 | reduction: sum 29 | 30 | BBoxPostProcess: 31 | decode: 32 | name: TTFBox 33 | max_per_img: 100 34 | score_thresh: 0.01 35 | down_ratio: 4 36 | -------------------------------------------------------------------------------- /ppyolo/configs/ttfnet/pafnet_10x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_10x.yml', 5 | '_base_/pafnet.yml', 6 | '_base_/pafnet_reader.yml', 7 | ] 8 | weights: output/pafnet_10x_coco/model_final 9 | -------------------------------------------------------------------------------- /ppyolo/configs/ttfnet/pafnet_lite_mobilenet_v3_20x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_20x.yml', 5 | '_base_/pafnet_lite.yml', 6 | '_base_/pafnet_lite_reader.yml', 7 | ] 8 | weights: output/pafnet_lite_mobilenet_v3_10x_coco/model_final 9 | -------------------------------------------------------------------------------- /ppyolo/configs/ttfnet/ttfnet_darknet53_1x_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_1x.yml', 5 | '_base_/ttfnet_darknet53.yml', 6 | '_base_/ttfnet_reader.yml', 7 | ] 8 | weights: output/ttfnet_darknet53_1x_coco/model_final 9 | -------------------------------------------------------------------------------- /ppyolo/configs/vehicle/demo/001.jpeg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/ppyolo/configs/vehicle/demo/001.jpeg -------------------------------------------------------------------------------- /ppyolo/configs/vehicle/demo/003.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/ppyolo/configs/vehicle/demo/003.png -------------------------------------------------------------------------------- /ppyolo/configs/vehicle/demo/004.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/ppyolo/configs/vehicle/demo/004.png -------------------------------------------------------------------------------- /ppyolo/configs/vehicle/demo/005.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/ppyolo/configs/vehicle/demo/005.png -------------------------------------------------------------------------------- /ppyolo/configs/yolov3/_base_/optimizer_270e.yml: -------------------------------------------------------------------------------- 1 | epoch: 270 2 | 3 | LearningRate: 4 | base_lr: 0.001 5 | schedulers: 6 | - !PiecewiseDecay 7 | gamma: 0.1 8 | milestones: 9 | - 216 10 | - 243 11 | - !LinearWarmup 12 | start_factor: 0. 13 | steps: 4000 14 | 15 | OptimizerBuilder: 16 | optimizer: 17 | momentum: 0.9 18 | type: Momentum 19 | regularizer: 20 | factor: 0.0005 21 | type: L2 22 | -------------------------------------------------------------------------------- /ppyolo/configs/yolov3/_base_/optimizer_40e.yml: -------------------------------------------------------------------------------- 1 | epoch: 40 2 | 3 | LearningRate: 4 | base_lr: 0.0001 5 | schedulers: 6 | - !PiecewiseDecay 7 | gamma: 0.1 8 | milestones: 9 | - 32 10 | - 36 11 | - !LinearWarmup 12 | start_factor: 0.3333333333333333 13 | steps: 100 14 | 15 | OptimizerBuilder: 16 | optimizer: 17 | momentum: 0.9 18 | type: Momentum 19 | regularizer: 20 | factor: 0.0005 21 | type: L2 22 | -------------------------------------------------------------------------------- /ppyolo/configs/yolov3/yolov3_darknet53_270e_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_270e.yml', 5 | '_base_/yolov3_darknet53.yml', 6 | '_base_/yolov3_reader.yml', 7 | ] 8 | 9 | snapshot_epoch: 5 10 | weights: output/yolov3_darknet53_270e_coco/model_final 11 | -------------------------------------------------------------------------------- /ppyolo/configs/yolov3/yolov3_darknet53_270e_voc.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/voc.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_270e.yml', 5 | '_base_/yolov3_darknet53.yml', 6 | '_base_/yolov3_reader.yml', 7 | ] 8 | 9 | snapshot_epoch: 5 10 | weights: output/yolov3_darknet53_270e_voc/model_final 11 | 12 | # set collate_batch to false because ground-truth info is needed 13 | # on voc dataset and should not collate data in batch when batch size 14 | # is larger than 1. 15 | EvalReader: 16 | collate_batch: false 17 | -------------------------------------------------------------------------------- /ppyolo/configs/yolov3/yolov3_mobilenet_v1_270e_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_270e.yml', 5 | '_base_/yolov3_mobilenet_v1.yml', 6 | '_base_/yolov3_reader.yml', 7 | ] 8 | 9 | snapshot_epoch: 5 10 | weights: output/yolov3_mobilenet_v1_270e_coco/model_final 11 | -------------------------------------------------------------------------------- /ppyolo/configs/yolov3/yolov3_mobilenet_v1_270e_voc.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/voc.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_270e.yml', 5 | '_base_/yolov3_mobilenet_v1.yml', 6 | '_base_/yolov3_reader.yml', 7 | ] 8 | 9 | snapshot_epoch: 5 10 | weights: output/yolov3_mobilenet_v1_270e_voc/model_final 11 | 12 | # set collate_batch to false because ground-truth info is needed 13 | # on voc dataset and should not collate data in batch when batch size 14 | # is larger than 1. 15 | EvalReader: 16 | collate_batch: false 17 | 18 | LearningRate: 19 | base_lr: 0.001 20 | schedulers: 21 | - !PiecewiseDecay 22 | gamma: 0.1 23 | milestones: 24 | - 216 25 | - 243 26 | - !LinearWarmup 27 | start_factor: 0. 28 | steps: 1000 29 | -------------------------------------------------------------------------------- /ppyolo/configs/yolov3/yolov3_mobilenet_v1_roadsign.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/roadsign_voc.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_40e.yml', 5 | '_base_/yolov3_mobilenet_v1.yml', 6 | '_base_/yolov3_reader.yml', 7 | ] 8 | pretrain_weights: resources/weights/yolov3_mobilenet_v1_270e_coco.pdparams 9 | weights: resources/weights/model_final 10 | 11 | YOLOv3Loss: 12 | ignore_thresh: 0.7 13 | label_smooth: true 14 | -------------------------------------------------------------------------------- /ppyolo/configs/yolov3/yolov3_mobilenet_v1_ssld_270e_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_270e.yml', 5 | '_base_/yolov3_mobilenet_v1.yml', 6 | '_base_/yolov3_reader.yml', 7 | ] 8 | 9 | snapshot_epoch: 5 10 | pretrain_weights: https://paddledet.bj.bcebos.com/models/pretrained/MobileNetV1_ssld_pretrained.pdparams 11 | weights: output/yolov3_mobilenet_v1_ssld_270e_coco/model_final 12 | -------------------------------------------------------------------------------- /ppyolo/configs/yolov3/yolov3_mobilenet_v3_large_270e_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_270e.yml', 5 | '_base_/yolov3_mobilenet_v3_large.yml', 6 | '_base_/yolov3_reader.yml', 7 | ] 8 | 9 | snapshot_epoch: 5 10 | weights: output/yolov3_mobilenet_v3_large_270e_coco/model_final 11 | -------------------------------------------------------------------------------- /ppyolo/configs/yolov3/yolov3_mobilenet_v3_large_270e_voc.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/voc.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_270e.yml', 5 | '_base_/yolov3_mobilenet_v3_large.yml', 6 | '_base_/yolov3_reader.yml', 7 | ] 8 | 9 | snapshot_epoch: 5 10 | weights: output/yolov3_mobilenet_v3_large_270e_voc/model_final 11 | 12 | # set collate_batch to false because ground-truth info is needed 13 | # on voc dataset and should not collate data in batch when batch size 14 | # is larger than 1. 15 | EvalReader: 16 | collate_batch: false 17 | 18 | LearningRate: 19 | base_lr: 0.001 20 | schedulers: 21 | - !PiecewiseDecay 22 | gamma: 0.1 23 | milestones: 24 | - 216 25 | - 243 26 | - !LinearWarmup 27 | start_factor: 0. 28 | steps: 1000 29 | -------------------------------------------------------------------------------- /ppyolo/configs/yolov3/yolov3_r34_270e_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_270e.yml', 5 | '_base_/yolov3_r34.yml', 6 | '_base_/yolov3_reader.yml', 7 | ] 8 | 9 | snapshot_epoch: 5 10 | weights: output/yolov3_r34_270e_coco/model_final 11 | -------------------------------------------------------------------------------- /ppyolo/configs/yolov3/yolov3_r50vd_dcn_270e_coco.yml: -------------------------------------------------------------------------------- 1 | _BASE_: [ 2 | '../datasets/coco_detection.yml', 3 | '../runtime.yml', 4 | '_base_/optimizer_270e.yml', 5 | '_base_/yolov3_r50vd_dcn.yml', 6 | '_base_/yolov3_reader.yml', 7 | ] 8 | 9 | snapshot_epoch: 5 10 | weights: output/yolov3_r50vd_dcn_270e_coco/model_final 11 | -------------------------------------------------------------------------------- /ppyolo/ppdet/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. 2 | # 3 | # Licensed under the Apache License, Version 2.0 (the "License"); 4 | # you may not use this file except in compliance with the License. 5 | # You may obtain a copy of the License at 6 | # 7 | # http://www.apache.org/licenses/LICENSE-2.0 8 | # 9 | # Unless required by applicable law or agreed to in writing, software 10 | # distributed under the License is distributed on an "AS IS" BASIS, 11 | # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12 | # See the License for the specific language governing permissions and 13 | # limitations under the License. 14 | 15 | from . import (core, data, engine, modeling, model_zoo, optimizer, metrics, 16 | utils, slim) 17 | -------------------------------------------------------------------------------- /ppyolo/ppdet/core/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. 2 | # 3 | # Licensed under the Apache License, Version 2.0 (the "License"); 4 | # you may not use this file except in compliance with the License. 5 | # You may obtain a copy of the License at 6 | # 7 | # http://www.apache.org/licenses/LICENSE-2.0 8 | # 9 | # Unless required by applicable law or agreed to in writing, software 10 | # distributed under the License is distributed on an "AS IS" BASIS, 11 | # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12 | # See the License for the specific language governing permissions and 13 | # limitations under the License. 14 | 15 | from . import config 16 | -------------------------------------------------------------------------------- /ppyolo/ppdet/core/config/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. 2 | # 3 | # Licensed under the Apache License, Version 2.0 (the "License"); 4 | # you may not use this file except in compliance with the License. 5 | # You may obtain a copy of the License at 6 | # 7 | # http://www.apache.org/licenses/LICENSE-2.0 8 | # 9 | # Unless required by applicable law or agreed to in writing, software 10 | # distributed under the License is distributed on an "AS IS" BASIS, 11 | # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12 | # See the License for the specific language governing permissions and 13 | # limitations under the License. 14 | -------------------------------------------------------------------------------- /ppyolo/ppdet/ext_op/setup.py: -------------------------------------------------------------------------------- 1 | from paddle.utils.cpp_extension import CppExtension, CUDAExtension, setup 2 | 3 | if __name__ == "__main__": 4 | setup( 5 | name='rbox_iou_ops', 6 | ext_modules=CUDAExtension(sources=['rbox_iou_op.cc', 'rbox_iou_op.cu'])) 7 | -------------------------------------------------------------------------------- /ppyolo/ppdet/model_zoo/.gitignore: -------------------------------------------------------------------------------- 1 | MODEL_ZOO 2 | -------------------------------------------------------------------------------- /ppyolo/ppdet/model_zoo/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. 2 | # 3 | # Licensed under the Apache License, Version 2.0 (the "License"); 4 | # you may not use this file except in compliance with the License. 5 | # You may obtain a copy of the License at 6 | # 7 | # http://www.apache.org/licenses/LICENSE-2.0 8 | # 9 | # Unless required by applicable law or agreed to in writing, software 10 | # distributed under the License is distributed on an "AS IS" BASIS, 11 | # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12 | # See the License for the specific language governing permissions and 13 | # limitations under the License. 14 | 15 | from . import model_zoo 16 | from .model_zoo import * 17 | 18 | __all__ = model_zoo.__all__ 19 | -------------------------------------------------------------------------------- /ppyolo/ppdet/model_zoo/tests/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. 2 | # 3 | # Licensed under the Apache License, Version 2.0 (the "License"); 4 | # you may not use this file except in compliance with the License. 5 | # You may obtain a copy of the License at 6 | # 7 | # http://www.apache.org/licenses/LICENSE-2.0 8 | # 9 | # Unless required by applicable law or agreed to in writing, software 10 | # distributed under the License is distributed on an "AS IS" BASIS, 11 | # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12 | # See the License for the specific language governing permissions and 13 | # limitations under the License. 14 | -------------------------------------------------------------------------------- /ppyolo/ppdet/modeling/mot/motion/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved. 2 | # 3 | # Licensed under the Apache License, Version 2.0 (the "License"); 4 | # you may not use this file except in compliance with the License. 5 | # You may obtain a copy of the License at 6 | # 7 | # http://www.apache.org/licenses/LICENSE-2.0 8 | # 9 | # Unless required by applicable law or agreed to in writing, software 10 | # distributed under the License is distributed on an "AS IS" BASIS, 11 | # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12 | # See the License for the specific language governing permissions and 13 | # limitations under the License. 14 | 15 | from . import kalman_filter 16 | 17 | from .kalman_filter import * 18 | -------------------------------------------------------------------------------- /ppyolo/ppdet/modeling/proposal_generator/__init__.py: -------------------------------------------------------------------------------- 1 | from . import rpn_head 2 | from .rpn_head import * 3 | -------------------------------------------------------------------------------- /ppyolo/ppdet/modeling/tests/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. 2 | # 3 | # Licensed under the Apache License, Version 2.0 (the "License"); 4 | # you may not use this file except in compliance with the License. 5 | # You may obtain a copy of the License at 6 | # 7 | # http://www.apache.org/licenses/LICENSE-2.0 8 | # 9 | # Unless required by applicable law or agreed to in writing, software 10 | # distributed under the License is distributed on an "AS IS" BASIS, 11 | # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12 | # See the License for the specific language governing permissions and 13 | # limitations under the License. 14 | -------------------------------------------------------------------------------- /ppyolo/ppdet/utils/__init__.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved. 2 | # 3 | # Licensed under the Apache License, Version 2.0 (the "License"); 4 | # you may not use this file except in compliance with the License. 5 | # You may obtain a copy of the License at 6 | # 7 | # http://www.apache.org/licenses/LICENSE-2.0 8 | # 9 | # Unless required by applicable law or agreed to in writing, software 10 | # distributed under the License is distributed on an "AS IS" BASIS, 11 | # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 12 | # See the License for the specific language governing permissions and 13 | # limitations under the License. 14 | -------------------------------------------------------------------------------- /ppyolo/resources/images/000000014439.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/ppyolo/resources/images/000000014439.jpg -------------------------------------------------------------------------------- /ppyolo/resources/images/000000087038.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/ppyolo/resources/images/000000087038.jpg -------------------------------------------------------------------------------- /ppyolo/resources/images/000000570688.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/ppyolo/resources/images/000000570688.jpg -------------------------------------------------------------------------------- /ppyolo/resources/runs/000000014439.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/ppyolo/resources/runs/000000014439.jpg -------------------------------------------------------------------------------- /ppyolo/resources/runs/000000087038.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/ppyolo/resources/runs/000000087038.jpg -------------------------------------------------------------------------------- /ppyolo/resources/runs/000000570688.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/ppyolo/resources/runs/000000570688.jpg -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/Base-AGW.yml: -------------------------------------------------------------------------------- 1 | _BASE_: Base-bagtricks.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | WITH_NL: True 6 | 7 | HEADS: 8 | POOL_LAYER: GeneralizedMeanPooling 9 | 10 | LOSSES: 11 | NAME: ("CrossEntropyLoss", "TripletLoss") 12 | CE: 13 | EPSILON: 0.1 14 | SCALE: 1.0 15 | 16 | TRI: 17 | MARGIN: 0.0 18 | HARD_MINING: False 19 | SCALE: 1.0 20 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/Base-MGN.yml: -------------------------------------------------------------------------------- 1 | _BASE_: Base-SBS.yml 2 | 3 | MODEL: 4 | META_ARCHITECTURE: MGN 5 | 6 | FREEZE_LAYERS: [backbone, b1, b2, b3,] 7 | 8 | BACKBONE: 9 | WITH_NL: False 10 | 11 | HEADS: 12 | EMBEDDING_DIM: 256 13 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/DukeMTMC/AGW_R101-ibn.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-AGW.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | DEPTH: 101x 6 | WITH_IBN: True 7 | 8 | DATASETS: 9 | NAMES: ("DukeMTMC",) 10 | TESTS: ("DukeMTMC",) 11 | 12 | OUTPUT_DIR: logs/dukemtmc/agw_R101-ibn 13 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/DukeMTMC/AGW_R50-ibn.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-AGW.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | WITH_IBN: True 6 | 7 | DATASETS: 8 | NAMES: ("DukeMTMC",) 9 | TESTS: ("DukeMTMC",) 10 | 11 | OUTPUT_DIR: logs/dukemtmc/agw_R50-ibn 12 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/DukeMTMC/AGW_R50.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-AGW.yml 2 | 3 | DATASETS: 4 | NAMES: ("DukeMTMC",) 5 | TESTS: ("DukeMTMC",) 6 | 7 | OUTPUT_DIR: logs/dukemtmc/agw_R50 8 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/DukeMTMC/AGW_S50.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-AGW.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | NAME: build_resnest_backbone 6 | 7 | DATASETS: 8 | NAMES: ("DukeMTMC",) 9 | TESTS: ("DukeMTMC",) 10 | 11 | OUTPUT_DIR: logs/dukemtmc/agw_S50 12 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/DukeMTMC/bagtricks_R101-ibn.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-bagtricks.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | DEPTH: 101x 6 | WITH_IBN: True 7 | 8 | DATASETS: 9 | NAMES: ("DukeMTMC",) 10 | TESTS: ("DukeMTMC",) 11 | 12 | OUTPUT_DIR: logs/dukemtmc/bagtricks_R101-ibn 13 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/DukeMTMC/bagtricks_R50-ibn.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-bagtricks.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | WITH_IBN: True 6 | 7 | DATASETS: 8 | NAMES: ("DukeMTMC",) 9 | TESTS: ("DukeMTMC",) 10 | 11 | OUTPUT_DIR: logs/dukemtmc/bagtricks_R50-ibn 12 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/DukeMTMC/bagtricks_R50.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-bagtricks.yml 2 | 3 | DATASETS: 4 | NAMES: ("DukeMTMC",) 5 | TESTS: ("DukeMTMC",) 6 | 7 | OUTPUT_DIR: logs/dukemtmc/bagtricks_R50 8 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/DukeMTMC/bagtricks_S50.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-bagtricks.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | NAME: build_resnest_backbone 6 | 7 | DATASETS: 8 | NAMES: ("DukeMTMC",) 9 | TESTS: ("DukeMTMC",) 10 | 11 | OUTPUT_DIR: logs/dukemtmc/bagtricks_S50 12 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/DukeMTMC/mgn_R50-ibn.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-MGN.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | WITH_IBN: True 6 | 7 | DATASETS: 8 | NAMES: ("DukeMTMC",) 9 | TESTS: ("DukeMTMC",) 10 | 11 | OUTPUT_DIR: logs/dukemtmc/mgn_R50-ibn 12 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/DukeMTMC/sbs_R101-ibn.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-SBS.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | DEPTH: 101x 6 | WITH_IBN: True 7 | 8 | DATASETS: 9 | NAMES: ("DukeMTMC",) 10 | TESTS: ("DukeMTMC",) 11 | 12 | OUTPUT_DIR: logs/dukemtmc/sbs_R101-ibn 13 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/DukeMTMC/sbs_R50-ibn.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-SBS.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | WITH_IBN: True 6 | 7 | DATASETS: 8 | NAMES: ("DukeMTMC",) 9 | TESTS: ("DukeMTMC",) 10 | 11 | OUTPUT_DIR: logs/dukemtmc/sbs_R50-ibn 12 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/DukeMTMC/sbs_R50.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-SBS.yml 2 | 3 | DATASETS: 4 | NAMES: ("DukeMTMC",) 5 | TESTS: ("DukeMTMC",) 6 | 7 | OUTPUT_DIR: logs/dukemtmc/sbs_R50 8 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/DukeMTMC/sbs_S50.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-SBS.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | NAME: build_resnest_backbone 6 | 7 | DATASETS: 8 | NAMES: ("DukeMTMC",) 9 | TESTS: ("DukeMTMC",) 10 | 11 | OUTPUT_DIR: logs/dukemtmc/sbs_S50 12 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/MSMT17/AGW_R101-ibn.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-AGW.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | DEPTH: 101x 6 | WITH_IBN: True 7 | 8 | DATASETS: 9 | NAMES: ("MSMT17",) 10 | TESTS: ("MSMT17",) 11 | 12 | OUTPUT_DIR: logs/msmt17/agw_R101-ibn 13 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/MSMT17/AGW_R50-ibn.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-AGW.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | WITH_IBN: True 6 | 7 | DATASETS: 8 | NAMES: ("MSMT17",) 9 | TESTS: ("MSMT17",) 10 | 11 | OUTPUT_DIR: logs/msmt17/agw_R50-ibn 12 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/MSMT17/AGW_R50.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-AGW.yml 2 | 3 | DATASETS: 4 | NAMES: ("MSMT17",) 5 | TESTS: ("MSMT17",) 6 | 7 | OUTPUT_DIR: logs/msmt17/agw_R50 8 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/MSMT17/AGW_S50.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-AGW.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | NAME: build_resnest_backbone 6 | 7 | DATASETS: 8 | NAMES: ("MSMT17",) 9 | TESTS: ("MSMT17",) 10 | 11 | OUTPUT_DIR: logs/msmt17/agw_S50 12 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/MSMT17/bagtricks_R101-ibn.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-bagtricks.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | DEPTH: 101x 6 | WITH_IBN: True 7 | 8 | DATASETS: 9 | NAMES: ("MSMT17",) 10 | TESTS: ("MSMT17",) 11 | 12 | OUTPUT_DIR: logs/msmt17/bagtricks_R101-ibn 13 | 14 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/MSMT17/bagtricks_R50-ibn.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-bagtricks.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | WITH_IBN: True 6 | 7 | DATASETS: 8 | NAMES: ("MSMT17",) 9 | TESTS: ("MSMT17",) 10 | 11 | OUTPUT_DIR: logs/msmt17/bagtricks_R50-ibn 12 | 13 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/MSMT17/bagtricks_R50.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-bagtricks.yml 2 | 3 | DATASETS: 4 | NAMES: ("MSMT17",) 5 | TESTS: ("MSMT17",) 6 | 7 | OUTPUT_DIR: logs/msmt17/bagtricks_R50 8 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/MSMT17/bagtricks_S50.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-bagtricks.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | NAME: build_resnest_backbone 6 | 7 | DATASETS: 8 | NAMES: ("MSMT17",) 9 | TESTS: ("MSMT17",) 10 | 11 | OUTPUT_DIR: logs/msmt17/bagtricks_S50 12 | 13 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/MSMT17/mgn_R50-ibn.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-MGN.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | WITH_IBN: True 6 | 7 | DATASETS: 8 | NAMES: ("MSMT17",) 9 | TESTS: ("MSMT17",) 10 | 11 | OUTPUT_DIR: logs/msmt17/mgn_R50-ibn 12 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/MSMT17/sbs_R101-ibn.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-SBS.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | DEPTH: 101x 6 | WITH_IBN: True 7 | 8 | DATASETS: 9 | NAMES: ("MSMT17",) 10 | TESTS: ("MSMT17",) 11 | 12 | OUTPUT_DIR: logs/msmt17/sbs_R101-ibn 13 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/MSMT17/sbs_R50-ibn.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-SBS.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | WITH_IBN: True 6 | 7 | DATASETS: 8 | NAMES: ("MSMT17",) 9 | TESTS: ("MSMT17",) 10 | 11 | OUTPUT_DIR: logs/msmt17/sbs_R50-ibn 12 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/MSMT17/sbs_R50.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-SBS.yml 2 | 3 | DATASETS: 4 | NAMES: ("MSMT17",) 5 | TESTS: ("MSMT17",) 6 | 7 | OUTPUT_DIR: logs/msmt17/sbs_R50 8 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/MSMT17/sbs_S50.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-SBS.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | NAME: build_resnest_backbone 6 | 7 | DATASETS: 8 | NAMES: ("MSMT17",) 9 | TESTS: ("MSMT17",) 10 | 11 | OUTPUT_DIR: logs/msmt17/sbs_S50 12 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/Market1501/AGW_R101-ibn.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-AGW.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | DEPTH: 101x 6 | WITH_IBN: True 7 | 8 | DATASETS: 9 | NAMES: ("Market1501",) 10 | TESTS: ("Market1501",) 11 | 12 | OUTPUT_DIR: logs/market1501/agw_R101-ibn 13 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/Market1501/AGW_R50-ibn.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-AGW.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | WITH_IBN: True 6 | 7 | DATASETS: 8 | NAMES: ("Market1501",) 9 | TESTS: ("Market1501",) 10 | 11 | OUTPUT_DIR: logs/market1501/agw_R50-ibn 12 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/Market1501/AGW_R50.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-AGW.yml 2 | 3 | DATASETS: 4 | NAMES: ("Market1501",) 5 | TESTS: ("Market1501",) 6 | 7 | OUTPUT_DIR: logs/market1501/agw_R50 8 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/Market1501/AGW_S50.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-AGW.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | NAME: build_resnest_backbone 6 | 7 | DATASETS: 8 | NAMES: ("Market1501",) 9 | TESTS: ("Market1501",) 10 | 11 | OUTPUT_DIR: logs/market1501/agw_S50 12 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/Market1501/bagtricks_R101-ibn.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-bagtricks.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | DEPTH: 101x 6 | WITH_IBN: True 7 | 8 | DATASETS: 9 | NAMES: ("Market1501",) 10 | TESTS: ("Market1501",) 11 | 12 | OUTPUT_DIR: logs/market1501/bagtricks_R101-ibn 13 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/Market1501/bagtricks_R50-ibn.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-bagtricks.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | WITH_IBN: True 6 | 7 | DATASETS: 8 | NAMES: ("Market1501",) 9 | TESTS: ("Market1501",) 10 | 11 | OUTPUT_DIR: logs/market1501/bagtricks_R50-ibn 12 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/Market1501/bagtricks_R50.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-bagtricks.yml 2 | 3 | DATASETS: 4 | NAMES: ("Market1501",) 5 | TESTS: ("Market1501",) 6 | 7 | OUTPUT_DIR: logs/market1501/bagtricks_R50 8 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/Market1501/bagtricks_S50.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-bagtricks.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | NAME: build_resnest_backbone 6 | 7 | DATASETS: 8 | NAMES: ("Market1501",) 9 | TESTS: ("Market1501",) 10 | 11 | OUTPUT_DIR: logs/market1501/bagtricks_S50 12 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/Market1501/mgn_R50-ibn.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-MGN.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | WITH_IBN: True 6 | 7 | DATASETS: 8 | NAMES: ("Market1501",) 9 | TESTS: ("Market1501",) 10 | 11 | OUTPUT_DIR: logs/market1501/mgn_R50-ibn 12 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/Market1501/sbs_R101-ibn.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-SBS.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | DEPTH: 101x 6 | WITH_IBN: True 7 | 8 | DATASETS: 9 | NAMES: ("Market1501",) 10 | TESTS: ("Market1501",) 11 | 12 | OUTPUT_DIR: logs/market1501/sbs_R101-ibn 13 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/Market1501/sbs_R50-ibn.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-SBS.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | WITH_IBN: True 6 | 7 | DATASETS: 8 | NAMES: ("Market1501",) 9 | TESTS: ("Market1501",) 10 | 11 | OUTPUT_DIR: logs/market1501/sbs_R50-ibn 12 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/Market1501/sbs_R50.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-SBS.yml 2 | 3 | DATASETS: 4 | NAMES: ("Market1501",) 5 | TESTS: ("Market1501",) 6 | 7 | OUTPUT_DIR: logs/market1501/sbs_R50 8 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/Market1501/sbs_S50.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-SBS.yml 2 | 3 | MODEL: 4 | BACKBONE: 5 | NAME: build_resnest_backbone 6 | 7 | DATASETS: 8 | NAMES: ("Market1501",) 9 | TESTS: ("Market1501",) 10 | 11 | OUTPUT_DIR: logs/market1501/sbs_S50 12 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/VERIWild/bagtricks_R50-ibn.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-bagtricks.yml 2 | 3 | INPUT: 4 | SIZE_TRAIN: [256, 256] 5 | SIZE_TEST: [256, 256] 6 | 7 | MODEL: 8 | BACKBONE: 9 | WITH_IBN: True 10 | 11 | HEADS: 12 | POOL_LAYER: GeneralizedMeanPooling 13 | 14 | LOSSES: 15 | TRI: 16 | HARD_MINING: False 17 | MARGIN: 0.0 18 | 19 | DATASETS: 20 | NAMES: ("VeRiWild",) 21 | TESTS: ("SmallVeRiWild", "MediumVeRiWild", "LargeVeRiWild",) 22 | 23 | SOLVER: 24 | IMS_PER_BATCH: 512 # 512 For 4 GPUs 25 | MAX_EPOCH: 120 26 | STEPS: [30, 70, 90] 27 | WARMUP_ITERS: 5000 28 | 29 | CHECKPOINT_PERIOD: 20 30 | 31 | TEST: 32 | EVAL_PERIOD: 10 33 | IMS_PER_BATCH: 128 34 | 35 | OUTPUT_DIR: logs/veriwild/bagtricks_R50-ibn_4gpu 36 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/VeRi/sbs_R50-ibn.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-SBS.yml 2 | 3 | INPUT: 4 | SIZE_TRAIN: [256, 256] 5 | SIZE_TEST: [256, 256] 6 | 7 | MODEL: 8 | BACKBONE: 9 | WITH_IBN: True 10 | WITH_NL: True 11 | 12 | SOLVER: 13 | OPT: SGD 14 | BASE_LR: 0.01 15 | ETA_MIN_LR: 7.7e-5 16 | 17 | IMS_PER_BATCH: 64 18 | MAX_EPOCH: 60 19 | WARMUP_ITERS: 3000 20 | FREEZE_ITERS: 3000 21 | 22 | CHECKPOINT_PERIOD: 10 23 | 24 | DATASETS: 25 | NAMES: ("VeRi",) 26 | TESTS: ("VeRi",) 27 | 28 | DATALOADER: 29 | SAMPLER_TRAIN: BalancedIdentitySampler 30 | 31 | TEST: 32 | EVAL_PERIOD: 10 33 | IMS_PER_BATCH: 256 34 | 35 | OUTPUT_DIR: logs/veri/sbs_R50-ibn 36 | -------------------------------------------------------------------------------- /pytorch/fast_reid/configs/VehicleID/bagtricks_R50-ibn.yml: -------------------------------------------------------------------------------- 1 | _BASE_: ../Base-bagtricks.yml 2 | 3 | INPUT: 4 | SIZE_TRAIN: [256, 256] 5 | SIZE_TEST: [256, 256] 6 | 7 | MODEL: 8 | BACKBONE: 9 | WITH_IBN: True 10 | HEADS: 11 | POOL_LAYER: GeneralizedMeanPooling 12 | 13 | LOSSES: 14 | TRI: 15 | HARD_MINING: False 16 | MARGIN: 0.0 17 | 18 | DATASETS: 19 | NAMES: ("VehicleID",) 20 | TESTS: ("SmallVehicleID", "MediumVehicleID", "LargeVehicleID",) 21 | 22 | SOLVER: 23 | BIAS_LR_FACTOR: 1. 24 | 25 | IMS_PER_BATCH: 512 26 | MAX_EPOCH: 60 27 | STEPS: [30, 50] 28 | WARMUP_ITERS: 2000 29 | 30 | CHECKPOINT_PERIOD: 20 31 | 32 | TEST: 33 | EVAL_PERIOD: 20 34 | IMS_PER_BATCH: 128 35 | 36 | OUTPUT_DIR: logs/vehicleid/bagtricks_R50-ibn_4gpu 37 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/__init__.py: -------------------------------------------------------------------------------- 1 | # encoding: utf-8 2 | """ 3 | @author: liaoxingyu 4 | @contact: sherlockliao01@gmail.com 5 | """ 6 | 7 | 8 | __version__ = "1.3" 9 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/config/__init__.py: -------------------------------------------------------------------------------- 1 | # encoding: utf-8 2 | """ 3 | @author: l1aoxingyu 4 | @contact: sherlockliao01@gmail.com 5 | """ 6 | 7 | from .config import CfgNode, get_cfg, global_cfg, set_global_cfg, configurable 8 | 9 | __all__ = [ 10 | 'CfgNode', 11 | 'get_cfg', 12 | 'global_cfg', 13 | 'set_global_cfg', 14 | 'configurable' 15 | ] 16 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/data/__init__.py: -------------------------------------------------------------------------------- 1 | # encoding: utf-8 2 | """ 3 | @author: sherlock 4 | @contact: sherlockliao01@gmail.com 5 | """ 6 | 7 | from . import transforms # isort:skip 8 | from .build import ( 9 | build_reid_train_loader, 10 | build_reid_test_loader 11 | ) 12 | from .common import CommDataset 13 | 14 | # ensure the builtin datasets are registered 15 | from . import datasets, samplers # isort:skip 16 | 17 | __all__ = [k for k in globals().keys() if not k.startswith("_")] 18 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/data/samplers/__init__.py: -------------------------------------------------------------------------------- 1 | # encoding: utf-8 2 | """ 3 | @author: liaoxingyu 4 | @contact: sherlockliao01@gmail.com 5 | """ 6 | 7 | from .triplet_sampler import BalancedIdentitySampler, NaiveIdentitySampler, SetReWeightSampler 8 | from .data_sampler import TrainingSampler, InferenceSampler 9 | from .imbalance_sampler import ImbalancedDatasetSampler 10 | 11 | __all__ = [ 12 | "BalancedIdentitySampler", 13 | "NaiveIdentitySampler", 14 | "SetReWeightSampler", 15 | "TrainingSampler", 16 | "InferenceSampler", 17 | "ImbalancedDatasetSampler", 18 | ] 19 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/data/transforms/__init__.py: -------------------------------------------------------------------------------- 1 | # encoding: utf-8 2 | """ 3 | @author: sherlock 4 | @contact: sherlockliao01@gmail.com 5 | """ 6 | 7 | from .autoaugment import AutoAugment 8 | from .build import build_transforms 9 | from .transforms import * 10 | 11 | __all__ = [k for k in globals().keys() if not k.startswith("_")] 12 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/engine/__init__.py: -------------------------------------------------------------------------------- 1 | # encoding: utf-8 2 | """ 3 | @author: liaoxingyu 4 | @contact: sherlockliao01@gmail.com 5 | """ 6 | from .train_loop import * 7 | 8 | __all__ = [k for k in globals().keys() if not k.startswith("_")] 9 | 10 | 11 | # prefer to let hooks and defaults live in separate namespaces (therefore not in __all__) 12 | # but still make them available here 13 | from .hooks import * 14 | from .defaults import * 15 | from .launch import * 16 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/evaluation/__init__.py: -------------------------------------------------------------------------------- 1 | from .evaluator import DatasetEvaluator, inference_context, inference_on_dataset 2 | from .rank import evaluate_rank 3 | from .reid_evaluation import ReidEvaluator 4 | from .clas_evaluator import ClasEvaluator 5 | from .roc import evaluate_roc 6 | from .testing import print_csv_format, verify_results 7 | 8 | __all__ = [k for k in globals().keys() if not k.startswith("_")] 9 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/evaluation/rank_cylib/Makefile: -------------------------------------------------------------------------------- 1 | all: 2 | python3 setup.py build_ext --inplace 3 | rm -rf build 4 | python3 test_cython.py 5 | clean: 6 | rm -rf build 7 | rm -f rank_cy.c *.so 8 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/evaluation/rank_cylib/__init__.py: -------------------------------------------------------------------------------- 1 | # encoding: utf-8 2 | """ 3 | @author: liaoxingyu 4 | @contact: sherlockliao01@gmail.com 5 | """ -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/evaluation/rank_cylib/setup.py: -------------------------------------------------------------------------------- 1 | from distutils.core import setup 2 | from distutils.extension import Extension 3 | 4 | import numpy as np 5 | from Cython.Build import cythonize 6 | 7 | 8 | def numpy_include(): 9 | try: 10 | numpy_include = np.get_include() 11 | except AttributeError: 12 | numpy_include = np.get_numpy_include() 13 | return numpy_include 14 | 15 | 16 | ext_modules = [ 17 | Extension( 18 | 'rank_cy', 19 | ['rank_cy.pyx'], 20 | include_dirs=[numpy_include()], 21 | ), 22 | Extension( 23 | 'roc_cy', 24 | ['roc_cy.pyx'], 25 | include_dirs=[numpy_include()], 26 | ) 27 | ] 28 | 29 | setup( 30 | name='Cython-based reid evaluation code', 31 | ext_modules=cythonize(ext_modules) 32 | ) 33 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/layers/__init__.py: -------------------------------------------------------------------------------- 1 | # encoding: utf-8 2 | """ 3 | @author: liaoxingyu 4 | @contact: sherlockliao01@gmail.com 5 | """ 6 | 7 | from .activation import * 8 | from .batch_norm import * 9 | from .context_block import ContextBlock 10 | from .drop import DropPath, DropBlock2d, drop_block_2d, drop_path 11 | from .frn import FRN, TLU 12 | from .gather_layer import GatherLayer 13 | from .helpers import to_ntuple, to_2tuple, to_3tuple, to_4tuple, make_divisible 14 | from .non_local import Non_local 15 | from .se_layer import SELayer 16 | from .splat import SplAtConv2d, DropBlock2D 17 | from .weight_init import ( 18 | trunc_normal_, variance_scaling_, lecun_normal_, weights_init_kaiming, weights_init_classifier 19 | ) 20 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/layers/se_layer.py: -------------------------------------------------------------------------------- 1 | # encoding: utf-8 2 | """ 3 | @author: liaoxingyu 4 | @contact: sherlockliao01@gmail.com 5 | """ 6 | 7 | from torch import nn 8 | 9 | 10 | class SELayer(nn.Module): 11 | def __init__(self, channel, reduction=16): 12 | super(SELayer, self).__init__() 13 | self.avg_pool = nn.AdaptiveAvgPool2d(1) 14 | self.fc = nn.Sequential( 15 | nn.Linear(channel, int(channel / reduction), bias=False), 16 | nn.ReLU(inplace=True), 17 | nn.Linear(int(channel / reduction), channel, bias=False), 18 | nn.Sigmoid() 19 | ) 20 | 21 | def forward(self, x): 22 | b, c, _, _ = x.size() 23 | y = self.avg_pool(x).view(b, c) 24 | y = self.fc(y).view(b, c, 1, 1) 25 | return x * y.expand_as(x) 26 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/__init__.py: -------------------------------------------------------------------------------- 1 | # encoding: utf-8 2 | """ 3 | @author: sherlock 4 | @contact: sherlockliao01@gmail.com 5 | """ 6 | 7 | from . import losses 8 | from .backbones import ( 9 | BACKBONE_REGISTRY, 10 | build_resnet_backbone, 11 | build_backbone, 12 | ) 13 | from .heads import ( 14 | REID_HEADS_REGISTRY, 15 | build_heads, 16 | EmbeddingHead, 17 | ) 18 | from .meta_arch import ( 19 | build_model, 20 | META_ARCH_REGISTRY, 21 | ) 22 | 23 | __all__ = [k for k in globals().keys() if not k.startswith("_")] -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/__init__.py: -------------------------------------------------------------------------------- 1 | # encoding: utf-8 2 | """ 3 | @author: liaoxingyu 4 | @contact: sherlockliao01@gmail.com 5 | """ 6 | 7 | from .build import build_backbone, BACKBONE_REGISTRY 8 | 9 | from .resnet import build_resnet_backbone 10 | from .osnet import build_osnet_backbone 11 | from .resnest import build_resnest_backbone 12 | from .resnext import build_resnext_backbone 13 | from .regnet import build_regnet_backbone, build_effnet_backbone 14 | from .shufflenet import build_shufflenetv2_backbone 15 | from .mobilenet import build_mobilenetv2_backbone 16 | from .repvgg import build_repvgg_backbone 17 | from .vision_transformer import build_vit_backbone 18 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/__init__.py: -------------------------------------------------------------------------------- 1 | 2 | 3 | from .regnet import build_regnet_backbone 4 | from .effnet import build_effnet_backbone 5 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/effnet/EN-B0_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: effnet 3 | NUM_CLASSES: 1000 4 | EN: 5 | STEM_W: 32 6 | STRIDES: [1, 2, 2, 2, 1, 2, 1] 7 | DEPTHS: [1, 2, 2, 3, 3, 4, 1] 8 | WIDTHS: [16, 24, 40, 80, 112, 192, 320] 9 | EXP_RATIOS: [1, 6, 6, 6, 6, 6, 6] 10 | KERNELS: [3, 3, 5, 3, 5, 5, 3] 11 | HEAD_W: 1280 12 | OPTIM: 13 | LR_POLICY: cos 14 | BASE_LR: 0.4 15 | MAX_EPOCH: 100 16 | MOMENTUM: 0.9 17 | WEIGHT_DECAY: 1e-5 18 | TRAIN: 19 | DATASET: imagenet 20 | IM_SIZE: 224 21 | BATCH_SIZE: 256 22 | TEST: 23 | DATASET: imagenet 24 | IM_SIZE: 256 25 | BATCH_SIZE: 200 26 | NUM_GPUS: 8 27 | OUT_DIR: . 28 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/effnet/EN-B1_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: effnet 3 | NUM_CLASSES: 1000 4 | EN: 5 | STEM_W: 32 6 | STRIDES: [1, 2, 2, 2, 1, 2, 1] 7 | DEPTHS: [2, 3, 3, 4, 4, 5, 2] 8 | WIDTHS: [16, 24, 40, 80, 112, 192, 320] 9 | EXP_RATIOS: [1, 6, 6, 6, 6, 6, 6] 10 | KERNELS: [3, 3, 5, 3, 5, 5, 3] 11 | HEAD_W: 1280 12 | OPTIM: 13 | LR_POLICY: cos 14 | BASE_LR: 0.4 15 | MAX_EPOCH: 100 16 | MOMENTUM: 0.9 17 | WEIGHT_DECAY: 1e-5 18 | TRAIN: 19 | DATASET: imagenet 20 | IM_SIZE: 240 21 | BATCH_SIZE: 256 22 | TEST: 23 | DATASET: imagenet 24 | IM_SIZE: 274 25 | BATCH_SIZE: 200 26 | NUM_GPUS: 8 27 | OUT_DIR: . 28 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/effnet/EN-B2_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: effnet 3 | NUM_CLASSES: 1000 4 | EN: 5 | STEM_W: 32 6 | STRIDES: [1, 2, 2, 2, 1, 2, 1] 7 | DEPTHS: [2, 3, 3, 4, 4, 5, 2] 8 | WIDTHS: [16, 24, 48, 88, 120, 208, 352] 9 | EXP_RATIOS: [1, 6, 6, 6, 6, 6, 6] 10 | KERNELS: [3, 3, 5, 3, 5, 5, 3] 11 | HEAD_W: 1408 12 | OPTIM: 13 | LR_POLICY: cos 14 | BASE_LR: 0.4 15 | MAX_EPOCH: 100 16 | MOMENTUM: 0.9 17 | WEIGHT_DECAY: 1e-5 18 | TRAIN: 19 | DATASET: imagenet 20 | IM_SIZE: 260 21 | BATCH_SIZE: 256 22 | TEST: 23 | DATASET: imagenet 24 | IM_SIZE: 298 25 | BATCH_SIZE: 200 26 | NUM_GPUS: 8 27 | OUT_DIR: . 28 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/effnet/EN-B3_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: effnet 3 | NUM_CLASSES: 1000 4 | EN: 5 | STEM_W: 40 6 | STRIDES: [1, 2, 2, 2, 1, 2, 1] 7 | DEPTHS: [2, 3, 3, 5, 5, 6, 2] 8 | WIDTHS: [24, 32, 48, 96, 136, 232, 384] 9 | EXP_RATIOS: [1, 6, 6, 6, 6, 6, 6] 10 | KERNELS: [3, 3, 5, 3, 5, 5, 3] 11 | HEAD_W: 1536 12 | OPTIM: 13 | LR_POLICY: cos 14 | BASE_LR: 0.4 15 | MAX_EPOCH: 100 16 | MOMENTUM: 0.9 17 | WEIGHT_DECAY: 1e-5 18 | TRAIN: 19 | DATASET: imagenet 20 | IM_SIZE: 300 21 | BATCH_SIZE: 256 22 | TEST: 23 | DATASET: imagenet 24 | IM_SIZE: 342 25 | BATCH_SIZE: 200 26 | NUM_GPUS: 8 27 | OUT_DIR: . 28 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/effnet/EN-B4_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: effnet 3 | NUM_CLASSES: 1000 4 | EN: 5 | STEM_W: 48 6 | STRIDES: [1, 2, 2, 2, 1, 2, 1] 7 | DEPTHS: [2, 4, 4, 6, 6, 8, 2] 8 | WIDTHS: [24, 32, 56, 112, 160, 272, 448] 9 | EXP_RATIOS: [1, 6, 6, 6, 6, 6, 6] 10 | KERNELS: [3, 3, 5, 3, 5, 5, 3] 11 | HEAD_W: 1792 12 | OPTIM: 13 | LR_POLICY: cos 14 | BASE_LR: 0.2 15 | MAX_EPOCH: 100 16 | MOMENTUM: 0.9 17 | WEIGHT_DECAY: 1e-5 18 | TRAIN: 19 | DATASET: imagenet 20 | IM_SIZE: 380 21 | BATCH_SIZE: 128 22 | TEST: 23 | DATASET: imagenet 24 | IM_SIZE: 434 25 | BATCH_SIZE: 104 26 | NUM_GPUS: 8 27 | OUT_DIR: . 28 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/effnet/EN-B5_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: effnet 3 | NUM_CLASSES: 1000 4 | EN: 5 | STEM_W: 48 6 | STRIDES: [1, 2, 2, 2, 1, 2, 1] 7 | DEPTHS: [3, 5, 5, 7, 7, 9, 3] 8 | WIDTHS: [24, 40, 64, 128, 176, 304, 512] 9 | EXP_RATIOS: [1, 6, 6, 6, 6, 6, 6] 10 | KERNELS: [3, 3, 5, 3, 5, 5, 3] 11 | HEAD_W: 2048 12 | OPTIM: 13 | LR_POLICY: cos 14 | BASE_LR: 0.1 15 | MAX_EPOCH: 100 16 | MOMENTUM: 0.9 17 | WEIGHT_DECAY: 1e-5 18 | TRAIN: 19 | DATASET: imagenet 20 | IM_SIZE: 456 21 | BATCH_SIZE: 64 22 | TEST: 23 | DATASET: imagenet 24 | IM_SIZE: 522 25 | BATCH_SIZE: 48 26 | NUM_GPUS: 8 27 | OUT_DIR: . 28 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/regnetx/RegNetX-1.6GF_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: regnet 3 | NUM_CLASSES: 1000 4 | REGNET: 5 | DEPTH: 18 6 | W0: 80 7 | WA: 34.01 8 | WM: 2.25 9 | GROUP_W: 24 10 | OPTIM: 11 | LR_POLICY: cos 12 | BASE_LR: 0.8 13 | MAX_EPOCH: 100 14 | MOMENTUM: 0.9 15 | WEIGHT_DECAY: 5e-5 16 | WARMUP_ITERS: 5 17 | TRAIN: 18 | DATASET: imagenet 19 | IM_SIZE: 224 20 | BATCH_SIZE: 1024 21 | TEST: 22 | DATASET: imagenet 23 | IM_SIZE: 256 24 | BATCH_SIZE: 800 25 | NUM_GPUS: 8 26 | OUT_DIR: . 27 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/regnetx/RegNetX-12GF_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: regnet 3 | NUM_CLASSES: 1000 4 | REGNET: 5 | DEPTH: 19 6 | W0: 168 7 | WA: 73.36 8 | WM: 2.37 9 | GROUP_W: 112 10 | OPTIM: 11 | LR_POLICY: cos 12 | BASE_LR: 0.4 13 | MAX_EPOCH: 100 14 | MOMENTUM: 0.9 15 | WEIGHT_DECAY: 5e-5 16 | WARMUP_ITERS: 5 17 | TRAIN: 18 | DATASET: imagenet 19 | IM_SIZE: 224 20 | BATCH_SIZE: 512 21 | TEST: 22 | DATASET: imagenet 23 | IM_SIZE: 256 24 | BATCH_SIZE: 400 25 | NUM_GPUS: 8 26 | OUT_DIR: . 27 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/regnetx/RegNetX-16GF_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: regnet 3 | NUM_CLASSES: 1000 4 | REGNET: 5 | DEPTH: 22 6 | W0: 216 7 | WA: 55.59 8 | WM: 2.1 9 | GROUP_W: 128 10 | OPTIM: 11 | LR_POLICY: cos 12 | BASE_LR: 0.4 13 | MAX_EPOCH: 100 14 | MOMENTUM: 0.9 15 | WEIGHT_DECAY: 5e-5 16 | WARMUP_ITERS: 5 17 | TRAIN: 18 | DATASET: imagenet 19 | IM_SIZE: 224 20 | BATCH_SIZE: 512 21 | TEST: 22 | DATASET: imagenet 23 | IM_SIZE: 256 24 | BATCH_SIZE: 400 25 | NUM_GPUS: 8 26 | OUT_DIR: . 27 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/regnetx/RegNetX-200MF_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: regnet 3 | NUM_CLASSES: 1000 4 | REGNET: 5 | DEPTH: 13 6 | W0: 24 7 | WA: 36.44 8 | WM: 2.49 9 | GROUP_W: 8 10 | OPTIM: 11 | LR_POLICY: cos 12 | BASE_LR: 0.8 13 | MAX_EPOCH: 100 14 | MOMENTUM: 0.9 15 | WEIGHT_DECAY: 5e-5 16 | WARMUP_ITERS: 5 17 | TRAIN: 18 | DATASET: imagenet 19 | IM_SIZE: 224 20 | BATCH_SIZE: 1024 21 | TEST: 22 | DATASET: imagenet 23 | IM_SIZE: 256 24 | BATCH_SIZE: 800 25 | NUM_GPUS: 8 26 | OUT_DIR: . 27 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/regnetx/RegNetX-3.2GF_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: regnet 3 | NUM_CLASSES: 1000 4 | REGNET: 5 | DEPTH: 25 6 | W0: 88 7 | WA: 26.31 8 | WM: 2.25 9 | GROUP_W: 48 10 | OPTIM: 11 | LR_POLICY: cos 12 | BASE_LR: 0.4 13 | MAX_EPOCH: 100 14 | MOMENTUM: 0.9 15 | WEIGHT_DECAY: 5e-5 16 | WARMUP_ITERS: 5 17 | TRAIN: 18 | DATASET: imagenet 19 | IM_SIZE: 224 20 | BATCH_SIZE: 512 21 | TEST: 22 | DATASET: imagenet 23 | IM_SIZE: 256 24 | BATCH_SIZE: 400 25 | NUM_GPUS: 8 26 | OUT_DIR: . 27 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/regnetx/RegNetX-32GF_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: regnet 3 | NUM_CLASSES: 1000 4 | REGNET: 5 | DEPTH: 23 6 | W0: 320 7 | WA: 69.86 8 | WM: 2.0 9 | GROUP_W: 168 10 | OPTIM: 11 | LR_POLICY: cos 12 | BASE_LR: 0.2 13 | MAX_EPOCH: 100 14 | MOMENTUM: 0.9 15 | WEIGHT_DECAY: 5e-5 16 | WARMUP_ITERS: 5 17 | TRAIN: 18 | DATASET: imagenet 19 | IM_SIZE: 224 20 | BATCH_SIZE: 256 21 | TEST: 22 | DATASET: imagenet 23 | IM_SIZE: 256 24 | BATCH_SIZE: 200 25 | NUM_GPUS: 8 26 | OUT_DIR: . 27 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/regnetx/RegNetX-4.0GF_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: regnet 3 | NUM_CLASSES: 1000 4 | REGNET: 5 | DEPTH: 23 6 | W0: 96 7 | WA: 38.65 8 | WM: 2.43 9 | GROUP_W: 40 10 | OPTIM: 11 | LR_POLICY: cos 12 | BASE_LR: 0.4 13 | MAX_EPOCH: 100 14 | MOMENTUM: 0.9 15 | WEIGHT_DECAY: 5e-5 16 | WARMUP_ITERS: 5 17 | TRAIN: 18 | DATASET: imagenet 19 | IM_SIZE: 224 20 | BATCH_SIZE: 512 21 | TEST: 22 | DATASET: imagenet 23 | IM_SIZE: 256 24 | BATCH_SIZE: 400 25 | NUM_GPUS: 8 26 | OUT_DIR: . 27 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/regnetx/RegNetX-400MF_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: regnet 3 | NUM_CLASSES: 1000 4 | REGNET: 5 | DEPTH: 22 6 | W0: 24 7 | WA: 24.48 8 | WM: 2.54 9 | GROUP_W: 16 10 | OPTIM: 11 | LR_POLICY: cos 12 | BASE_LR: 0.8 13 | MAX_EPOCH: 100 14 | MOMENTUM: 0.9 15 | WEIGHT_DECAY: 5e-5 16 | WARMUP_ITERS: 5 17 | TRAIN: 18 | DATASET: imagenet 19 | IM_SIZE: 224 20 | BATCH_SIZE: 1024 21 | TEST: 22 | DATASET: imagenet 23 | IM_SIZE: 256 24 | BATCH_SIZE: 800 25 | NUM_GPUS: 8 26 | OUT_DIR: . 27 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/regnetx/RegNetX-6.4GF_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: regnet 3 | NUM_CLASSES: 1000 4 | REGNET: 5 | DEPTH: 17 6 | W0: 184 7 | WA: 60.83 8 | WM: 2.07 9 | GROUP_W: 56 10 | OPTIM: 11 | LR_POLICY: cos 12 | BASE_LR: 0.4 13 | MAX_EPOCH: 100 14 | MOMENTUM: 0.9 15 | WEIGHT_DECAY: 5e-5 16 | WARMUP_ITERS: 5 17 | TRAIN: 18 | DATASET: imagenet 19 | IM_SIZE: 224 20 | BATCH_SIZE: 512 21 | TEST: 22 | DATASET: imagenet 23 | IM_SIZE: 256 24 | BATCH_SIZE: 400 25 | NUM_GPUS: 8 26 | OUT_DIR: . 27 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/regnetx/RegNetX-600MF_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: regnet 3 | NUM_CLASSES: 1000 4 | REGNET: 5 | DEPTH: 16 6 | W0: 48 7 | WA: 36.97 8 | WM: 2.24 9 | GROUP_W: 24 10 | OPTIM: 11 | LR_POLICY: cos 12 | BASE_LR: 0.8 13 | MAX_EPOCH: 100 14 | MOMENTUM: 0.9 15 | WEIGHT_DECAY: 5e-5 16 | WARMUP_ITERS: 5 17 | TRAIN: 18 | DATASET: imagenet 19 | IM_SIZE: 224 20 | BATCH_SIZE: 1024 21 | TEST: 22 | DATASET: imagenet 23 | IM_SIZE: 256 24 | BATCH_SIZE: 800 25 | NUM_GPUS: 8 26 | OUT_DIR: . 27 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/regnetx/RegNetX-8.0GF_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: regnet 3 | NUM_CLASSES: 1000 4 | REGNET: 5 | DEPTH: 23 6 | W0: 80 7 | WA: 49.56 8 | WM: 2.88 9 | GROUP_W: 120 10 | OPTIM: 11 | LR_POLICY: cos 12 | BASE_LR: 0.4 13 | MAX_EPOCH: 100 14 | MOMENTUM: 0.9 15 | WEIGHT_DECAY: 5e-5 16 | WARMUP_ITERS: 5 17 | TRAIN: 18 | DATASET: imagenet 19 | IM_SIZE: 224 20 | BATCH_SIZE: 512 21 | TEST: 22 | DATASET: imagenet 23 | IM_SIZE: 256 24 | BATCH_SIZE: 400 25 | NUM_GPUS: 8 26 | OUT_DIR: . 27 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/regnetx/RegNetX-800MF_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: regnet 3 | NUM_CLASSES: 1000 4 | REGNET: 5 | DEPTH: 16 6 | W0: 56 7 | WA: 35.73 8 | WM: 2.28 9 | GROUP_W: 16 10 | OPTIM: 11 | LR_POLICY: cos 12 | BASE_LR: 0.8 13 | MAX_EPOCH: 100 14 | MOMENTUM: 0.9 15 | WEIGHT_DECAY: 5e-5 16 | WARMUP_ITERS: 5 17 | TRAIN: 18 | DATASET: imagenet 19 | IM_SIZE: 224 20 | BATCH_SIZE: 1024 21 | TEST: 22 | DATASET: imagenet 23 | IM_SIZE: 256 24 | BATCH_SIZE: 800 25 | NUM_GPUS: 8 26 | OUT_DIR: . 27 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/regnety/RegNetY-1.6GF_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: regnet 3 | NUM_CLASSES: 1000 4 | REGNET: 5 | SE_ON: True 6 | DEPTH: 27 7 | W0: 48 8 | WA: 20.71 9 | WM: 2.65 10 | GROUP_W: 24 11 | OPTIM: 12 | LR_POLICY: cos 13 | BASE_LR: 0.8 14 | MAX_EPOCH: 100 15 | MOMENTUM: 0.9 16 | WEIGHT_DECAY: 5e-5 17 | WARMUP_ITERS: 5 18 | TRAIN: 19 | DATASET: imagenet 20 | IM_SIZE: 224 21 | BATCH_SIZE: 1024 22 | TEST: 23 | DATASET: imagenet 24 | IM_SIZE: 256 25 | BATCH_SIZE: 800 26 | NUM_GPUS: 8 27 | OUT_DIR: . 28 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/regnety/RegNetY-12GF_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: regnet 3 | NUM_CLASSES: 1000 4 | REGNET: 5 | SE_ON: True 6 | DEPTH: 19 7 | W0: 168 8 | WA: 73.36 9 | WM: 2.37 10 | GROUP_W: 112 11 | OPTIM: 12 | LR_POLICY: cos 13 | BASE_LR: 0.4 14 | MAX_EPOCH: 100 15 | MOMENTUM: 0.9 16 | WEIGHT_DECAY: 5e-5 17 | WARMUP_ITERS: 5 18 | TRAIN: 19 | DATASET: imagenet 20 | IM_SIZE: 224 21 | BATCH_SIZE: 512 22 | TEST: 23 | DATASET: imagenet 24 | IM_SIZE: 256 25 | BATCH_SIZE: 400 26 | NUM_GPUS: 8 27 | OUT_DIR: . 28 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/regnety/RegNetY-16GF_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: regnet 3 | NUM_CLASSES: 1000 4 | REGNET: 5 | SE_ON: True 6 | DEPTH: 18 7 | W0: 200 8 | WA: 106.23 9 | WM: 2.48 10 | GROUP_W: 112 11 | OPTIM: 12 | LR_POLICY: cos 13 | BASE_LR: 0.2 14 | MAX_EPOCH: 100 15 | MOMENTUM: 0.9 16 | WEIGHT_DECAY: 5e-5 17 | WARMUP_ITERS: 5 18 | TRAIN: 19 | DATASET: imagenet 20 | IM_SIZE: 224 21 | BATCH_SIZE: 256 22 | TEST: 23 | DATASET: imagenet 24 | IM_SIZE: 256 25 | BATCH_SIZE: 200 26 | NUM_GPUS: 8 27 | OUT_DIR: . 28 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/regnety/RegNetY-200MF_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: regnet 3 | NUM_CLASSES: 1000 4 | REGNET: 5 | SE_ON: True 6 | DEPTH: 13 7 | W0: 24 8 | WA: 36.44 9 | WM: 2.49 10 | GROUP_W: 8 11 | OPTIM: 12 | LR_POLICY: cos 13 | BASE_LR: 0.8 14 | MAX_EPOCH: 100 15 | MOMENTUM: 0.9 16 | WEIGHT_DECAY: 5e-5 17 | TRAIN: 18 | DATASET: imagenet 19 | IM_SIZE: 224 20 | BATCH_SIZE: 1024 21 | TEST: 22 | DATASET: imagenet 23 | IM_SIZE: 256 24 | BATCH_SIZE: 800 25 | NUM_GPUS: 8 26 | OUT_DIR: . 27 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/regnety/RegNetY-3.2GF_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: regnet 3 | NUM_CLASSES: 1000 4 | REGNET: 5 | SE_ON: True 6 | DEPTH: 21 7 | W0: 80 8 | WA: 42.63 9 | WM: 2.66 10 | GROUP_W: 24 11 | OPTIM: 12 | LR_POLICY: cos 13 | BASE_LR: 0.4 14 | MAX_EPOCH: 100 15 | MOMENTUM: 0.9 16 | WEIGHT_DECAY: 5e-5 17 | WARMUP_ITERS: 5 18 | TRAIN: 19 | DATASET: imagenet 20 | IM_SIZE: 224 21 | BATCH_SIZE: 512 22 | TEST: 23 | DATASET: imagenet 24 | IM_SIZE: 256 25 | BATCH_SIZE: 400 26 | NUM_GPUS: 8 27 | OUT_DIR: . 28 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/regnety/RegNetY-32GF_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: regnet 3 | NUM_CLASSES: 1000 4 | REGNET: 5 | SE_ON: True 6 | DEPTH: 20 7 | W0: 232 8 | WA: 115.89 9 | WM: 2.53 10 | GROUP_W: 232 11 | OPTIM: 12 | LR_POLICY: cos 13 | BASE_LR: 0.2 14 | MAX_EPOCH: 100 15 | MOMENTUM: 0.9 16 | WEIGHT_DECAY: 5e-5 17 | WARMUP_ITERS: 5 18 | TRAIN: 19 | DATASET: imagenet 20 | IM_SIZE: 224 21 | BATCH_SIZE: 256 22 | TEST: 23 | DATASET: imagenet 24 | IM_SIZE: 256 25 | BATCH_SIZE: 200 26 | NUM_GPUS: 8 27 | OUT_DIR: . 28 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/regnety/RegNetY-4.0GF_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: regnet 3 | NUM_CLASSES: 1000 4 | REGNET: 5 | SE_ON: True 6 | DEPTH: 22 7 | W0: 96 8 | WA: 31.41 9 | WM: 2.24 10 | GROUP_W: 64 11 | OPTIM: 12 | LR_POLICY: cos 13 | BASE_LR: 0.4 14 | MAX_EPOCH: 100 15 | MOMENTUM: 0.9 16 | WEIGHT_DECAY: 5e-5 17 | WARMUP_ITERS: 5 18 | TRAIN: 19 | DATASET: imagenet 20 | IM_SIZE: 224 21 | BATCH_SIZE: 512 22 | TEST: 23 | DATASET: imagenet 24 | IM_SIZE: 256 25 | BATCH_SIZE: 400 26 | NUM_GPUS: 8 27 | OUT_DIR: . 28 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/regnety/RegNetY-400MF_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: regnet 3 | NUM_CLASSES: 1000 4 | REGNET: 5 | SE_ON: True 6 | DEPTH: 16 7 | W0: 48 8 | WA: 27.89 9 | WM: 2.09 10 | GROUP_W: 8 11 | OPTIM: 12 | LR_POLICY: cos 13 | BASE_LR: 0.8 14 | MAX_EPOCH: 100 15 | MOMENTUM: 0.9 16 | WEIGHT_DECAY: 5e-5 17 | WARMUP_ITERS: 5 18 | TRAIN: 19 | DATASET: imagenet 20 | IM_SIZE: 224 21 | BATCH_SIZE: 1024 22 | TEST: 23 | DATASET: imagenet 24 | IM_SIZE: 256 25 | BATCH_SIZE: 800 26 | NUM_GPUS: 8 27 | OUT_DIR: . 28 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/regnety/RegNetY-6.4GF_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: regnet 3 | NUM_CLASSES: 1000 4 | REGNET: 5 | SE_ON: True 6 | DEPTH: 25 7 | W0: 112 8 | WA: 33.22 9 | WM: 2.27 10 | GROUP_W: 72 11 | OPTIM: 12 | LR_POLICY: cos 13 | BASE_LR: 0.4 14 | MAX_EPOCH: 100 15 | MOMENTUM: 0.9 16 | WEIGHT_DECAY: 5e-5 17 | WARMUP_ITERS: 5 18 | TRAIN: 19 | DATASET: imagenet 20 | IM_SIZE: 224 21 | BATCH_SIZE: 512 22 | TEST: 23 | DATASET: imagenet 24 | IM_SIZE: 256 25 | BATCH_SIZE: 400 26 | NUM_GPUS: 8 27 | OUT_DIR: . 28 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/regnety/RegNetY-600MF_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: regnet 3 | NUM_CLASSES: 1000 4 | REGNET: 5 | SE_ON: True 6 | DEPTH: 15 7 | W0: 48 8 | WA: 32.54 9 | WM: 2.32 10 | GROUP_W: 16 11 | OPTIM: 12 | LR_POLICY: cos 13 | BASE_LR: 0.8 14 | MAX_EPOCH: 100 15 | MOMENTUM: 0.9 16 | WEIGHT_DECAY: 5e-5 17 | WARMUP_ITERS: 5 18 | TRAIN: 19 | DATASET: imagenet 20 | IM_SIZE: 224 21 | BATCH_SIZE: 1024 22 | TEST: 23 | DATASET: imagenet 24 | IM_SIZE: 256 25 | BATCH_SIZE: 800 26 | NUM_GPUS: 8 27 | OUT_DIR: . 28 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/regnety/RegNetY-8.0GF_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: regnet 3 | NUM_CLASSES: 1000 4 | REGNET: 5 | SE_ON: true 6 | DEPTH: 17 7 | W0: 192 8 | WA: 76.82 9 | WM: 2.19 10 | GROUP_W: 56 11 | OPTIM: 12 | LR_POLICY: cos 13 | BASE_LR: 0.4 14 | MAX_EPOCH: 100 15 | MOMENTUM: 0.9 16 | WEIGHT_DECAY: 5e-5 17 | WARMUP_ITERS: 5 18 | TRAIN: 19 | DATASET: imagenet 20 | IM_SIZE: 224 21 | BATCH_SIZE: 512 22 | TEST: 23 | DATASET: imagenet 24 | IM_SIZE: 256 25 | BATCH_SIZE: 400 26 | NUM_GPUS: 8 27 | OUT_DIR: . 28 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/backbones/regnet/regnety/RegNetY-800MF_dds_8gpu.yaml: -------------------------------------------------------------------------------- 1 | MODEL: 2 | TYPE: regnet 3 | NUM_CLASSES: 1000 4 | REGNET: 5 | SE_ON: True 6 | DEPTH: 14 7 | W0: 56 8 | WA: 38.84 9 | WM: 2.4 10 | GROUP_W: 16 11 | OPTIM: 12 | LR_POLICY: cos 13 | BASE_LR: 0.8 14 | MAX_EPOCH: 100 15 | MOMENTUM: 0.9 16 | WEIGHT_DECAY: 5e-5 17 | WARMUP_ITERS: 5 18 | TRAIN: 19 | DATASET: imagenet 20 | IM_SIZE: 224 21 | BATCH_SIZE: 1024 22 | TEST: 23 | DATASET: imagenet 24 | IM_SIZE: 256 25 | BATCH_SIZE: 800 26 | NUM_GPUS: 8 27 | OUT_DIR: . 28 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/heads/__init__.py: -------------------------------------------------------------------------------- 1 | # encoding: utf-8 2 | """ 3 | @author: liaoxingyu 4 | @contact: sherlockliao01@gmail.com 5 | """ 6 | 7 | from .build import REID_HEADS_REGISTRY, build_heads 8 | 9 | # import all the meta_arch, so they will be registered 10 | from .embedding_head import EmbeddingHead 11 | from .clas_head import ClasHead 12 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/heads/build.py: -------------------------------------------------------------------------------- 1 | # encoding: utf-8 2 | """ 3 | @author: liaoxingyu 4 | @contact: sherlockliao01@gmail.com 5 | """ 6 | 7 | from ...utils.registry import Registry 8 | 9 | REID_HEADS_REGISTRY = Registry("HEADS") 10 | REID_HEADS_REGISTRY.__doc__ = """ 11 | Registry for reid heads in a baseline model. 12 | 13 | ROIHeads take feature maps and region proposals, and 14 | perform per-region computation. 15 | The registered object will be called with `obj(cfg, input_shape)`. 16 | The call is expected to return an :class:`ROIHeads`. 17 | """ 18 | 19 | 20 | def build_heads(cfg): 21 | """ 22 | Build REIDHeads defined by `cfg.MODEL.REID_HEADS.NAME`. 23 | """ 24 | head = cfg.MODEL.HEADS.NAME 25 | return REID_HEADS_REGISTRY.get(head)(cfg) 26 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/losses/__init__.py: -------------------------------------------------------------------------------- 1 | # encoding: utf-8 2 | """ 3 | @author: l1aoxingyu 4 | @contact: sherlockliao01@gmail.com 5 | """ 6 | 7 | from .circle_loss import * 8 | from .cross_entroy_loss import cross_entropy_loss, log_accuracy 9 | from .focal_loss import focal_loss 10 | from .triplet_loss import triplet_loss 11 | 12 | __all__ = [k for k in globals().keys() if not k.startswith("_")] -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/modeling/meta_arch/__init__.py: -------------------------------------------------------------------------------- 1 | # encoding: utf-8 2 | """ 3 | @author: liaoxingyu 4 | @contact: sherlockliao01@gmail.com 5 | """ 6 | 7 | from .build import META_ARCH_REGISTRY, build_model 8 | 9 | 10 | # import all the meta_arch, so they will be registered 11 | from .baseline import Baseline 12 | from .mgn import MGN 13 | from .moco import MoCo 14 | from .distiller import Distiller 15 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/solver/__init__.py: -------------------------------------------------------------------------------- 1 | # encoding: utf-8 2 | """ 3 | @author: liaoxingyu 4 | @contact: sherlockliao01@gmail.com 5 | """ 6 | 7 | 8 | from .build import build_lr_scheduler, build_optimizer -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/solver/optim/__init__.py: -------------------------------------------------------------------------------- 1 | # encoding: utf-8 2 | """ 3 | @author: xingyu liao 4 | @contact: sherlockliao01@gmail.com 5 | """ 6 | 7 | from .lamb import Lamb 8 | from .swa import SWA 9 | from .radam import RAdam 10 | from torch.optim import * 11 | -------------------------------------------------------------------------------- /pytorch/fast_reid/fastreid/utils/__init__.py: -------------------------------------------------------------------------------- 1 | # encoding: utf-8 2 | """ 3 | @author: sherlock 4 | @contact: sherlockliao01@gmail.com 5 | """ 6 | 7 | -------------------------------------------------------------------------------- /pytorch/fast_reid/images/cap.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/pytorch/fast_reid/images/cap.jpg -------------------------------------------------------------------------------- /pytorch/fast_reid/images/cap2.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/pytorch/fast_reid/images/cap2.jpg -------------------------------------------------------------------------------- /pytorch/fast_reid/images/car1_1.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/pytorch/fast_reid/images/car1_1.jpg -------------------------------------------------------------------------------- /pytorch/fast_reid/images/car1_2.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/pytorch/fast_reid/images/car1_2.jpg -------------------------------------------------------------------------------- /pytorch/fast_reid/images/car1_3.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/pytorch/fast_reid/images/car1_3.jpg -------------------------------------------------------------------------------- /pytorch/fast_reid/images/car2_1.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/pytorch/fast_reid/images/car2_1.jpg -------------------------------------------------------------------------------- /pytorch/fast_reid/images/car2_2.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/pytorch/fast_reid/images/car2_2.jpg -------------------------------------------------------------------------------- /pytorch/fast_reid/images/car2_3.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/pytorch/fast_reid/images/car2_3.jpg -------------------------------------------------------------------------------- /pytorch/fast_reid/images/car3_1.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/pytorch/fast_reid/images/car3_1.jpg -------------------------------------------------------------------------------- /pytorch/fast_reid/images/car3_2.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/pytorch/fast_reid/images/car3_2.jpg -------------------------------------------------------------------------------- /pytorch/fast_reid/images/car3_3.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/pytorch/fast_reid/images/car3_3.jpg -------------------------------------------------------------------------------- /pytorch/fast_reid/images/car3_4.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/pytorch/fast_reid/images/car3_4.jpg -------------------------------------------------------------------------------- /pytorch/fast_reid/images/car3_5.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/pytorch/fast_reid/images/car3_5.jpg -------------------------------------------------------------------------------- /pytorch/fast_reid/images/car3_6.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/pytorch/fast_reid/images/car3_6.jpg -------------------------------------------------------------------------------- /pytorch/fast_reid/images/car4_1.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/pytorch/fast_reid/images/car4_1.jpg -------------------------------------------------------------------------------- /pytorch/fast_reid/images/car4_2.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/pytorch/fast_reid/images/car4_2.jpg -------------------------------------------------------------------------------- /pytorch/fast_reid/images/car4_3.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/pytorch/fast_reid/images/car4_3.jpg -------------------------------------------------------------------------------- /pytorch/images/world.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/pytorch/images/world.jpg -------------------------------------------------------------------------------- /sklearn/Supervised_learning/Linear_Models/ex05_elastic_net.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | Created on 2021/7/5 23:01 4 | Filename : ex05_elastic_net.py 5 | Author : Taosy.W 6 | Zhihu : https://www.zhihu.com/people/1105936347 7 | Github : https://github.com/AFei19911012/PythonSamples 8 | Description: 9 | """ 10 | 11 | 12 | # ======================================================= 13 | 14 | 15 | def plot_lasso_coordinate_descent_path(): 16 | """ https://scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_coordinate_descent_path.html#sphx-glr-auto-examples-linear-model-plot 17 | -lasso-coordinate-descent-path-py """ 18 | pass 19 | -------------------------------------------------------------------------------- /sklearn/Supervised_learning/Stochastic_Gradient_Descent/ex03_sgd_sparse_data.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | Created on 2021/7/9 0:07 4 | Filename : ex03_sgd_sparse_data.py 5 | Author : Taosy.W 6 | Zhihu : https://www.zhihu.com/people/1105936347 7 | Github : https://github.com/AFei19911012/PythonSamples 8 | Description: 9 | """ 10 | 11 | # ======================================================= 12 | 13 | 14 | def plot_document_classification_20newsgroups(): 15 | """ https://scikit-learn.org/stable/auto_examples/text/plot_document_classification_20newsgroups.html#sphx-glr-auto-examples-text-plot-document 16 | -classification-20newsgroups-py """ 17 | pass 18 | 19 | 20 | if __name__ == '__main__': 21 | plot_document_classification_20newsgroups() 22 | -------------------------------------------------------------------------------- /sklearn/examples/Linear_Models/ex05_elastic_net.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | Created on 2021/7/5 23:01 4 | Filename : ex05_elastic_net.py 5 | Author : Taosy.W 6 | Zhihu : https://www.zhihu.com/people/1105936347 7 | Github : https://github.com/AFei19911012/PythonSamples 8 | Description: 9 | """ 10 | 11 | 12 | # ======================================================= 13 | 14 | 15 | def plot_lasso_coordinate_descent_path(): 16 | """ https://scikit-learn.org/stable/auto_examples/linear_model/plot_lasso_coordinate_descent_path.html#sphx-glr-auto-examples-linear-model-plot 17 | -lasso-coordinate-descent-path-py """ 18 | pass 19 | -------------------------------------------------------------------------------- /sklearn/examples/Stochastic_Gradient_Descent/ex03_sgd_sparse_data.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | Created on 2021/7/9 0:07 4 | Filename : ex03_sgd_sparse_data.py 5 | Author : Taosy.W 6 | Zhihu : https://www.zhihu.com/people/1105936347 7 | Github : https://github.com/AFei19911012/PythonSamples 8 | Description: 9 | """ 10 | 11 | # ======================================================= 12 | 13 | 14 | def plot_document_classification_20newsgroups(): 15 | """ https://scikit-learn.org/stable/auto_examples/text/plot_document_classification_20newsgroups.html#sphx-glr-auto-examples-text-plot-document 16 | -classification-20newsgroups-py """ 17 | pass 18 | 19 | 20 | if __name__ == '__main__': 21 | plot_document_classification_20newsgroups() 22 | -------------------------------------------------------------------------------- /yolov4/config/coco.data: -------------------------------------------------------------------------------- 1 | classes= 80 2 | train = data/coco/trainvalno5k.txt 3 | valid = data/coco_testdev 4 | #valid = data/coco_val_5k.list 5 | names = ../config/coco.names 6 | backup = backup/ 7 | eval=coco 8 | 9 | -------------------------------------------------------------------------------- /yolov4/config/forklift.data: -------------------------------------------------------------------------------- 1 | classes= 2 2 | train = C:/2021Taosy/Python/yolov4/config/forklift_train.txt 3 | valid = C:/2021Taosy/Python/yolov4/config/forklift_train.txt 4 | names = ../config/forklift.names 5 | backup = /home/seer/Project/train/cfg/coldstore/backup -------------------------------------------------------------------------------- /yolov4/config/forklift.names: -------------------------------------------------------------------------------- 1 | forklift 2 | cargo -------------------------------------------------------------------------------- /yolov4/config/helmet.data: -------------------------------------------------------------------------------- 1 | classes= 2 2 | train = data/helmet_train.txt # train 3 | valid = data/helmet_val.txt # val 4 | names = ../config/helmet.names 5 | backup = backup/ # weights 6 | eval=coco 7 | 8 | -------------------------------------------------------------------------------- /yolov4/config/helmet.names: -------------------------------------------------------------------------------- 1 | person 2 | helmet 3 | -------------------------------------------------------------------------------- /yolov4/demo_voc_label.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | Created on 2021/4/11 21:40 4 | Filename: demo_voc_label.py 5 | Author : Taosy 6 | Zhihu : https://www.zhihu.com/people/1105936347 7 | Github : https://github.com/AFei19911012 8 | Describe: 9 | """ 10 | 11 | import os 12 | 13 | 14 | def main(): 15 | wd = os.getcwd() 16 | # Get train and val 17 | file_list = os.listdir('data/helmet_2021_04_11') 18 | train_list = [] 19 | for f in file_list: 20 | if '.jpg' in f: 21 | train_list.append(f[:-4]) 22 | # Write to train.txt 23 | list_file = open(f'config/helmet_train.txt', 'w') 24 | for image_id in train_list: 25 | list_file.write(f'{wd}/data/helmet_2021_04_11/{image_id}.jpg\n') 26 | list_file.close() 27 | 28 | 29 | if __name__ == '__main__': 30 | main() 31 | -------------------------------------------------------------------------------- /yolov4/images/_dog.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov4/images/_dog.jpg -------------------------------------------------------------------------------- /yolov4/images/_image_01.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov4/images/_image_01.jpg -------------------------------------------------------------------------------- /yolov4/images/_image_02.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov4/images/_image_02.jpg -------------------------------------------------------------------------------- /yolov4/images/_image_03.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov4/images/_image_03.jpg -------------------------------------------------------------------------------- /yolov4/images/_image_04.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov4/images/_image_04.jpg -------------------------------------------------------------------------------- /yolov4/images/_image_05.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov4/images/_image_05.jpg -------------------------------------------------------------------------------- /yolov4/images/bird.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov4/images/bird.jpg -------------------------------------------------------------------------------- /yolov4/images/cat.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov4/images/cat.jpg -------------------------------------------------------------------------------- /yolov4/images/dog.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov4/images/dog.jpg -------------------------------------------------------------------------------- /yolov4/images/dog_yolov4_darknet_dll.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov4/images/dog_yolov4_darknet_dll.jpg -------------------------------------------------------------------------------- /yolov4/images/image_01.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov4/images/image_01.jpg -------------------------------------------------------------------------------- /yolov4/images/image_02.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov4/images/image_02.jpg -------------------------------------------------------------------------------- /yolov4/images/image_03.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov4/images/image_03.jpg -------------------------------------------------------------------------------- /yolov4/images/image_04.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov4/images/image_04.jpg -------------------------------------------------------------------------------- /yolov4/images/image_05.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov4/images/image_05.jpg -------------------------------------------------------------------------------- /yolov4/images/person.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov4/images/person.jpg -------------------------------------------------------------------------------- /yolov4/images/person_yolov4_darknet_dll.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov4/images/person_yolov4_darknet_dll.jpg -------------------------------------------------------------------------------- /yolov4/images/xiyou.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov4/images/xiyou.jpg -------------------------------------------------------------------------------- /yolov4/images/xiyou_yolov4_darknet_dll.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov4/images/xiyou_yolov4_darknet_dll.jpg -------------------------------------------------------------------------------- /yolov5/data/hyp.finetune_objects365.yaml: -------------------------------------------------------------------------------- 1 | lr0: 0.00258 2 | lrf: 0.17 3 | momentum: 0.779 4 | weight_decay: 0.00058 5 | warmup_epochs: 1.33 6 | warmup_momentum: 0.86 7 | warmup_bias_lr: 0.0711 8 | box: 0.0539 9 | cls: 0.299 10 | cls_pw: 0.825 11 | obj: 0.632 12 | obj_pw: 1.0 13 | iou_t: 0.2 14 | anchor_t: 3.44 15 | anchors: 3.2 16 | fl_gamma: 0.0 17 | hsv_h: 0.0188 18 | hsv_s: 0.704 19 | hsv_v: 0.36 20 | degrees: 0.0 21 | translate: 0.0902 22 | scale: 0.491 23 | shear: 0.0 24 | perspective: 0.0 25 | flipud: 0.0 26 | fliplr: 0.5 27 | mosaic: 1.0 28 | mixup: 0.0 29 | -------------------------------------------------------------------------------- /yolov5/data/images/bus.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov5/data/images/bus.jpg -------------------------------------------------------------------------------- /yolov5/data/images/game_1.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov5/data/images/game_1.jpg -------------------------------------------------------------------------------- /yolov5/data/images/game_2.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov5/data/images/game_2.jpg -------------------------------------------------------------------------------- /yolov5/data/images/image_01.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov5/data/images/image_01.jpg -------------------------------------------------------------------------------- /yolov5/data/images/image_02.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov5/data/images/image_02.jpg -------------------------------------------------------------------------------- /yolov5/data/images/image_03.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov5/data/images/image_03.jpg -------------------------------------------------------------------------------- /yolov5/data/images/image_04.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov5/data/images/image_04.jpg -------------------------------------------------------------------------------- /yolov5/data/images/image_05.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov5/data/images/image_05.jpg -------------------------------------------------------------------------------- /yolov5/data/images/rubbish.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov5/data/images/rubbish.jpg -------------------------------------------------------------------------------- /yolov5/data/images/zidane.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/AFei19911012/PythonSamples/18a75b4e81339957f7f950b9b2828a05e7a61d0a/yolov5/data/images/zidane.jpg -------------------------------------------------------------------------------- /yolov5/data/my_yolo.yaml: -------------------------------------------------------------------------------- 1 | # COCO 2017 dataset http://cocodataset.org - first 128 training images 2 | # Train command: python train.py --data coco128.yaml 3 | # Default dataset location is next to YOLOv5: 4 | # /parent_folder 5 | # /coco128 6 | # /yolov5 7 | 8 | 9 | # download command/URL (optional) 10 | #download: https://github.com/ultralytics/yolov5/releases/download/v1.0/coco128.zip 11 | 12 | # train and val data as 1) directory: path/images/, 2) file: path/images.txt, or 3) list: [path1/images/, path2/images/] 13 | train: D:/MyPrograms/DataSet/car/images/ 14 | val: D:/MyPrograms/DataSet/car/images/ 15 | 16 | # number of classes 17 | nc: 1 18 | 19 | # class names 20 | names: ['car'] 21 | -------------------------------------------------------------------------------- /yolov5/data/scripts/download_weights.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | # Download latest models from https://github.com/ultralytics/yolov5/releases 3 | # Usage: 4 | # $ bash path/to/download_weights.sh 5 | 6 | python - <