├── results └── tmp.txt ├── data ├── dog.jpg ├── eagle.jpg ├── giraffe.jpg ├── horses.jpg ├── person.jpg ├── scream.jpg ├── labels │ ├── 100_0.png │ ├── 100_1.png │ ├── 100_2.png │ ├── 100_3.png │ ├── 100_4.png │ ├── 100_5.png │ ├── 100_6.png │ ├── 100_7.png │ ├── 101_0.png │ ├── 101_1.png │ ├── 101_2.png │ ├── 101_3.png │ ├── 101_4.png │ ├── 101_5.png │ ├── 101_6.png │ ├── 101_7.png │ ├── 102_0.png │ ├── 102_1.png │ ├── 102_2.png │ ├── 102_3.png │ ├── 102_4.png │ ├── 102_5.png │ ├── 102_6.png │ ├── 102_7.png │ ├── 103_0.png │ ├── 103_1.png │ ├── 103_2.png │ ├── 103_3.png │ ├── 103_4.png │ ├── 103_5.png │ ├── 103_6.png │ ├── 103_7.png │ ├── 104_0.png │ ├── 104_1.png │ ├── 104_2.png │ ├── 104_3.png │ ├── 104_4.png │ ├── 104_5.png │ ├── 104_6.png │ ├── 104_7.png │ ├── 105_0.png │ ├── 105_1.png │ ├── 105_2.png │ ├── 105_3.png │ ├── 105_4.png │ ├── 105_5.png │ ├── 105_6.png │ ├── 105_7.png │ ├── 106_0.png │ ├── 106_1.png │ ├── 106_2.png │ ├── 106_3.png │ ├── 106_4.png │ ├── 106_5.png │ ├── 106_6.png │ ├── 106_7.png │ ├── 107_0.png │ ├── 107_1.png │ ├── 107_2.png │ ├── 107_3.png │ ├── 107_4.png │ ├── 107_5.png │ ├── 107_6.png │ ├── 107_7.png │ ├── 108_0.png │ ├── 108_1.png │ ├── 108_2.png │ ├── 108_3.png │ ├── 108_4.png │ ├── 108_5.png │ ├── 108_6.png │ ├── 108_7.png │ ├── 109_0.png │ ├── 109_1.png │ ├── 109_2.png │ ├── 109_3.png │ ├── 109_4.png │ ├── 109_5.png │ ├── 109_6.png │ ├── 109_7.png │ ├── 110_0.png │ ├── 110_1.png │ ├── 110_2.png │ ├── 110_3.png │ ├── 110_4.png │ ├── 110_5.png │ ├── 110_6.png │ ├── 110_7.png │ ├── 111_0.png │ ├── 111_1.png │ ├── 111_2.png │ ├── 111_3.png │ ├── 111_4.png │ ├── 111_5.png │ ├── 111_6.png │ ├── 111_7.png │ ├── 112_0.png │ ├── 112_1.png │ ├── 112_2.png │ ├── 112_3.png │ ├── 112_4.png │ ├── 112_5.png │ ├── 112_6.png │ ├── 112_7.png │ ├── 113_0.png │ ├── 113_1.png │ ├── 113_2.png │ ├── 113_3.png │ ├── 113_4.png │ ├── 113_5.png │ ├── 113_6.png │ ├── 113_7.png │ ├── 114_0.png │ ├── 114_1.png │ ├── 114_2.png │ ├── 114_3.png │ ├── 114_4.png │ ├── 114_5.png │ ├── 114_6.png │ ├── 114_7.png │ ├── 115_0.png │ ├── 115_1.png │ ├── 115_2.png │ ├── 115_3.png │ ├── 115_4.png │ ├── 115_5.png │ ├── 115_6.png │ ├── 115_7.png │ ├── 116_0.png │ ├── 116_1.png │ ├── 116_2.png │ ├── 116_3.png │ ├── 116_4.png │ ├── 116_5.png │ ├── 116_6.png │ ├── 116_7.png │ ├── 117_0.png │ ├── 117_1.png │ ├── 117_2.png │ ├── 117_3.png │ ├── 117_4.png │ ├── 117_5.png │ ├── 117_6.png │ ├── 117_7.png │ ├── 118_0.png │ ├── 118_1.png │ ├── 118_2.png │ ├── 118_3.png │ ├── 118_4.png │ ├── 118_5.png │ ├── 118_6.png │ ├── 118_7.png │ ├── 119_0.png │ ├── 119_1.png │ ├── 119_2.png │ ├── 119_3.png │ ├── 119_4.png │ ├── 119_5.png │ ├── 119_6.png │ ├── 119_7.png │ ├── 120_0.png │ ├── 120_1.png │ ├── 120_2.png │ ├── 120_3.png │ ├── 120_4.png │ ├── 120_5.png │ ├── 120_6.png │ ├── 120_7.png │ ├── 121_0.png │ ├── 121_1.png │ ├── 121_2.png │ ├── 121_3.png │ ├── 121_4.png │ ├── 121_5.png │ ├── 121_6.png │ ├── 121_7.png │ ├── 122_0.png │ ├── 122_1.png │ ├── 122_2.png │ ├── 122_3.png │ ├── 122_4.png │ ├── 122_5.png │ ├── 122_6.png │ ├── 122_7.png │ ├── 123_0.png │ ├── 123_1.png │ ├── 123_2.png │ ├── 123_3.png │ ├── 123_4.png │ ├── 123_5.png │ ├── 123_6.png │ ├── 123_7.png │ ├── 124_0.png │ ├── 124_1.png │ ├── 124_2.png │ ├── 124_3.png │ ├── 124_4.png │ ├── 124_5.png │ ├── 124_6.png │ ├── 124_7.png │ ├── 125_0.png │ ├── 125_1.png │ ├── 125_2.png │ ├── 125_3.png │ ├── 125_4.png │ ├── 125_5.png │ ├── 125_6.png │ ├── 125_7.png │ ├── 126_0.png │ ├── 126_1.png │ ├── 126_2.png │ ├── 126_3.png │ ├── 126_4.png │ ├── 126_5.png │ ├── 126_6.png │ ├── 126_7.png │ ├── 32_0.png │ ├── 32_1.png │ ├── 32_2.png │ ├── 32_3.png │ ├── 32_4.png │ ├── 32_5.png │ ├── 32_6.png │ ├── 32_7.png │ ├── 33_0.png │ ├── 33_1.png │ ├── 33_2.png │ ├── 33_3.png │ ├── 33_4.png │ ├── 33_5.png │ ├── 33_6.png │ ├── 33_7.png │ ├── 34_0.png │ ├── 34_1.png │ ├── 34_2.png │ ├── 34_3.png │ ├── 34_4.png │ ├── 34_5.png │ ├── 34_6.png │ ├── 34_7.png │ ├── 35_0.png │ ├── 35_1.png │ ├── 35_2.png │ ├── 35_3.png │ ├── 35_4.png │ ├── 35_5.png │ ├── 35_6.png │ ├── 35_7.png │ ├── 36_0.png │ ├── 36_1.png │ ├── 36_2.png │ ├── 36_3.png │ ├── 36_4.png │ ├── 36_5.png │ ├── 36_6.png │ ├── 36_7.png │ ├── 37_0.png │ ├── 37_1.png │ ├── 37_2.png │ ├── 37_3.png │ ├── 37_4.png │ ├── 37_5.png │ ├── 37_6.png │ ├── 37_7.png │ ├── 38_0.png │ ├── 38_1.png │ ├── 38_2.png │ ├── 38_3.png │ ├── 38_4.png │ ├── 38_5.png │ ├── 38_6.png │ ├── 38_7.png │ ├── 39_0.png │ ├── 39_1.png │ ├── 39_2.png │ ├── 39_3.png │ ├── 39_4.png │ ├── 39_5.png │ ├── 39_6.png │ ├── 39_7.png │ ├── 40_0.png │ ├── 40_1.png │ ├── 40_2.png │ ├── 40_3.png │ ├── 40_4.png │ ├── 40_5.png │ ├── 40_6.png │ ├── 40_7.png │ ├── 41_0.png │ ├── 41_1.png │ ├── 41_2.png │ ├── 41_3.png │ ├── 41_4.png │ ├── 41_5.png │ ├── 41_6.png │ ├── 41_7.png │ ├── 42_0.png │ ├── 42_1.png │ ├── 42_2.png │ ├── 42_3.png │ ├── 42_4.png │ ├── 42_5.png │ ├── 42_6.png │ ├── 42_7.png │ ├── 43_0.png │ ├── 43_1.png │ ├── 43_2.png │ ├── 43_3.png │ ├── 43_4.png │ ├── 43_5.png │ ├── 43_6.png │ ├── 43_7.png │ ├── 44_0.png │ ├── 44_1.png │ ├── 44_2.png │ ├── 44_3.png │ ├── 44_4.png │ ├── 44_5.png │ ├── 44_6.png │ ├── 44_7.png │ ├── 45_0.png │ ├── 45_1.png │ ├── 45_2.png │ ├── 45_3.png │ ├── 45_4.png │ ├── 45_5.png │ ├── 45_6.png │ ├── 45_7.png │ ├── 46_0.png │ ├── 46_1.png │ ├── 46_2.png │ ├── 46_3.png │ ├── 46_4.png │ ├── 46_5.png │ ├── 46_6.png │ ├── 46_7.png │ ├── 47_0.png │ ├── 47_1.png │ ├── 47_2.png │ ├── 47_3.png │ ├── 47_4.png │ ├── 47_5.png │ ├── 47_6.png │ ├── 47_7.png │ ├── 48_0.png │ ├── 48_1.png │ ├── 48_2.png │ ├── 48_3.png │ ├── 48_4.png │ ├── 48_5.png │ ├── 48_6.png │ ├── 48_7.png │ ├── 49_0.png │ ├── 49_1.png │ ├── 49_2.png │ ├── 49_3.png │ ├── 49_4.png │ ├── 49_5.png │ ├── 49_6.png │ ├── 49_7.png │ ├── 50_0.png │ ├── 50_1.png │ ├── 50_2.png │ ├── 50_3.png │ ├── 50_4.png │ ├── 50_5.png │ ├── 50_6.png │ ├── 50_7.png │ ├── 51_0.png │ ├── 51_1.png │ ├── 51_2.png │ ├── 51_3.png │ ├── 51_4.png │ ├── 51_5.png │ ├── 51_6.png │ ├── 51_7.png │ ├── 52_0.png │ ├── 52_1.png │ ├── 52_2.png │ ├── 52_3.png │ ├── 52_4.png │ ├── 52_5.png │ ├── 52_6.png │ ├── 52_7.png │ ├── 53_0.png │ ├── 53_1.png │ ├── 53_2.png │ ├── 53_3.png │ ├── 53_4.png │ ├── 53_5.png │ ├── 53_6.png │ ├── 53_7.png │ ├── 54_0.png │ ├── 54_1.png │ ├── 54_2.png │ ├── 54_3.png │ ├── 54_4.png │ ├── 54_5.png │ ├── 54_6.png │ ├── 54_7.png │ ├── 55_0.png │ ├── 55_1.png │ ├── 55_2.png │ ├── 55_3.png │ ├── 55_4.png │ ├── 55_5.png │ ├── 55_6.png │ ├── 55_7.png │ ├── 56_0.png │ ├── 56_1.png │ ├── 56_2.png │ ├── 56_3.png │ ├── 56_4.png │ ├── 56_5.png │ ├── 56_6.png │ ├── 56_7.png │ ├── 57_0.png │ ├── 57_1.png │ ├── 57_2.png │ ├── 57_3.png │ ├── 57_4.png │ ├── 57_5.png │ ├── 57_6.png │ ├── 57_7.png │ ├── 58_0.png │ ├── 58_1.png │ ├── 58_2.png │ ├── 58_3.png │ ├── 58_4.png │ ├── 58_5.png │ ├── 58_6.png │ ├── 58_7.png │ ├── 59_0.png │ ├── 59_1.png │ ├── 59_2.png │ ├── 59_3.png │ ├── 59_4.png │ ├── 59_5.png │ ├── 59_6.png │ ├── 59_7.png │ ├── 60_0.png │ ├── 60_1.png │ 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├── 93_4.png │ ├── 93_5.png │ ├── 93_6.png │ ├── 93_7.png │ ├── 94_0.png │ ├── 94_1.png │ ├── 94_2.png │ ├── 94_3.png │ ├── 94_4.png │ ├── 94_5.png │ ├── 94_6.png │ ├── 94_7.png │ ├── 95_0.png │ ├── 95_1.png │ ├── 95_2.png │ ├── 95_3.png │ ├── 95_4.png │ ├── 95_5.png │ ├── 95_6.png │ ├── 95_7.png │ ├── 96_0.png │ ├── 96_1.png │ ├── 96_2.png │ ├── 96_3.png │ ├── 96_4.png │ ├── 96_5.png │ ├── 96_6.png │ ├── 96_7.png │ ├── 97_0.png │ ├── 97_1.png │ ├── 97_2.png │ ├── 97_3.png │ ├── 97_4.png │ ├── 97_5.png │ ├── 97_6.png │ ├── 97_7.png │ ├── 98_0.png │ ├── 98_1.png │ ├── 98_2.png │ ├── 98_3.png │ ├── 98_4.png │ ├── 98_5.png │ ├── 98_6.png │ ├── 98_7.png │ ├── 99_0.png │ ├── 99_1.png │ ├── 99_2.png │ ├── 99_3.png │ ├── 99_4.png │ ├── 99_5.png │ ├── 99_6.png │ └── 99_7.png ├── goal.txt ├── voc.names └── coco9k.map ├── src ├── version.h ├── .editorconfig ├── version.h.in ├── classifier.h ├── csharp │ └── CMakeLists.txt ├── demo.h ├── activation_layer.h ├── list.h ├── parser.h ├── crop_layer.h ├── sam_layer.h ├── upsample_layer.h ├── reorg_layer.h ├── reorg_old_layer.h ├── route_layer.h ├── tree.h ├── cost_layer.h ├── scale_channels_layer.h └── dropout_layer.h ├── scripts ├── log_parser │ ├── plot.jpg │ ├── run_log_parser_windows.cmd │ └── readme.md ├── gen_tactic.sh ├── requested_cuda_version.sh ├── windows │ ├── windows_imagenet_label.sh │ ├── win_cifar.cmd │ ├── windows_imagenet_train.sh │ └── win_get_otb_datasets.cmd ├── get_imagenet_train.sh ├── imagenet_label.sh └── dice_label.sh ├── 3rdparty └── pthreads │ ├── bin │ ├── pthreadGC2.dll │ └── pthreadVC2.dll │ └── lib │ ├── libpthreadGC2.a │ └── pthreadVC2.lib ├── video_yolov3.sh ├── video_yolov4.sh ├── image_yolov3.sh ├── image_yolov4.sh ├── cfg ├── voc.data ├── coco.data ├── openimages.data ├── imagenet1k.data ├── imagenet22k.dataset ├── imagenet9k.hierarchy.dataset ├── combine9k.data ├── gru.cfg ├── lstm.train.cfg ├── writing.cfg ├── rnn.cfg ├── rnn.train.cfg ├── coco9k.map └── crnn.train.cfg ├── net_cam_v3.sh ├── net_cam_v4.sh ├── json_mjpeg_streams.sh ├── .github └── ISSUE_TEMPLATE │ └── feature_request.md └── LICENSE /results/tmp.txt: -------------------------------------------------------------------------------- 1 | -------------------------------------------------------------------------------- /data/dog.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/facedetection/darknet/master/data/dog.jpg -------------------------------------------------------------------------------- /data/eagle.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/facedetection/darknet/master/data/eagle.jpg -------------------------------------------------------------------------------- /data/giraffe.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/facedetection/darknet/master/data/giraffe.jpg -------------------------------------------------------------------------------- /data/horses.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/facedetection/darknet/master/data/horses.jpg -------------------------------------------------------------------------------- /data/person.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/facedetection/darknet/master/data/person.jpg -------------------------------------------------------------------------------- /data/scream.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/facedetection/darknet/master/data/scream.jpg -------------------------------------------------------------------------------- /src/version.h: -------------------------------------------------------------------------------- 1 | #define MAJOR_VERSION 0 2 | #define 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-------------------------------------------------------------------------------- /data/goal.txt: -------------------------------------------------------------------------------- 1 | +++++ 2 | val_eq (Val.add (Val.add (r3 PC) Vone) Vone) (Val.add (x2 PC) Vone) 3 | ***** 4 | -------------------------------------------------------------------------------- /scripts/log_parser/plot.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/facedetection/darknet/master/scripts/log_parser/plot.jpg -------------------------------------------------------------------------------- /3rdparty/pthreads/bin/pthreadGC2.dll: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/facedetection/darknet/master/3rdparty/pthreads/bin/pthreadGC2.dll -------------------------------------------------------------------------------- /3rdparty/pthreads/bin/pthreadVC2.dll: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/facedetection/darknet/master/3rdparty/pthreads/bin/pthreadVC2.dll -------------------------------------------------------------------------------- /3rdparty/pthreads/lib/libpthreadGC2.a: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/facedetection/darknet/master/3rdparty/pthreads/lib/libpthreadGC2.a -------------------------------------------------------------------------------- /3rdparty/pthreads/lib/pthreadVC2.lib: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/facedetection/darknet/master/3rdparty/pthreads/lib/pthreadVC2.lib -------------------------------------------------------------------------------- /src/.editorconfig: -------------------------------------------------------------------------------- 1 | root=true 2 | 3 | [*] 4 | trim_trailing_whitespace = true 5 | indent_style = space 6 | indent_size = 4 7 | 8 | 9 | -------------------------------------------------------------------------------- /video_yolov3.sh: -------------------------------------------------------------------------------- 1 | 2 | 3 | ./darknet detector demo ./cfg/coco.data ./cfg/yolov3.cfg ./yolov3.weights test50.mp4 -i 0 -thresh 0.25 4 | 5 | 6 | 7 | -------------------------------------------------------------------------------- /video_yolov4.sh: -------------------------------------------------------------------------------- 1 | 2 | 3 | ./darknet detector demo ./cfg/coco.data ./cfg/yolov4.cfg ./yolov4.weights test50.mp4 -i 0 -thresh 0.25 4 | 5 | 6 | 7 | -------------------------------------------------------------------------------- /image_yolov3.sh: -------------------------------------------------------------------------------- 1 | 2 | 3 | ./darknet detector test ./cfg/coco.data ./cfg/yolov3.cfg ./yolov3.weights data/dog.jpg -i 0 -thresh 0.25 4 | 5 | 6 | 7 | -------------------------------------------------------------------------------- /image_yolov4.sh: -------------------------------------------------------------------------------- 1 | 2 | 3 | ./darknet detector test ./cfg/coco.data ./cfg/yolov4.cfg ./yolov4.weights data/dog.jpg -i 0 -thresh 0.25 4 | 5 | 6 | 7 | -------------------------------------------------------------------------------- /src/version.h.in: -------------------------------------------------------------------------------- 1 | #define MAJOR_VERSION @Darknet_MAJOR_VERSION@ 2 | #define MINOR_VERSION @Darknet_MINOR_VERSION@ 3 | #define PATCH_VERSION @Darknet_PATCH_VERSION@ 4 | -------------------------------------------------------------------------------- /cfg/voc.data: -------------------------------------------------------------------------------- 1 | classes= 20 2 | train = /home/pjreddie/data/voc/train.txt 3 | valid = /home/pjreddie/data/voc/2007_test.txt 4 | names = data/voc.names 5 | backup = /home/pjreddie/backup/ 6 | 7 | -------------------------------------------------------------------------------- /net_cam_v3.sh: -------------------------------------------------------------------------------- 1 | #rm test_dnn_out.avi 2 | 3 | ./darknet detector demo ./cfg/coco.data ./cfg/yolov3.cfg ./yolov3.weights rtsp://admin:admin12345@192.168.0.228:554 -i 0 -thresh 0.25 4 | 5 | 6 | 7 | -------------------------------------------------------------------------------- /net_cam_v4.sh: -------------------------------------------------------------------------------- 1 | #rm test_dnn_out.avi 2 | 3 | ./darknet detector demo ./cfg/coco.data ./cfg/yolov4.cfg ./yolov4.weights rtsp://admin:admin12345@192.168.0.228:554 -i 0 -thresh 0.25 4 | 5 | 6 | 7 | -------------------------------------------------------------------------------- /scripts/gen_tactic.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | # Usage: 3 | # wget http://pjreddie.com/media/files/peek.weights 4 | # scripts/gen_tactic.sh < data/goal.txt 5 | ./darknet rnn generatetactic cfg/gru.cfg peek.weights 2>/dev/null 6 | -------------------------------------------------------------------------------- /cfg/coco.data: -------------------------------------------------------------------------------- 1 | classes= 80 2 | train = /home/pjreddie/data/coco/trainvalno5k.txt 3 | valid = coco_testdev 4 | #valid = data/coco_val_5k.list 5 | names = data/coco.names 6 | backup = /home/pjreddie/backup/ 7 | eval=coco 8 | 9 | -------------------------------------------------------------------------------- /scripts/requested_cuda_version.sh: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env bash 2 | 3 | export CUDA_VERSION="11.7" 4 | export CUDA_VERSION_DASHED="${CUDA_VERSION//./-}" 5 | export CUDNN_VERSION="8.4.1" 6 | export CUDNN_VERSION_DASHED="${CUDNN_VERSION//./-}" 7 | -------------------------------------------------------------------------------- /cfg/openimages.data: -------------------------------------------------------------------------------- 1 | classes= 601 2 | train = /home/pjreddie/data/openimsv4/openimages.train.list 3 | #valid = coco_testdev 4 | valid = data/coco_val_5k.list 5 | names = data/openimages.names 6 | backup = /home/pjreddie/backup/ 7 | eval=coco 8 | 9 | -------------------------------------------------------------------------------- /data/voc.names: -------------------------------------------------------------------------------- 1 | aeroplane 2 | bicycle 3 | bird 4 | boat 5 | bottle 6 | bus 7 | car 8 | cat 9 | chair 10 | cow 11 | diningtable 12 | dog 13 | horse 14 | motorbike 15 | person 16 | pottedplant 17 | sheep 18 | sofa 19 | train 20 | tvmonitor 21 | -------------------------------------------------------------------------------- /scripts/log_parser/run_log_parser_windows.cmd: -------------------------------------------------------------------------------- 1 | C:\Python27\Scripts\pip install numpy 2 | C:\Python27\Scripts\pip install matplotlib 3 | 4 | C:\Python27\python.exe log_parser.py --source-dir ./ --save-dir ./ --log-file test.log --show true 5 | 6 | pause -------------------------------------------------------------------------------- /src/classifier.h: -------------------------------------------------------------------------------- 1 | #ifndef CLASSIFIER_H 2 | #define CLASSIFIER_H 3 | 4 | #include "list.h" 5 | #ifdef __cplusplus 6 | extern "C" { 7 | #endif 8 | list *read_data_cfg(char *filename); 9 | #ifdef __cplusplus 10 | } 11 | #endif 12 | #endif 13 | -------------------------------------------------------------------------------- /cfg/imagenet1k.data: -------------------------------------------------------------------------------- 1 | classes=1000 2 | train = /data/imagenet/imagenet1k.train.list 3 | valid = /data/imagenet/imagenet1k.valid.list 4 | backup = /home/pjreddie/backup/ 5 | labels = data/imagenet.labels.list 6 | names = data/imagenet.shortnames.list 7 | top=5 8 | 9 | -------------------------------------------------------------------------------- /cfg/imagenet22k.dataset: -------------------------------------------------------------------------------- 1 | classes=21842 2 | train = /data/imagenet/imagenet22k.train.list 3 | valid = /data/imagenet/imagenet22k.valid.list 4 | backup = /home/pjreddie/backup/ 5 | labels = data/imagenet.labels.list 6 | names = data/imagenet.shortnames.list 7 | top = 5 8 | 9 | -------------------------------------------------------------------------------- /cfg/imagenet9k.hierarchy.dataset: -------------------------------------------------------------------------------- 1 | classes=9418 2 | train = data/9k.train.list 3 | valid = /data/imagenet/imagenet1k.valid.list 4 | leaves = data/imagenet1k.labels 5 | backup = /home/pjreddie/backup/ 6 | labels = data/9k.labels 7 | names = data/9k.names 8 | top=5 9 | 10 | -------------------------------------------------------------------------------- /cfg/combine9k.data: -------------------------------------------------------------------------------- 1 | classes= 9418 2 | #train = /home/pjreddie/data/coco/trainvalno5k.txt 3 | train = data/combine9k.train.list 4 | valid = /home/pjreddie/data/imagenet/det.val.files 5 | labels = data/9k.labels 6 | names = data/9k.names 7 | backup = backup/ 8 | map = data/inet9k.map 9 | eval = imagenet 10 | results = results 11 | -------------------------------------------------------------------------------- /json_mjpeg_streams.sh: -------------------------------------------------------------------------------- 1 | # Run this file and then open URL in Chrome/Firefox in 2 tabs: http://localhost:8070 and http://localhost:8090 2 | # Or open: http://ip-address:8070 and http://ip-address:8090 3 | # to get run: sudo ifconfig 4 | 5 | ./darknet detector demo ./cfg/coco.data ./cfg/yolov3.cfg ./yolov3.weights test50.mp4 -json_port 8070 -mjpeg_port 8090 -ext_output 6 | 7 | -------------------------------------------------------------------------------- /.github/ISSUE_TEMPLATE/feature_request.md: -------------------------------------------------------------------------------- 1 | --- 2 | name: Feature request 3 | about: Suggest an idea for this project 4 | title: '' 5 | labels: Feature-request 6 | assignees: '' 7 | 8 | --- 9 | 10 | For Feature-request: 11 | * describe your feature as detailed as possible 12 | * provide link to the paper and/or source code if it exist 13 | * attach chart/table with comparison that shows improvement 14 | -------------------------------------------------------------------------------- /scripts/windows/windows_imagenet_label.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | mkdir -p labelled 4 | wd=`pwd` 5 | 6 | for f in val/*.xml; 7 | do 8 | label=`grep -m1 "" $f | grep -oP '\K[^<]*'` 9 | im=`echo $f | sed 's/val/imgs/; s/xml/JPEG/'` 10 | out=`echo $im | sed 's/JPEG/'${label}'.JPEG/; s/imgs/labelled/'` 11 | mv ${wd}/$im ${wd}/$out 12 | #ln -s ${wd}/$im ${wd}/$out 13 | done 14 | 15 | #find ${wd}/labelled -name \*.JPEG > inet.val.list 16 | 17 | -------------------------------------------------------------------------------- /cfg/gru.cfg: -------------------------------------------------------------------------------- 1 | [net] 2 | subdivisions=1 3 | inputs=256 4 | batch = 1 5 | momentum=0.9 6 | decay=0.001 7 | time_steps=1 8 | learning_rate=0.5 9 | 10 | policy=poly 11 | power=4 12 | max_batches=2000 13 | 14 | [gru] 15 | batch_normalize=1 16 | output = 1024 17 | 18 | [gru] 19 | batch_normalize=1 20 | output = 1024 21 | 22 | [gru] 23 | batch_normalize=1 24 | output = 1024 25 | 26 | [connected] 27 | output=256 28 | activation=linear 29 | 30 | [softmax] 31 | 32 | [cost] 33 | type=sse 34 | 35 | -------------------------------------------------------------------------------- /src/csharp/CMakeLists.txt: -------------------------------------------------------------------------------- 1 | 2 | project(YoloCSharpWrapper LANGUAGES CSharp) 3 | include(CSharpUtilities) 4 | 5 | add_library(${PROJECT_NAME} 6 | ${PROJECT_NAME}.cs 7 | ) 8 | 9 | target_link_libraries(${PROJECT_NAME} PRIVATE dark) 10 | 11 | set_property(TARGET ${PROJECT_NAME} PROPERTY VS_DOTNET_REFERENCES 12 | "System" 13 | "System.Runtime.InteropServices" 14 | ) 15 | 16 | install(TARGETS ${PROJECT_NAME} 17 | RUNTIME DESTINATION "${INSTALL_BIN_DIR}" 18 | COMPONENT dev 19 | ) 20 | -------------------------------------------------------------------------------- /cfg/lstm.train.cfg: -------------------------------------------------------------------------------- 1 | [net] 2 | subdivisions=8 3 | inputs=256 4 | batch = 128 5 | momentum=0.9 6 | decay=0.001 7 | max_batches = 2000 8 | time_steps=576 9 | learning_rate=0.5 10 | policy=steps 11 | burn_in=10 12 | steps=1000,1500 13 | scales=.1,.1 14 | 15 | [lstm] 16 | batch_normalize=1 17 | output = 1024 18 | 19 | [lstm] 20 | batch_normalize=1 21 | output = 1024 22 | 23 | [lstm] 24 | batch_normalize=1 25 | output = 1024 26 | 27 | [connected] 28 | output=256 29 | activation=leaky 30 | 31 | [softmax] 32 | 33 | [cost] 34 | type=sse 35 | 36 | -------------------------------------------------------------------------------- /scripts/get_imagenet_train.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | wget http://www.image-net.org/challenges/LSVRC/2012/nnoupb/ILSVRC2012_img_train.tar 4 | mkdir -p ILSVRC2012_img_train 5 | tar --force-local -xf ILSVRC2012_img_train.tar -C ILSVRC2012_img_train 6 | 7 | wd=`pwd` 8 | 9 | for f in ILSVRC2012_img_train/*.tar; 10 | do 11 | name=$(echo "$f" | cut -f 1 -d '.') 12 | mkdir "${wd}/${name}" 13 | tar --force-local -xf "${wd}/${f}" -C "${wd}/${name}" 14 | done 15 | 16 | find "${wd}/ILSVRC2012_img_train" -name \*.JPEG > imagenet1k.train.list 17 | 18 | -------------------------------------------------------------------------------- /scripts/windows/win_cifar.cmd: -------------------------------------------------------------------------------- 1 | echo Run install_cygwin.cmd before: 2 | 3 | 4 | c:\cygwin64\bin\wget https://pjreddie.com/media/files/cifar.tgz 5 | 6 | c:\cygwin64\bin\gzip -d "%CD:\=/%/cifar.tgz" 7 | 8 | c:\cygwin64\bin\tar --force-local -xvf "%CD:\=/%/cifar.tar" 9 | 10 | c:\cygwin64\bin\cat "%CD:\=/%/labels.txt" 11 | 12 | 13 | c:\cygwin64\bin\find "%CD:\=/%/cifar/train" -name \*.png > "%CD:\=/%/cifar/train.list" 14 | 15 | c:\cygwin64\bin\find "%CD:\=/%/cifar/test" -name \*.png > "%CD:\=/%/cifar/test.list" 16 | 17 | 18 | 19 | pause -------------------------------------------------------------------------------- /scripts/windows/windows_imagenet_train.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | #wget http://www.image-net.org/challenges/LSVRC/2012/nnoupb/ILSVRC2012_img_train.tar 4 | #mkdir -p ILSVRC2012_img_train 5 | #tar --force-local -xf ILSVRC2012_img_train.tar -C ILSVRC2012_img_train 6 | 7 | wd=`pwd` 8 | 9 | for f in ILSVRC2012_img_train/*.tar; 10 | do 11 | name=$(echo "$f" | cut -f 1 -d '.') 12 | mkdir "${wd}/${name}" 13 | tar --force-local -xf "${wd}/${f}" -C "${wd}/${name}" 14 | done 15 | 16 | #find "${wd}/ILSVRC2012_img_train" -name \*.JPEG > imagenet1k.train.list 17 | 18 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | YOLO LICENSE 2 | Version 2, July 29 2016 3 | 4 | THIS SOFTWARE LICENSE IS PROVIDED "ALL CAPS" SO THAT YOU KNOW IT IS SUPER 5 | SERIOUS AND YOU DON'T MESS AROUND WITH COPYRIGHT LAW BECAUSE YOU WILL GET IN 6 | TROUBLE HERE ARE SOME OTHER BUZZWORDS COMMONLY IN THESE THINGS WARRANTIES 7 | LIABILITY CONTRACT TORT LIABLE CLAIMS RESTRICTION MERCHANTABILITY. NOW HERE'S 8 | THE REAL LICENSE: 9 | 10 | 0. Darknet is public domain. 11 | 1. Do whatever you want with it. 12 | 2. Stop emailing me about it! 13 | -------------------------------------------------------------------------------- /src/demo.h: -------------------------------------------------------------------------------- 1 | #ifndef DEMO_H 2 | #define DEMO_H 3 | 4 | #include "image.h" 5 | #ifdef __cplusplus 6 | extern "C" { 7 | #endif 8 | void demo(char *cfgfile, char *weightfile, float thresh, float hier_thresh, int cam_index, const char *filename, char **names, int classes, int avgframes, 9 | int frame_skip, char *prefix, char *out_filename, int mjpeg_port, int dontdraw_bbox, int json_port, int dont_show, int ext_output, int letter_box_in, int time_limit_sec, char *http_post_host, int benchmark, int benchmark_layers); 10 | #ifdef __cplusplus 11 | } 12 | #endif 13 | 14 | #endif 15 | -------------------------------------------------------------------------------- /cfg/writing.cfg: -------------------------------------------------------------------------------- 1 | [net] 2 | batch=128 3 | subdivisions=2 4 | height=256 5 | width=256 6 | channels=3 7 | learning_rate=0.00000001 8 | momentum=0.9 9 | decay=0.0005 10 | seen=0 11 | 12 | [convolutional] 13 | filters=32 14 | size=3 15 | stride=1 16 | pad=1 17 | activation=leaky 18 | 19 | [convolutional] 20 | filters=32 21 | size=3 22 | stride=1 23 | pad=1 24 | activation=leaky 25 | 26 | [convolutional] 27 | filters=32 28 | size=3 29 | stride=1 30 | pad=1 31 | activation=leaky 32 | 33 | [convolutional] 34 | filters=1 35 | size=3 36 | stride=1 37 | pad=1 38 | activation=logistic 39 | 40 | [cost] 41 | 42 | -------------------------------------------------------------------------------- /cfg/rnn.cfg: -------------------------------------------------------------------------------- 1 | [net] 2 | subdivisions=1 3 | inputs=256 4 | batch = 1 5 | momentum=0.9 6 | decay=0.001 7 | max_batches = 2000 8 | time_steps=1 9 | learning_rate=0.1 10 | policy=steps 11 | steps=1000,1500 12 | scales=.1,.1 13 | 14 | [rnn] 15 | batch_normalize=1 16 | output = 1024 17 | hidden=1024 18 | activation=leaky 19 | 20 | [rnn] 21 | batch_normalize=1 22 | output = 1024 23 | hidden=1024 24 | activation=leaky 25 | 26 | [rnn] 27 | batch_normalize=1 28 | output = 1024 29 | hidden=1024 30 | activation=leaky 31 | 32 | [connected] 33 | output=256 34 | activation=leaky 35 | 36 | [softmax] 37 | 38 | [cost] 39 | type=sse 40 | 41 | -------------------------------------------------------------------------------- /scripts/imagenet_label.sh: -------------------------------------------------------------------------------- 1 | #!/bin/bash 2 | 3 | #wget http://www.image-net.org/challenges/LSVRC/2012/nnoupb/ILSVRC2012_bbox_val_v3.tgz 4 | #other downloads: http://www.image-net.org/challenges/LSVRC/2012/nonpub-downloads 5 | #read: https://pjreddie.com/darknet/imagenet/ 6 | 7 | mkdir -p labelled 8 | wd=`pwd` 9 | 10 | for f in val/*.xml; 11 | do 12 | label=`grep -m1 "" $f | grep -oP '\K[^<]*'` 13 | im=`echo $f | sed 's/val/imgs/; s/xml/JPEG/'` 14 | out=`echo $im | sed 's/JPEG/'${label}'.JPEG/; s/imgs/labelled/'` 15 | ln -s ${wd}/$im ${wd}/$out 16 | done 17 | 18 | find ${wd}/labelled -name \*.JPEG > inet.val.list 19 | 20 | -------------------------------------------------------------------------------- /cfg/rnn.train.cfg: -------------------------------------------------------------------------------- 1 | [net] 2 | subdivisions=8 3 | inputs=256 4 | batch = 128 5 | momentum=0.9 6 | decay=0.001 7 | max_batches = 2000 8 | time_steps=576 9 | learning_rate=0.1 10 | policy=steps 11 | steps=1000,1500 12 | scales=.1,.1 13 | 14 | [rnn] 15 | batch_normalize=1 16 | output = 1024 17 | hidden=1024 18 | activation=leaky 19 | 20 | [rnn] 21 | batch_normalize=1 22 | output = 1024 23 | hidden=1024 24 | activation=leaky 25 | 26 | [rnn] 27 | batch_normalize=1 28 | output = 1024 29 | hidden=1024 30 | activation=leaky 31 | 32 | [connected] 33 | output=256 34 | activation=leaky 35 | 36 | [softmax] 37 | 38 | [cost] 39 | type=sse 40 | 41 | -------------------------------------------------------------------------------- /scripts/windows/win_get_otb_datasets.cmd: -------------------------------------------------------------------------------- 1 | echo Run install_cygwin.cmd before: 2 | 3 | rem http://cvlab.hanyang.ac.kr/tracker_benchmark/datasets.html 4 | 5 | c:\cygwin64\bin\bash -l -c "cd %CD:\=/%/; echo $PWD" 6 | 7 | c:\cygwin64\bin\dos2unix "%CD:\=/%/otb_get_labels.sh" 8 | 9 | 10 | c:\cygwin64\bin\bash -l -c "cd %CD:\=/%/; %CD:\=/%/otb_get_labels.sh Suv 320 240" 11 | 12 | c:\cygwin64\bin\bash -l -c "cd %CD:\=/%/; %CD:\=/%/otb_get_labels.sh Liquor 640 480" 13 | 14 | c:\cygwin64\bin\bash -l -c "cd %CD:\=/%/; %CD:\=/%/otb_get_labels.sh Freeman4 360 240" 15 | 16 | c:\cygwin64\bin\bash -l -c "cd %CD:\=/%/; %CD:\=/%/otb_get_labels.sh Human3 480 640" 17 | 18 | pause -------------------------------------------------------------------------------- /src/activation_layer.h: -------------------------------------------------------------------------------- 1 | #ifndef ACTIVATION_LAYER_H 2 | #define ACTIVATION_LAYER_H 3 | 4 | #include "activations.h" 5 | #include "layer.h" 6 | #include "network.h" 7 | 8 | #ifdef __cplusplus 9 | extern "C" { 10 | #endif 11 | layer make_activation_layer(int batch, int inputs, ACTIVATION activation); 12 | 13 | void forward_activation_layer(layer l, network_state state); 14 | void backward_activation_layer(layer l, network_state state); 15 | 16 | #ifdef GPU 17 | void forward_activation_layer_gpu(layer l, network_state state); 18 | void backward_activation_layer_gpu(layer l, network_state state); 19 | #endif 20 | 21 | #ifdef __cplusplus 22 | } 23 | #endif 24 | 25 | #endif 26 | -------------------------------------------------------------------------------- /src/list.h: -------------------------------------------------------------------------------- 1 | #ifndef LIST_H 2 | #define LIST_H 3 | 4 | typedef struct node{ 5 | void *val; 6 | struct node *next; 7 | struct node *prev; 8 | } node; 9 | 10 | typedef struct list{ 11 | int size; 12 | node *front; 13 | node *back; 14 | } list; 15 | 16 | #ifdef __cplusplus 17 | extern "C" { 18 | #endif 19 | list *make_list(); 20 | int list_find(list *l, void *val); 21 | 22 | void list_insert(list *, void *); 23 | 24 | void **list_to_array(list *l); 25 | 26 | void free_list_val(list *l); 27 | void free_list(list *l); 28 | void free_list_contents(list *l); 29 | void free_list_contents_kvp(list *l); 30 | 31 | #ifdef __cplusplus 32 | } 33 | #endif 34 | #endif 35 | -------------------------------------------------------------------------------- /src/parser.h: -------------------------------------------------------------------------------- 1 | #ifndef PARSER_H 2 | #define PARSER_H 3 | #include "network.h" 4 | 5 | #ifdef __cplusplus 6 | extern "C" { 7 | #endif 8 | network parse_network_cfg(char *filename); 9 | network parse_network_cfg_custom(char *filename, int batch, int time_steps); 10 | void save_network(network net, char *filename); 11 | void save_weights(network net, char *filename); 12 | void save_weights_upto(network net, char *filename, int cutoff, int save_ema); 13 | void save_weights_double(network net, char *filename); 14 | void load_weights(network *net, char *filename); 15 | void load_weights_upto(network *net, char *filename, int cutoff); 16 | 17 | #ifdef __cplusplus 18 | } 19 | #endif 20 | #endif 21 | -------------------------------------------------------------------------------- /src/crop_layer.h: -------------------------------------------------------------------------------- 1 | #ifndef CROP_LAYER_H 2 | #define CROP_LAYER_H 3 | 4 | #include "image.h" 5 | #include "layer.h" 6 | #include "network.h" 7 | 8 | typedef layer crop_layer; 9 | 10 | #ifdef __cplusplus 11 | extern "C" { 12 | #endif 13 | image get_crop_image(crop_layer l); 14 | crop_layer make_crop_layer(int batch, int h, int w, int c, int crop_height, int crop_width, int flip, float angle, float saturation, float exposure); 15 | void forward_crop_layer(const crop_layer l, network_state state); 16 | void resize_crop_layer(layer *l, int w, int h); 17 | 18 | #ifdef GPU 19 | void forward_crop_layer_gpu(crop_layer l, network_state state); 20 | #endif 21 | 22 | #ifdef __cplusplus 23 | } 24 | #endif 25 | 26 | #endif 27 | -------------------------------------------------------------------------------- /src/sam_layer.h: -------------------------------------------------------------------------------- 1 | #ifndef SAM_CHANNELS_LAYER_H 2 | #define SAM_CHANNELS_LAYER_H 3 | 4 | #include "layer.h" 5 | #include "network.h" 6 | 7 | #ifdef __cplusplus 8 | extern "C" { 9 | #endif 10 | layer make_sam_layer(int batch, int index, int w, int h, int c, int w2, int h2, int c2); 11 | void forward_sam_layer(const layer l, network_state state); 12 | void backward_sam_layer(const layer l, network_state state); 13 | void resize_sam_layer(layer *l, int w, int h); 14 | 15 | #ifdef GPU 16 | void forward_sam_layer_gpu(const layer l, network_state state); 17 | void backward_sam_layer_gpu(const layer l, network_state state); 18 | #endif 19 | 20 | #ifdef __cplusplus 21 | } 22 | #endif 23 | #endif // SAM_CHANNELS_LAYER_H 24 | -------------------------------------------------------------------------------- /src/upsample_layer.h: -------------------------------------------------------------------------------- 1 | #ifndef UPSAMPLE_LAYER_H 2 | #define UPSAMPLE_LAYER_H 3 | #include "dark_cuda.h" 4 | #include "layer.h" 5 | #include "network.h" 6 | 7 | #ifdef __cplusplus 8 | extern "C" { 9 | #endif 10 | layer make_upsample_layer(int batch, int w, int h, int c, int stride); 11 | void forward_upsample_layer(const layer l, network_state state); 12 | void backward_upsample_layer(const layer l, network_state state); 13 | void resize_upsample_layer(layer *l, int w, int h); 14 | 15 | #ifdef GPU 16 | void forward_upsample_layer_gpu(const layer l, network_state state); 17 | void backward_upsample_layer_gpu(const layer l, network_state state); 18 | #endif 19 | 20 | #ifdef __cplusplus 21 | } 22 | #endif 23 | #endif 24 | -------------------------------------------------------------------------------- /src/reorg_layer.h: -------------------------------------------------------------------------------- 1 | #ifndef REORG_LAYER_H 2 | #define REORG_LAYER_H 3 | 4 | #include "image.h" 5 | #include "dark_cuda.h" 6 | #include "layer.h" 7 | #include "network.h" 8 | 9 | #ifdef __cplusplus 10 | extern "C" { 11 | #endif 12 | layer make_reorg_layer(int batch, int w, int h, int c, int stride, int reverse); 13 | void resize_reorg_layer(layer *l, int w, int h); 14 | void forward_reorg_layer(const layer l, network_state state); 15 | void backward_reorg_layer(const layer l, network_state state); 16 | 17 | #ifdef GPU 18 | void forward_reorg_layer_gpu(layer l, network_state state); 19 | void backward_reorg_layer_gpu(layer l, network_state state); 20 | #endif 21 | 22 | #ifdef __cplusplus 23 | } 24 | #endif 25 | 26 | #endif 27 | -------------------------------------------------------------------------------- /scripts/dice_label.sh: -------------------------------------------------------------------------------- 1 | mkdir -p images 2 | mkdir -p images/orig 3 | mkdir -p images/train 4 | mkdir -p images/val 5 | 6 | ffmpeg -i Face1.mp4 images/orig/face1_%6d.jpg 7 | ffmpeg -i Face2.mp4 images/orig/face2_%6d.jpg 8 | ffmpeg -i Face3.mp4 images/orig/face3_%6d.jpg 9 | ffmpeg -i Face4.mp4 images/orig/face4_%6d.jpg 10 | ffmpeg -i Face5.mp4 images/orig/face5_%6d.jpg 11 | ffmpeg -i Face6.mp4 images/orig/face6_%6d.jpg 12 | 13 | mogrify -resize 100x100^ -gravity center -crop 100x100+0+0 +repage images/orig/* 14 | 15 | ls images/orig/* | shuf | head -n 1000 | xargs mv -t images/val 16 | mv images/orig/* images/train 17 | 18 | find `pwd`/images/train > dice.train.list -name \*.jpg 19 | find `pwd`/images/val > dice.val.list -name \*.jpg 20 | 21 | -------------------------------------------------------------------------------- /scripts/log_parser/readme.md: -------------------------------------------------------------------------------- 1 | #### parsing training log and plot 2 | **Requirement** 3 | 1. ** matplotlib needed ** 4 | 5 | **Usage** 6 | 1. --source-dir the directory of training log files 7 | 2. --save-dir the directory to save loss curve, image and csv file 8 | 3. --log-file log file name to be parsed 9 | 4. --csv-file csv file name to save loss data, default it's same with training log file name 10 | 5. --show whether to show after finished parsing, default False, just works on windows or linux with GUI desktop 11 | 12 | `python log_parser.py --source-dir ./ --save-dir ./ --log-file test.log --show true` 13 | 14 | ![plot](https://github.com/Adesun/darknet/blob/log_parser/scripts/log_parser/plot.jpg) 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | -------------------------------------------------------------------------------- /src/reorg_old_layer.h: -------------------------------------------------------------------------------- 1 | #ifndef REORG_OLD_LAYER_H 2 | #define REORG_OLD_LAYER_H 3 | 4 | #include "image.h" 5 | #include "dark_cuda.h" 6 | #include "layer.h" 7 | #include "network.h" 8 | 9 | #ifdef __cplusplus 10 | extern "C" { 11 | #endif 12 | layer make_reorg_old_layer(int batch, int w, int h, int c, int stride, int reverse); 13 | void resize_reorg_old_layer(layer *l, int w, int h); 14 | void forward_reorg_old_layer(const layer l, network_state state); 15 | void backward_reorg_old_layer(const layer l, network_state state); 16 | 17 | #ifdef GPU 18 | void forward_reorg_old_layer_gpu(layer l, network_state state); 19 | void backward_reorg_old_layer_gpu(layer l, network_state state); 20 | #endif 21 | 22 | #ifdef __cplusplus 23 | } 24 | #endif 25 | 26 | #endif 27 | -------------------------------------------------------------------------------- /src/route_layer.h: -------------------------------------------------------------------------------- 1 | #ifndef ROUTE_LAYER_H 2 | #define ROUTE_LAYER_H 3 | #include "network.h" 4 | #include "layer.h" 5 | 6 | typedef layer route_layer; 7 | 8 | #ifdef __cplusplus 9 | extern "C" { 10 | #endif 11 | route_layer make_route_layer(int batch, int n, int *input_layers, int *input_size, int groups, int group_id); 12 | void forward_route_layer(const route_layer l, network_state state); 13 | void backward_route_layer(const route_layer l, network_state state); 14 | void resize_route_layer(route_layer *l, network *net); 15 | 16 | #ifdef GPU 17 | void forward_route_layer_gpu(const route_layer l, network_state state); 18 | void backward_route_layer_gpu(const route_layer l, network_state state); 19 | #endif 20 | 21 | #ifdef __cplusplus 22 | } 23 | #endif 24 | #endif 25 | -------------------------------------------------------------------------------- /cfg/coco9k.map: -------------------------------------------------------------------------------- 1 | 5177 2 | 3768 3 | 3802 4 | 3800 5 | 4107 6 | 4072 7 | 4071 8 | 3797 9 | 4097 10 | 2645 11 | 5150 12 | 2644 13 | 3257 14 | 2523 15 | 6527 16 | 6866 17 | 6912 18 | 7342 19 | 7255 20 | 7271 21 | 7217 22 | 6858 23 | 7343 24 | 7233 25 | 3704 26 | 4374 27 | 3641 28 | 5001 29 | 3899 30 | 2999 31 | 2631 32 | 5141 33 | 2015 34 | 1133 35 | 1935 36 | 1930 37 | 5144 38 | 5143 39 | 2371 40 | 3916 41 | 3745 42 | 3640 43 | 4749 44 | 4736 45 | 4735 46 | 3678 47 | 58 48 | 42 49 | 771 50 | 81 51 | 152 52 | 141 53 | 786 54 | 700 55 | 218 56 | 791 57 | 2518 58 | 2521 59 | 3637 60 | 2458 61 | 2505 62 | 2519 63 | 3499 64 | 2837 65 | 3503 66 | 2597 67 | 3430 68 | 2080 69 | 5103 70 | 5111 71 | 5102 72 | 3013 73 | 5096 74 | 1102 75 | 3218 76 | 4010 77 | 2266 78 | 1127 79 | 5122 80 | 2360 81 | -------------------------------------------------------------------------------- /data/coco9k.map: -------------------------------------------------------------------------------- 1 | 5177 2 | 3768 3 | 3802 4 | 3800 5 | 4107 6 | 4072 7 | 4071 8 | 3797 9 | 4097 10 | 2645 11 | 5150 12 | 2644 13 | 3257 14 | 2523 15 | 6527 16 | 6866 17 | 6912 18 | 7342 19 | 7255 20 | 7271 21 | 7217 22 | 6858 23 | 7343 24 | 7233 25 | 3704 26 | 4374 27 | 3641 28 | 5001 29 | 3899 30 | 2999 31 | 2631 32 | 5141 33 | 2015 34 | 1133 35 | 1935 36 | 1930 37 | 5144 38 | 5143 39 | 2371 40 | 3916 41 | 3745 42 | 3640 43 | 4749 44 | 4736 45 | 4735 46 | 3678 47 | 58 48 | 42 49 | 771 50 | 81 51 | 152 52 | 141 53 | 786 54 | 700 55 | 218 56 | 791 57 | 2518 58 | 2521 59 | 3637 60 | 2458 61 | 2505 62 | 2519 63 | 3499 64 | 2837 65 | 3503 66 | 2597 67 | 3430 68 | 2080 69 | 5103 70 | 5111 71 | 5102 72 | 3013 73 | 5096 74 | 1102 75 | 3218 76 | 4010 77 | 2266 78 | 1127 79 | 5122 80 | 2360 81 | -------------------------------------------------------------------------------- /src/tree.h: -------------------------------------------------------------------------------- 1 | #ifndef TREE_H 2 | #define TREE_H 3 | #include "darknet.h" 4 | 5 | //typedef struct{ 6 | // int *leaf; 7 | // int n; 8 | // int *parent; 9 | // int *child; 10 | // int *group; 11 | // char **name; 12 | // 13 | // int groups; 14 | // int *group_size; 15 | // int *group_offset; 16 | //} tree; 17 | 18 | #ifdef __cplusplus 19 | extern "C" { 20 | #endif 21 | //tree *read_tree(char *filename); 22 | int hierarchy_top_prediction(float *predictions, tree *hier, float thresh, int stride); 23 | void hierarchy_predictions(float *predictions, int n, tree *hier, int only_leaves); 24 | void change_leaves(tree *t, char *leaf_list); 25 | float get_hierarchy_probability(float *x, tree *hier, int c); 26 | 27 | #ifdef __cplusplus 28 | } 29 | #endif 30 | #endif 31 | -------------------------------------------------------------------------------- /cfg/crnn.train.cfg: -------------------------------------------------------------------------------- 1 | [net] 2 | subdivisions=8 3 | inputs=256 4 | batch = 128 5 | momentum=0.9 6 | decay=0.001 7 | max_batches = 2000 8 | time_steps=576 9 | learning_rate=0.1 10 | policy=steps 11 | steps=1000,1500 12 | scales=.1,.1 13 | 14 | try_fix_nan=1 15 | 16 | [connected] 17 | output=256 18 | activation=leaky 19 | 20 | [crnn] 21 | batch_normalize=1 22 | size=1 23 | pad=0 24 | output = 1024 25 | hidden=1024 26 | activation=leaky 27 | 28 | [crnn] 29 | batch_normalize=1 30 | size=1 31 | pad=0 32 | output = 1024 33 | hidden=1024 34 | activation=leaky 35 | 36 | [crnn] 37 | batch_normalize=1 38 | size=1 39 | pad=0 40 | output = 1024 41 | hidden=1024 42 | activation=leaky 43 | 44 | [connected] 45 | output=256 46 | activation=leaky 47 | 48 | [softmax] 49 | 50 | [cost] 51 | type=sse 52 | 53 | -------------------------------------------------------------------------------- /src/cost_layer.h: -------------------------------------------------------------------------------- 1 | #ifndef COST_LAYER_H 2 | #define COST_LAYER_H 3 | #include "layer.h" 4 | #include "network.h" 5 | 6 | typedef layer cost_layer; 7 | 8 | #ifdef __cplusplus 9 | extern "C" { 10 | #endif 11 | COST_TYPE get_cost_type(char *s); 12 | char *get_cost_string(COST_TYPE a); 13 | cost_layer make_cost_layer(int batch, int inputs, COST_TYPE cost_type, float scale); 14 | void forward_cost_layer(const cost_layer l, network_state state); 15 | void backward_cost_layer(const cost_layer l, network_state state); 16 | void resize_cost_layer(cost_layer *l, int inputs); 17 | 18 | #ifdef GPU 19 | void forward_cost_layer_gpu(cost_layer l, network_state state); 20 | void backward_cost_layer_gpu(const cost_layer l, network_state state); 21 | #endif 22 | 23 | #ifdef __cplusplus 24 | } 25 | #endif 26 | #endif 27 | -------------------------------------------------------------------------------- /src/scale_channels_layer.h: -------------------------------------------------------------------------------- 1 | #ifndef SCALE_CHANNELS_LAYER_H 2 | #define SCALE_CHANNELS_LAYER_H 3 | 4 | #include "layer.h" 5 | #include "network.h" 6 | 7 | #ifdef __cplusplus 8 | extern "C" { 9 | #endif 10 | layer make_scale_channels_layer(int batch, int index, int w, int h, int c, int w2, int h2, int c2, int scale_wh); 11 | void forward_scale_channels_layer(const layer l, network_state state); 12 | void backward_scale_channels_layer(const layer l, network_state state); 13 | void resize_scale_channels_layer(layer *l, network *net); 14 | 15 | #ifdef GPU 16 | void forward_scale_channels_layer_gpu(const layer l, network_state state); 17 | void backward_scale_channels_layer_gpu(const layer l, network_state state); 18 | #endif 19 | 20 | #ifdef __cplusplus 21 | } 22 | #endif 23 | #endif // SCALE_CHANNELS_LAYER_H 24 | -------------------------------------------------------------------------------- /src/dropout_layer.h: -------------------------------------------------------------------------------- 1 | #ifndef DROPOUT_LAYER_H 2 | #define DROPOUT_LAYER_H 3 | 4 | #include "layer.h" 5 | #include "network.h" 6 | 7 | typedef layer dropout_layer; 8 | 9 | #ifdef __cplusplus 10 | extern "C" { 11 | #endif 12 | dropout_layer make_dropout_layer(int batch, int inputs, float probability, int dropblock, float dropblock_size_rel, int dropblock_size_abs, int w, int h, int c); 13 | 14 | void forward_dropout_layer(dropout_layer l, network_state state); 15 | void backward_dropout_layer(dropout_layer l, network_state state); 16 | void resize_dropout_layer(dropout_layer *l, int inputs); 17 | 18 | #ifdef GPU 19 | void forward_dropout_layer_gpu(dropout_layer l, network_state state); 20 | void backward_dropout_layer_gpu(dropout_layer l, network_state state); 21 | 22 | #endif 23 | #ifdef __cplusplus 24 | } 25 | #endif 26 | #endif 27 | --------------------------------------------------------------------------------