darknet-YOLOV4修改版可以直接在Jetson系列产品上使用 （2000个子文件） 
libpthreadGC2.a 91KB gemm.c 103KB parser.c 84KB data.c 73KB detector.c 72KB convolutional_layer.c 59KB conv_lstm_layer.c 53KB image.c 47KB network.c 45KB classifier.c 44KB yolo_layer.c 39KB gaussian_yolo_layer.c 36KB box.c 29KB go.c 26KB lstm_layer.c 25KB utils.c 22KB region_layer.c 22KB blas.c 22KB darknet.c 19KB dark_cuda.c 16KB batchnorm_layer.c 16KB gru_layer.c 15KB coco.c 14KB connected_layer.c 14KB maxpool_layer.c 14KB rnn.c 14KB crnn_layer.c 14KB demo.c 14KB getopt.c 13KB layer.c 12KB shortcut_layer.c 12KB yolo.c 12KB detection_layer.c 12KB activations.c 11KB captcha.c 11KB compare.c 11KB softmax_layer.c 10KB rnn_layer.c 10KB nightmare.c 9KB kmeansiou.c 9KB local_layer.c 9KB cifar.c 8KB matrix.c 8KB rnn_vid.c 7KB deconvolutional_layer.c 6KB normalization_layer.c 6KB route_layer.c 5KB scale_channels_layer.c 5KB voxel.c 5KB tag.c 4KB writing.c 4KB cost_layer.c 4KB im2col.c 4KB super.c 4KB tree.c 4KB dice.c 4KB col2im.c 4KB sam_layer.c 3KB option_list.c 3KB upsample_layer.c 3KB reorg_layer.c 3KB reorg_old_layer.c 3KB dropout_layer.c 3KB crop_layer.c 3KB swag.c 2KB cpu_gemm.c 2KB avgpool_layer.c 2KB list.c 2KB activation_layer.c 2KB art.c 2KB gettimeofday.c 1KB resnet152_trident.cfg 23KB resnet152_trident.cfg 23KB densenet201_yolo.cfg 20KB densenet201.cfg 19KB densenet201.cfg 19KB resnext152-32x4d.cfg 16KB resnext152-32x4d.cfg 16KB resnet152_yolo.cfg 15KB resnet152.cfg 15KB resnet152.cfg 15KB yolov4.cfg 13KB efficientnet-lite3.cfg 12KB efficientnet-lite3.cfg 12KB enet-coco.cfg 12KB enet-coco.cfg 12KB cd53paspp-gamma.cfg 12KB cd53paspp-gamma.cfg 12KB yolov4-custom.cfg 12KB yolov4-custom.cfg 12KB yolov4.cfg 12KB efficientnet_b0.cfg 11KB efficientnet_b0.cfg 11KB csresnext50-panet-spp-original-optimal.cfg 11KB csresnext50-panet-spp-original-optimal.cfg 11KB csresnext50-panet-spp.cfg 10KB csresnext50-panet-spp.cfg 10KB yolov3_5l.cfg 10KB yolov3_5l.cfg 10KB resnet101.cfg 10KB共 2000 条
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