lilith.lu 994aa0c2cd 来自svn 6986 8 months ago
..
bin 994aa0c2cd 来自svn 6986 8 months ago
doc 994aa0c2cd 来自svn 6986 8 months ago
model_configs 994aa0c2cd 来自svn 6986 8 months ago
tool 994aa0c2cd 来自svn 6986 8 months ago
cfg.py 994aa0c2cd 来自svn 6986 8 months ago
cmd.txt 994aa0c2cd 来自svn 6986 8 months ago
compute_test_set_aps.py 994aa0c2cd 来自svn 6986 8 months ago
darknettoonnx.py 994aa0c2cd 来自svn 6986 8 months ago
dataset.py 994aa0c2cd 来自svn 6986 8 months ago
demo.py 994aa0c2cd 来自svn 6986 8 months ago
demo_darknet2onnx.py 994aa0c2cd 来自svn 6986 8 months ago
demo_pytorch2onnx.py 994aa0c2cd 来自svn 6986 8 months ago
demo_tensorflow.py 994aa0c2cd 来自svn 6986 8 months ago
demo_trt.py 994aa0c2cd 来自svn 6986 8 months ago
eval_normal_breast.py 994aa0c2cd 来自svn 6986 8 months ago
evaluate_on_coco.py 994aa0c2cd 来自svn 6986 8 months ago
models.py 994aa0c2cd 来自svn 6986 8 months ago
plot_test_set_bboxes.py 994aa0c2cd 来自svn 6986 8 months ago
readme.txt 994aa0c2cd 来自svn 6986 8 months ago
train.py 994aa0c2cd 来自svn 6986 8 months ago

readme.txt

1. 该版本YOLO默认Cuda11,如需训练能支持其他版本Cuda的YOLO模型,需要重新编译,编译方法参考“”YOLO编译方法.pdf“”
2. cmd.txt中存放可能用到的命令行
3. bin目录下存放编出来的exe
4. 自己训练模型的配置参数,存放在model_configs目录下