问题描述
如何将 YOLOv4-CSP 暗网权重转换为 Tensorflow (tf) 格式?
我尝试过使用这个 repo,但没有用.>
我收到此错误消息:
回溯(最近一次调用最后一次):文件save_model.py",第 58 行,在 <module> 中.应用程序运行(主)文件C:\Python37\lib\site-packages\absl\app.py",第 303 行,运行中_run_main(main, args)文件C:\Python37\lib\site-packages\absl\app.py",第 251 行,在 _run_main 中sys.exit(main(argv))文件save_model.py",第 54 行,在主目录中save_tf()文件save_model.py",第 49 行,在 save_tf 中utils.load_weights(model, FLAGS.weights, FLAGS.model, FLAGS.tiny)文件D:\swap\20210319\tensorflow-yolov4-tflite\core\utils.py",第63行,load_weightsconv_weights = conv_weights.reshape(conv_shape).transpose([2, 3, 1, 0])ValueError:无法将大小为 3791890 的数组重塑为形状 (1024,512,3,3)
您使用的存储库尚不支持 Scaled YoloV4 或 Yolov4-csp 的转换.根据this issue
,它仍然是一个功能请求幸运的是有一个解决方法.我发现 this 存储库做同样的事情,唯一的区别是它转换在转换为 tensorflow 格式之前将模型转换为 .h5
(keras 格式).这也支持yolov4-csp
.
我制作了一个用于转换的 Google Colab 笔记本,可以在 这里.
How to convert YOLOv4-CSP darknet weights to Tensorflow (tf) format?
I have tried using this repo but it didn't work.
I had this error message:
Traceback (most recent call last):
File "save_model.py", line 58, in <module>
app.run(main)
File "C:\Python37\lib\site-packages\absl\app.py", line 303, in run
_run_main(main, args)
File "C:\Python37\lib\site-packages\absl\app.py", line 251, in _run_main
sys.exit(main(argv))
File "save_model.py", line 54, in main
save_tf()
File "save_model.py", line 49, in save_tf
utils.load_weights(model, FLAGS.weights, FLAGS.model, FLAGS.tiny)
File "D:\swap\20210319\tensorflow-yolov4-tflite\core\utils.py", line 63, in load_weights
conv_weights = conv_weights.reshape(conv_shape).transpose([2, 3, 1, 0])
ValueError: cannot reshape array of size 3791890 into shape (1024,512,3,3)
The repository that you are using doesn't support conversion of Scaled YoloV4 or Yolov4-csp yet. It's still a feature request according to this issue
There's luckily a workaround. I found this repository that does the same thing, only difference being it converts the model to .h5
(keras format) before converting into tensorflow format. This also supports yolov4-csp
.
I made a Google Colab notebook that does the conversion, which can be found here.
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