yolo如何导出.weights和.cfg

crlong33

各位老师好，最近新接触一个opencv库中的函数cv::dnn::readnet（）函数；        参数1是yolo训练好的模型.weights后缀文件，
        参数2是超参数.cfg后缀的文件。
如何才能得到这2个后缀的文件呢（*.weigthts和*.cfg），或者其他的也行，因为yolov8训练好的都是*.pt和*.yaml配套。网上还可以发现能导出*.onnx，但是第二个参数怎么整呀？
如何导出一套来呢？只要能用上readnet函数就可以。



官网解释：

Net cv::dnn::readNet	(	const String &	model,
		const String &	config = "",
		const String &	framework = ""
	)

Python:
	cv.dnn.readNet(	model[, config[, framework]]	) ->	retval
	cv.dnn.readNet(	framework, bufferModel[, bufferConfig]	) ->	retval

Parameters

[in]	model	Binary file contains trained weights. The following file extensions are expected for models from different frameworks: *.caffemodel (Caffe, http://caffe.berkeleyvision.org/) *.pb (TensorFlow, https://www.tensorflow.org/) *.t7 | *.net (Torch, http://torch.ch/) *.weights (Darknet, https://pjreddie.com/darknet/) *.bin (DLDT, https://software.intel.com/openvino-toolkit) *.onnx (ONNX, https://onnx.ai/)
[in]	config	Text file contains network configuration. It could be a file with the following extensions: *.prototxt (Caffe, http://caffe.berkeleyvision.org/) *.pbtxt (TensorFlow, https://www.tensorflow.org/) *.cfg (Darknet, https://pjreddie.com/darknet/) *.xml (DLDT, https://software.intel.com/openvino-toolkit)
[in]	framework	Explicit framework name tag to determine a format.

yuanadrt113

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4102小白

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雷欧库珀

在yolov5的export.py代码中添加：
from models.yolo import Model
model=Model(‘yolov5s.yaml’)
model.load_state_dict(torch.load(‘yolov5s.pt’)[‘model’].state_dict())
torch.save(model.state_dict(),‘yolov5s.weights’)