关于hubconf.py中process_image的疑问

[clhne]

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• I have read the README carefully. 我已经仔细阅读了README上的操作指引。

• I want to train my custom dataset, and I have read the tutorials for training your custom data carefully and organize my dataset correctly; (FYI: We recommand you to apply the config files of xx_finetune.py.) 我想训练自定义数据集，我已经仔细阅读了训练自定义数据的教程，以及按照正确的目录结构存放数据集。（FYI: 我们推荐使用xx_finetune.py等配置文件训练自定义数据集。）

• I have pulled the latest code of main branch to run again and the problem still existed. 我已经拉取了主分支上最新的代码，重新运行之后，问题仍不能解决。

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• I have searched the YOLOv6 issues and found no similar questions.

Question

请问下process_image中从opencv imread后，图像的格式默认就是BGR的，为什么又做了一次RGB2BGR的格式转换？
https://github.com/meituan/YOLOv6/blob/main/hubconf.py#L76

def process_image(path, img_size, stride):
    '''Preprocess image before inference.'''
    try:
            img_src = cv2.imread(path)                           # opencv imread读进来不就是BGR格式的吗
            img_src = cv2.cvtColor(img_src, cv2.COLOR_RGB2BGR)   # 为啥这里又做了一次RGB2BGR的转换？？？
            assert img_src is not None, f"opencv cannot read image correctly or {path} not exists"
    except:
            img_src = np.asarray(Image.open(path))
            assert img_src is not None, f"Image Not Found {path}, workdir: {os.getcwd()}"

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