resize_norm_img 直接resize问题，宽高比大于10的数据丢弃代码怎么没找到呢

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Bug (问题描述)

def resize_norm_img(img, image_shape, padding=True, interpolation=cv2.INTER_LINEAR): imgC, imgH, imgW = image_shape h = img.shape[0] w = img.shape[1] if not padding: resized_image = cv2.resize(img, (imgW, imgH), interpolation=interpolation) resized_w = imgW else: ratio = w / float(h) if math.ceil(imgH * ratio) > imgW: resized_w = imgW else: resized_w = int(math.ceil(imgH * ratio)) resized_image = cv2.resize(img, (resized_w, imgH)) resized_image = resized_image.astype("float32") if image_shape[0] == 1: resized_image = resized_image / 255 resized_image = resized_image[np.newaxis, :] else: resized_image = resized_image.transpose((2, 0, 1)) / 255 resized_image -= 0.5 resized_image /= 0.5 padding_im = np.zeros((imgC, imgH, imgW), dtype=np.float32) padding_im[:, :, 0:resized_w] = resized_image valid_ratio = min(1.0, float(resized_w / imgW)) return padding_im, valid_ratio

训练识别模型的时候 resized_image = cv2.resize(img, (resized_w, imgH))这里强制resize 当大于宽度320的图片直接resize 会变形，这个没有处理？

‍♂️ Environment (运行环境)

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Minimal Reproducible Example (最小可复现问题的Demo)

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