我去将mask和lable缩小8倍，因为模型中有3层卷积层步数为2。
def __getitem__(self, idx):
label = copy.deepcopy(self._labels[idx]) # label modified in transform
image = cv2.imread(os.path.join(self._images_folder, label['img_paths']), cv2.IMREAD_COLOR)
mask = np.ones(shape=(label['img_height'], label['img_width']), dtype=np.float32)
mask = get_mask(label['segmentations'], mask)
sample = {
'label': label,
'image': image,
'mask': mask
}
if self._transform:
sample = self._transform(sample)
mask = cv2.resize(sample['mask'], dsize=None, fx=1/self._stride, fy=1/self._stride, interpolation=cv2.INTER_AREA)
记事本缩小8倍。
标签：cv2,self,._,mask,label,sample,stride,lightweight,openpose From： https://www.cnblogs.com/hahaah/p/17093934.html