pytorch ValueError:图像的高度和宽度,蒙版或蒙版应该相等,通过设置合成类的is_check_shapes=False来禁用形状检查

rvpgvaaj  于 11个月前  发布在  其他
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我想提一下,变换前图像的形状是:
| | Shape |
| --|--|
| 原始图像|(360,640,3)|
| 原始掩膜|(360,640)|
| 变换图像|(320,320,3)|
| 变换掩模|(320,320)|
img_trans定义为:

img_trans = A.Compose([
    A.Resize(a_config.INPUT_IMAGE_HEIGHT, a_config.INPUT_IMAGE_WIDTH)],
    is_check_shapes=False
)

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代码片段是:

def image_mask_transformation(image, mask, img_trans, aug_trans=None, normalize=True,
                              var_min=10, var_max=400):

    
    
    print("Original image shape:", image.shape)
    transformed = img_trans(image=image, mask=mask)
    image = transformed["image"]
    mask = transformed["mask"]
    print("transformed image shape:", image.shape)
    # image, mask still uint 8 in 0, 255 range


但我得到了一个错误:

ValueError: Caught ValueError in DataLoader worker process 0.
Original Traceback (most recent call last):
  File "/usr/local/lib/python3.10/dist-packages/torch/utils/data/_utils/worker.py", line 308, in _worker_loop
    data = fetcher.fetch(index)
  File "/usr/local/lib/python3.10/dist-packages/torch/utils/data/_utils/fetch.py", line 51, in fetch
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File "/usr/local/lib/python3.10/dist-packages/torch/utils/data/_utils/fetch.py", line 51, in <listcomp>
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File "/content/drive/MyDrive/Colab Notebooks/CRACK500/tool/dataset.py", line 131, in __getitem__
    image_store, mask_store = image_mask_transformation(image, mask, self.img_trans, aug_trans=self.aug_trans,
  File "/content/drive/MyDrive/Colab Notebooks/CRACK500/tool/dataset.py", line 40, in image_mask_transformation
    transformed = img_trans(image=image, mask=mask)
  File "/usr/local/lib/python3.10/dist-packages/albumentations/core/composition.py", line 195, in __call__
    self._check_args(**data)
  File "/usr/local/lib/python3.10/dist-packages/albumentations/core/composition.py", line 286, in _check_args
    raise ValueError(
ValueError: Height and Width of image, mask or masks should be equal. You can disable shapes check by setting a parameter is_check_shapes=False of Compose class (do it only if you are sure about your data consistency)..


我不确定我是否得到了错误,因为最初的第三维是图像而不是掩码。因此,我试图在定义img_trans时添加is_check_shapes=False,但我仍然得到错误。
你能建议我是否应该在哪里添加is_check_shapes=False,或者错误可以通过其他方式解决吗?

tsm1rwdh

tsm1rwdh1#

这是旧的,但我有一个问题,我在执行转换之前改变了我的图像/遮罩的尺寸。在我的例子中,我在我的pytorch数据集中转换之前先将图像转换为通道。
我有这个:

def __getitem__(self, idx):
  ...
  if self.channel_first:
        image = np.transpose(image, (2, 0, 1)).astype(np.float32)
        mask = np.transpose(mask, (2, 0, 1)).astype(np.float32)

    if self.transform:
        transformed = self.transform(image=image, mask=mask)
        image = transformed["image"]
        mask = transformed["mask"]

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我本该得到这个的

def __getitem__(self, idx):
   ...

    if self.transform:
        transformed = self.transform(image=image, mask=mask)
        image = transformed["image"]
        mask = transformed["mask"]

    if self.channel_first:
        image = np.transpose(image, (2, 0, 1)).astype(np.float32)
        mask = np.transpose(mask, (2, 0, 1)).astype(np.float32)

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