File "/home/bnua213/miniconda3/envs/cg/lib/python3.8/runpy.py", line 194, in _run_module_as_main return _run_code(code, main_globals, None, File "/home/bnua213/miniconda3/envs/cg/lib/python3.8/runpy.py", line 87, in _run_code exec(code, run_globals) File "/home/bnua213/cg/neurecon/train.py", line 294, in <module> main_function(config) File "/home/bnua213/cg/neurecon/train.py", line 160, in main_function logger.add_imgs(to_img(target_rgb), 'val/gt_rgb', it) File "/home/bnua213/cg/neurecon/utils/rend_util.py", line 239, in lin2img assert num_samples == H * W AssertionError 为什么报错只有一个AssertionError

`AssertionError`是一个断言错误，它会在断言语句的条件为False时触发。在你提供的错误信息中，报错的位置在文件`rend_util.py`的第239行，具体代码如下：

assert num_samples == H * W

这个断言语句要求`num_samples`的值必须等于`H * W`。然而，在运行时，这个条件没有得到满足，所以断言失败，触发了`AssertionError`。

可能的原因是你的代码逻辑有误或者输入数据不符合预期。你可以检查一下相应的变量和数据，确保它们的值是正确的，并满足该断言条件。如果需要，你还可以添加适当的错误处理机制或调整代码逻辑来避免这个错误。

相关问题

TypeError: Caught TypeError in DataLoader worker process 0. Original Traceback (most recent call last): File "/root/miniconda3/envs/py38/lib/python3.8/site-packages/torch/utils/data/_utils/worker.py", line 287, in _worker_loop data = fetcher.fetch(index) File "/root/miniconda3/envs/py38/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 49, in fetch data = [self.dataset[idx] for idx in possibly_batched_index] File "/root/miniconda3/envs/py38/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 49, in <listcomp> data = [self.dataset[idx] for idx in possibly_batched_index] File "/root/ConvNeXt/my_dataset.py", line 40, in __getitem__ img = self.transform(a) File "/root/miniconda3/envs/py38/lib/python3.8/site-packages/torchvision/transforms/transforms.py", line 95, in __call__ img = t(img) File "/root/miniconda3/envs/py38/lib/python3.8/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl return forward_call(*input, **kwargs) File "/root/miniconda3/envs/py38/lib/python3.8/site-packages/torchvision/transforms/transforms.py", line 952, in forward i, j, h, w = self.get_params(img, self.scale, self.ratio) File "/root/miniconda3/envs/py38/lib/python3.8/site-packages/torchvision/transforms/transforms.py", line 913, in get_params width, height = F.get_image_size(img) File "/root/miniconda3/envs/py38/lib/python3.8/site-packages/torchvision/transforms/functional.py", line 76, in get_image_size return F_pil.get_image_size(img) File "/root/miniconda3/envs/py38/lib/python3.8/site-packages/torchvision/transforms/functional_pil.py", line 27, in get_image_size raise TypeError(f"Unexpected type {type(img)}") TypeError: Unexpected type <class 'numpy.ndarray'>

这个错误是由于在 DataLoader 的 worker 进程中，数据集中的某个样本在进行 transform 时出现了错误。具体来说，是由于 get_image_size 函数期望的 PIL.Image 对象被传入了一个 numpy 数组。你可以检查一下数据集中的这个样本，看看是否正确加载，并且检查一下 transform 中是否使用了正确的数据类型。

The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/root/miniconda3/envs/py38/lib/python3.8/site-packages/torch/utils/data/_utils/worker.py", line 287, in _worker_loop data = fetcher.fetch(index) File "/root/miniconda3/envs/py38/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 49, in fetch data = [self.dataset[idx] for idx in possibly_batched_index] File "/root/miniconda3/envs/py38/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 49, in <listcomp> data = [self.dataset[idx] for idx in possibly_batched_index] File "/root/ConvNeXt/my_dataset.py", line 33, in __getitem__ a = Image.fromarray(a) File "/root/miniconda3/envs/py38/lib/python3.8/site-packages/PIL/Image.py", line 2955, in fromarray raise TypeError("Cannot handle this data type: %s, %s" % typekey) from e TypeError: Cannot handle this data type: (1, 1, 47), |u1

这是一个错误信息，看起来是在使用 PyTorch 的 DataLoader 时出现了问题。具体来说，可能是在调用自定义的数据集类时，数据集中的一些图片数据类型不被支持。建议检查数据集类中的图片读取部分，确保图片数据类型正确，并且与 DataLoader 的参数相匹配。如果问题仍然存在，可以尝试打印出出错的图片的具体信息，以便更好地排查问题。