generate_pos_neg_label_crop_centers No sampling location available.

[MOMOANNIE]

Hello, I used the training set for training in the process of segmenting nodules, and I can pass the entire code normally, but the result of dice is not good, so I screened the diameter of the nodules in the training set, and I eliminated the data with a diameter less than 5mm for training. When I trained again, when I cropped the training set with RandCropByPosNegLabeld, the following problems occurred:

train_transforms = Compose( [ LoadImaged(keys=["image", "label"]), AddChanneld(keys=["image", "label"]), Spacingd(keys=["image", "label"], pixdim=( 1.0, 1.0, 1.2), mode=("bilinear", "nearest")), # ResizeWithPadOrCropd(keys=["image", "label"], spatial_size=(256,256,128), mode=("constant")), Orientationd(keys=["image", "label"], axcodes="RAS"), ScaleIntensityRanged( keys=["image"], a_min=-125, a_max=275, b_min=0.0, b_max=1.0, clip=True, ), CropForegroundd(keys=["image", "label"], source_key='label', select_fn=lambda x: x > 0, margin=0), RandCropByPosNegLabeld( keys=["image", "label"], label_key="label", spatial_size=(96, 96, 96), pos=1, neg=1, num_samples=crop_samples, allow_smaller=True, ), RandShiftIntensityd( keys=["image"], offsets=0.10, prob=0.50, ), RandAffined( keys=['image', 'label'], mode=('bilinear', 'nearest'), prob=1.0, spatial_size=(96, 96, 96), rotate_range=(0, 0, np.pi / 30), scale_range=(0.1, 0.1, 0.1)), ToTensord(keys=["image", "label"]), ] ) val_transforms = Compose( [ LoadImaged(keys=["image", "label"]), AddChanneld(keys=["image", "label"]), Spacingd(keys=["image", "label"], pixdim=(1.0, 1.0, 1.2), mode=("bilinear", "nearest")), Orientationd(keys=["image", "label"], axcodes="RAS"), ScaleIntensityRanged( keys=["image"], a_min=-125, a_max=275, b_min=0.0, b_max=1.0, clip=True, ), CropForegroundd(keys=["image", "label"], source_key='label', select_fn=lambda x: x > 0, margin=0), ToTensord(keys=["image", "label"]), ] )

for step, batch in enumerate(epoch_iterator): File "/home/.local/lib/python3.9/site-packages/tqdm/std.py", line 1195, in iter for obj in iterable: File "/home/local/miniconda/envs/uxnet/lib/python3.9/site-packages/torch/utils/data/dataloader.py", line 681, in next data = self._next_data() File "/home/local/miniconda/envs/uxnet/lib/python3.9/site-packages/torch/utils/data/dataloader.py", line 1376, in _next_data return self._process_data(data) File "/home/local/miniconda/envs/uxnet/lib/python3.9/site-packages/torch/utils/data/dataloader.py", line 1402, in _process_data data.reraise() File "/home/local/miniconda/envs/uxnet/lib/python3.9/site-packages/torch/_utils.py", line 461, in reraise raise exception RuntimeError: Caught RuntimeError in DataLoader worker process 1. Original Traceback (most recent call last): File "/home/local/miniconda/envs/uxnet/lib/python3.9/site-packages/monai/transforms/transform.py", line 89, in apply_transform return _apply_transform(transform, data, unpack_items) File "/home/local/miniconda/envs/uxnet/lib/python3.9/site-packages/monai/transforms/transform.py", line 53, in _apply_transform return transform(parameters) File "/home/local/miniconda/envs/uxnet/lib/python3.9/site-packages/monai/transforms/croppad/dictionary.py", line 1171, in call self.randomize(label, fg_indices, bg_indices, image) File "/home/local/miniconda/envs/uxnet/lib/python3.9/site-packages/monai/transforms/croppad/dictionary.py", line 1153, in randomize self.centers = generate_pos_neg_label_crop_centers( File "/home/local/miniconda/envs/uxnet/lib/python3.9/site-packages/monai/transforms/utils.py", line 497, in generate_pos_neg_label_crop_centers raise ValueError("No sampling location available.") ValueError: No sampling location available. The above exception was the direct cause of the following exception: Traceback (most recent call last): File "/home/local/miniconda/envs/uxnet/lib/python3.9/site-packages/torch/utils/data/_utils/worker.py", line 302, in _worker_loop data = fetcher.fetch(index) File "/home/local/miniconda/envs/uxnet/lib/python3.9/site-packages/torch/utils/data/_utils/fetch.py", line 49, in fetch data = [self.dataset[idx] for idx in possibly_batched_index] File "/home/local/miniconda/envs/uxnet/lib/python3.9/site-packages/torch/utils/data/_utils/fetch.py", line 49, in data = [self.dataset[idx] for idx in possibly_batched_index] File "/home/local/miniconda/envs/uxnet/lib/python3.9/site-packages/monai/data/dataset.py", line 97, in getitem return self._transform(index) File "/home/local/miniconda/envs/uxnet/lib/python3.9/site-packages/monai/data/dataset.py", line 807, in _transform data = apply_transform(_transform, data) File "/home/local/miniconda/envs/uxnet/lib/python3.9/site-packages/monai/transforms/transform.py", line 113, in apply_transform raise RuntimeError(f"applying transform {transform}") from e RuntimeError: applying transform <monai.transforms.croppad.dictionary.RandCropByPosNegLabeld object at 0x7fc270415880>

What's going on with this?

[KumoLiu]

Hi @MOMOANNIE, the error message looks from line 557, could you please try to check the data before RandCropByPosNegLabeld?

MONAI/monai/transforms/utils.py

Line 557 in 28c9083

if len(fg_indices) == 0 and len(bg_indices) == 0: