Multiple Instance Learning (MIL) Examples RuntimeError: LoadImage cannot find a suitable reader for file

[DocandBean]

Describe the bug
Command

python -u panda_mil_train_evaluate_pytorch_gpu.py --data_root=/PandaChallenge2020/train_images --amp --distributed --mil_mode=att_trans --batch_size=4 --epochs=50 --logdir=./logs

generates

RuntimeError: LoadImage cannot find a suitable reader for file: /PandaChallenge2020/train_images/c2b4cc586b3984b248e7d095d4c0bd03.tiff.

Full error message below

To Reproduce
Steps to reproduce the behavior:

1. git clone MONAI tutorials
2. Install suggested required dependencies tifffile, imagecodecs (via pip) and downloaded Kaggle file per README
3. Install sklearn via pip
4. Run command 'python -u panda_mil_train_evaluate_pytorch_gpu.py --data_root=/PandaChallenge2020/train_images --amp --distributed --mil_mode=att_trans --batch_size=4 --epochs=50 --logdir=./logs'

Expected behavior
Train in multi-gpu mode with AMP using all available gpus, assuming the training images in /PandaChallenge2020/train_images folder, using pre-defined 80/20 data split

Environment (please complete the following information):

• OS: Ubuntu 20.04.4 LTS
• Python version: 3.9
• MONAI version: 0.9.1+14.g81fb7e41
• CUDA/cuDNN version: 11.6.0
• GPU models and configuration: NVIDIA A100

Additional context
Access/permissions to the file and the ImageLoader class do not seem to be the problem.

import os
import shutil
from monai.transforms import LoadImage
from monai.config import print_config

filename = 'PandaChallenge2020/train_images/c2b4cc586b3984b248e7d095d4c0bd03.tiff'

data, meta = LoadImage()(filename)

print(f"image data shape:{data.shape}")
print(f"meta data:{meta}")

from monai.data import WSIReader

data, meta = LoadImage(WSIReader)(filename)

print(f"image data shape:{data.shape}")
print(f"meta data:{meta}")

yields the following output

image data shape:(7424, 8448, 4)
meta data:{'spacing': array([0.00048619, 0.00048619]), original_affine: array([[-4.86187619e-04,  0.00000000e+00,  0.00000000e+00],
       [ 0.00000000e+00, -4.86187619e-04,  0.00000000e+00],
       [ 0.00000000e+00,  0.00000000e+00,  1.00000000e+00]]), space: RAS, affine: tensor([[-4.8619e-04,  0.0000e+00,  0.0000e+00],
        [ 0.0000e+00, -4.8619e-04,  0.0000e+00],
        [ 0.0000e+00,  0.0000e+00,  1.0000e+00]], dtype=torch.float64), spatial_shape: array([7424, 8448]), original_channel_dim: -1, 'filename_or_obj': 'PandaChallenge2020/train_images/c2b4cc586b3984b248e7d095d4c0bd03.tiff'}
image data shape:(3, 8448, 7424)
meta data:{'backend': 'cucim', 'original_channel_dim': 0, 'spatial_shape': array([8448, 7424]), 'num_patches': 1, 'path': '/home/dabean/MONAI_tutorials/tutorials/pathology/multiple_instance_learning/PandaChallenge2020/train_images/c2b4cc586b3984b248e7d095d4c0bd03.tiff', 'patch_location': array([0, 0]), 'patch_size': array([8448, 7424]), 'patch_level': 0, 'filename_or_obj': 'PandaChallenge2020/train_images/c2b4cc586b3984b248e7d095d4c0bd03.tiff', affine: tensor([[1., 0., 0., 0.],
        [0., 1., 0., 0.],
        [0., 0., 1., 0.],
        [0., 0., 0., 1.]], dtype=torch.float64), space: RAS}

Complete Error Output

python -u panda_mil_train_evaluate_pytorch_gpu.py --data_root=/PandaChallenge2020/train_images --amp --distributed --mil_mode=att_trans --batch_size=4 --epochs=50 --logdir=./logs
Argument values:
data_root => /PandaChallenge2020/train_images
dataset_json => None
num_classes => 5
mil_mode => att_trans
tile_count => 44
tile_size => 256
checkpoint => None
validate => False
logdir => ./logs
epochs => 50
batch_size => 4
optim_lr => 3e-05
weight_decay => 0
amp => True
val_every => 1
workers => 2
distributed => True
world_size => 1
rank => 0
dist_url => tcp://127.0.0.1:23456
dist_backend => nccl
quick => False
-----------------
Multigpu 1 rescaled lr 1.5e-05
0  gpu 0
Batch size is: 4 epochs 50
Dataset training: 8490 validation: 2124
The parameter 'pretrained' is deprecated since 0.13 and will be removed in 0.15, please use 'weights' instead.
Arguments other than a weight enum or `None` for 'weights' are deprecated since 0.13 and will be removed in 0.15. The current behavior is equivalent to passing `weights=ResNet50_Weights.IMAGENET1K_V1`. You can also use `weights=ResNet50_Weights.DEFAULT` to get the most up-to-date weights.
Writing Tensorboard logs to  ./logs
0 Wed Aug  3 17:53:21 2022 Epoch: 0
Traceback (most recent call last):
  File "/home/dabean/MONAI_tutorials/tutorials/pathology/multiple_instance_learning/panda_mil_train_evaluate_pytorch_gpu.py", line 547, in <module>
    mp.spawn(main_worker, nprocs=ngpus_per_node, args=(args,))
  File "/home/dabean/miniconda3/envs/MONAI_d01_env/lib/python3.9/site-packages/torch/multiprocessing/spawn.py", line 240, in spawn
    return start_processes(fn, args, nprocs, join, daemon, start_method='spawn')
  File "/home/dabean/miniconda3/envs/MONAI_d01_env/lib/python3.9/site-packages/torch/multiprocessing/spawn.py", line 198, in start_processes
    while not context.join():
  File "/home/dabean/miniconda3/envs/MONAI_d01_env/lib/python3.9/site-packages/torch/multiprocessing/spawn.py", line 160, in join
    raise ProcessRaisedException(msg, error_index, failed_process.pid)
torch.multiprocessing.spawn.ProcessRaisedException:

-- Process 0 terminated with the following error:
Traceback (most recent call last):
  File "/home/dabean/miniconda3/envs/MONAI_d01_env/lib/python3.9/site-packages/torch/multiprocessing/spawn.py", line 69, in _wrap
    fn(i, *args)
  File "/home/dabean/MONAI_tutorials/tutorials/pathology/multiple_instance_learning/panda_mil_train_evaluate_pytorch_gpu.py", line 414, in main_worker
    train_loss, train_acc = train_epoch(model, train_loader, optimizer, scaler=scaler, epoch=epoch, args=args)
  File "/home/dabean/MONAI_tutorials/tutorials/pathology/multiple_instance_learning/panda_mil_train_evaluate_pytorch_gpu.py", line 48, in train_epoch
    for idx, batch_data in enumerate(loader):
  File "/home/dabean/miniconda3/envs/MONAI_d01_env/lib/python3.9/site-packages/torch/utils/data/dataloader.py", line 652, in __next__
    data = self._next_data()
  File "/home/dabean/miniconda3/envs/MONAI_d01_env/lib/python3.9/site-packages/torch/utils/data/dataloader.py", line 1347, in _next_data
    return self._process_data(data)
  File "/home/dabean/miniconda3/envs/MONAI_d01_env/lib/python3.9/site-packages/torch/utils/data/dataloader.py", line 1373, in _process_data
    data.reraise()
  File "/home/dabean/miniconda3/envs/MONAI_d01_env/lib/python3.9/site-packages/torch/_utils.py", line 461, in reraise
    raise exception
RuntimeError: Caught RuntimeError in DataLoader worker process 0.
Original Traceback (most recent call last):
  File "/home/dabean/MONAI_install/MONAI/monai/transforms/transform.py", line 90, in apply_transform
    return _apply_transform(transform, data, unpack_items)
  File "/home/dabean/MONAI_install/MONAI/monai/transforms/transform.py", line 54, in _apply_transform
    return transform(parameters)
  File "/home/dabean/MONAI_install/MONAI/monai/transforms/io/dictionary.py", line 133, in __call__
    data = self._loader(d[key], reader)
  File "/home/dabean/MONAI_install/MONAI/monai/transforms/io/array.py", line 245, in __call__
    raise RuntimeError(
RuntimeError: LoadImage cannot find a suitable reader for file: /PandaChallenge2020/train_images/c2b4cc586b3984b248e7d095d4c0bd03.tiff.
    Please install the reader libraries, see also the installation instructions:
    https://docs.monai.io/en/latest/installation.html#installing-the-recommended-dependencies.
   The current registered: [<monai.data.image_reader.PydicomReader object at 0x7f0d64ae22b0>, <monai.data.image_reader.ITKReader object at 0x7f0c56023940>, <monai.data.image_reader.NrrdReader object at 0x7f0c56023970>, <monai.data.image_reader.NumpyReader object at 0x7f0c56023a00>, <monai.data.image_reader.PILReader object at 0x7f0c55bc9250>, <monai.data.image_reader.NibabelReader object at 0x7f0c55bc9340>, <monai.data.wsi_reader.WSIReader object at 0x7f0c55bc93d0>].
Traceback (most recent call last):
  File "/home/dabean/MONAI_install/MONAI/monai/transforms/io/array.py", line 230, in __call__
    img = reader.read(filename)
  File "/home/dabean/MONAI_install/MONAI/monai/data/wsi_reader.py", line 347, in read
    return self.reader.read(data=data, **kwargs)
  File "/home/dabean/MONAI_install/MONAI/monai/data/wsi_reader.py", line 428, in read
    wsi = CuImage(filename, **kwargs_)
ValueError: Cannot open /PandaChallenge2020/train_images/c2b4cc586b3984b248e7d095d4c0bd03.tiff!

Traceback (most recent call last):
  File "/home/dabean/miniconda3/envs/MONAI_d01_env/lib/python3.9/site-packages/nibabel/loadsave.py", line 90, in load
    stat_result = os.stat(filename)
FileNotFoundError: [Errno 2] No such file or directory: '/PandaChallenge2020/train_images/c2b4cc586b3984b248e7d095d4c0bd03.tiff'

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/dabean/MONAI_install/MONAI/monai/transforms/io/array.py", line 230, in __call__
    img = reader.read(filename)
  File "/home/dabean/MONAI_install/MONAI/monai/data/image_reader.py", line 912, in read
    img = nib.load(name, **kwargs_)
  File "/home/dabean/miniconda3/envs/MONAI_d01_env/lib/python3.9/site-packages/nibabel/loadsave.py", line 92, in load
    raise FileNotFoundError(f"No such file or no access: '{filename}'")
FileNotFoundError: No such file or no access: '/PandaChallenge2020/train_images/c2b4cc586b3984b248e7d095d4c0bd03.tiff'

Traceback (most recent call last):
  File "/home/dabean/MONAI_install/MONAI/monai/transforms/io/array.py", line 230, in __call__
    img = reader.read(filename)
  File "/home/dabean/MONAI_install/MONAI/monai/data/image_reader.py", line 1167, in read
    img = PILImage.open(name, **kwargs_)
TypeError: open() got an unexpected keyword argument 'backend'

Traceback (most recent call last):
  File "/home/dabean/MONAI_install/MONAI/monai/transforms/io/array.py", line 230, in __call__
    img = reader.read(filename)
  File "/home/dabean/MONAI_install/MONAI/monai/data/image_reader.py", line 1074, in read
    img = np.load(name, allow_pickle=True, **kwargs_)
TypeError: load() got an unexpected keyword argument 'backend'

Traceback (most recent call last):
  File "/home/dabean/MONAI_install/MONAI/monai/transforms/io/array.py", line 230, in __call__
    img = reader.read(filename)
  File "/home/dabean/MONAI_install/MONAI/monai/data/image_reader.py", line 1548, in read
    nrrd_image = NrrdImage(*nrrd.read(name, index_order=self.index_order, *kwargs_))
TypeError: read() got multiple values for argument 'index_order'

Traceback (most recent call last):
  File "/home/dabean/MONAI_install/MONAI/monai/transforms/io/array.py", line 230, in __call__
    img = reader.read(filename)
  File "/home/dabean/MONAI_install/MONAI/monai/data/image_reader.py", line 267, in read
    img_.append(itk.imread(name, **kwargs_))
TypeError: imread() got an unexpected keyword argument 'backend'

Traceback (most recent call last):
  File "/home/dabean/MONAI_install/MONAI/monai/transforms/io/array.py", line 230, in __call__
    img = reader.read(filename)
  File "/home/dabean/MONAI_install/MONAI/monai/data/image_reader.py", line 481, in read
    ds = pydicom.dcmread(fp=name, **kwargs_)
TypeError: dcmread() got an unexpected keyword argument 'backend'


The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/home/dabean/MONAI_install/MONAI/monai/transforms/transform.py", line 90, in apply_transform
    return _apply_transform(transform, data, unpack_items)
  File "/home/dabean/MONAI_install/MONAI/monai/transforms/transform.py", line 54, in _apply_transform
    return transform(parameters)
  File "/home/dabean/MONAI_install/MONAI/monai/transforms/compose.py", line 173, in __call__
    input_ = apply_transform(_transform, input_, self.map_items, self.unpack_items, self.log_stats)
  File "/home/dabean/MONAI_install/MONAI/monai/transforms/transform.py", line 114, in apply_transform
    raise RuntimeError(f"applying transform {transform}") from e
RuntimeError: applying transform <monai.transforms.io.dictionary.LoadImaged object at 0x7f0d64a66e80>

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/home/dabean/miniconda3/envs/MONAI_d01_env/lib/python3.9/site-packages/torch/utils/data/_utils/worker.py", line 302, in _worker_loop
    data = fetcher.fetch(index)
  File "/home/dabean/miniconda3/envs/MONAI_d01_env/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/dabean/miniconda3/envs/MONAI_d01_env/lib/python3.9/site-packages/torch/utils/data/_utils/fetch.py", line 49, in <listcomp>
    data = [self.dataset[idx] for idx in possibly_batched_index]
  File "/home/dabean/MONAI_install/MONAI/monai/data/dataset.py", line 105, in __getitem__
    return self._transform(index)
  File "/home/dabean/MONAI_install/MONAI/monai/data/dataset.py", line 91, in _transform
    return apply_transform(self.transform, data_i) if self.transform is not None else data_i
  File "/home/dabean/MONAI_install/MONAI/monai/transforms/transform.py", line 114, in apply_transform
    raise RuntimeError(f"applying transform {transform}") from e
RuntimeError: applying transform <monai.transforms.compose.Compose object at 0x7f0d64469bb0>

[wyli]

Mainly this issue "ValueError: Cannot open /PandaChallenge2020/train_images/c2b4cc586b3984b248e7d095d4c0bd03.tiff", looks like you should remove the first / in the folder path. Or please double-check the absolute file path.

[DocandBean]

Solved. Consider updating the readme