Albumentations error

[pedrozamboni]

Hey, Im having some issues while trying to use Albumentations direct on my config file. I always get this error:

File "tools/train.py", line 247, in
main()
File "tools/train.py", line 236, in main
train_detector(
File "/home/pedro/Documents/Documents/mmdetection-2.28.2/mmdet/apis/train.py", line 246, in train_detector
runner.run(data_loaders, cfg.workflow)
File "/home/pedro/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 136, in run
epoch_runner(data_loaders[i], **kwargs)
File "/home/pedro/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmcv/runner/epoch_based_runner.py", line 49, in train
for i, data_batch in enumerate(self.data_loader):
File "/home/pedro/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 634, in next
data = self._next_data()
File "/home/pedro/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 1346, in _next_data
return self._process_data(data)
File "/home/pedro/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/dataloader.py", line 1372, in _process_data
data.reraise()
File "/home/pedro/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/_utils.py", line 644, in reraise
raise exception
ValueError: Caught ValueError in DataLoader worker process 0.
Original Traceback (most recent call last):
File "/home/pedro/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/_utils/worker.py", line 308, in _worker_loop
data = fetcher.fetch(index)
File "/home/pedro/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 51, in fetch
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/pedro/anaconda3/envs/openmmlab/lib/python3.8/site-packages/torch/utils/data/_utils/fetch.py", line 51, in
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/home/pedro/Documents/Documents/mmdetection-2.28.2/mmdet/datasets/custom.py", line 220, in getitem
data = self.prepare_train_img(idx)
File "/home/pedro/Documents/Documents/mmdetection-2.28.2/mmdet/datasets/custom.py", line 243, in prepare_train_img
return self.pipeline(results)
File "/home/pedro/Documents/Documents/mmdetection-2.28.2/mmdet/datasets/pipelines/compose.py", line 41, in call
data = t(data)
File "/home/pedro/Documents/Documents/mmdetection-2.28.2/mmdet/datasets/pipelines/transforms.py", line 1487, in call
results = self.aug(**results)
File "/home/pedro/anaconda3/envs/openmmlab/lib/python3.8/site-packages/albumentations/core/composition.py", line 304, in call
self.preprocess(data)
File "/home/pedro/anaconda3/envs/openmmlab/lib/python3.8/site-packages/albumentations/core/composition.py", line 331, in preprocess
raise ValueError(msg)
ValueError: Key img_info is not in available keys.

I`m using a custom dataset and a custom loading functions to open npy files with 5 bands.

This is my loading func:

class LoadImageFromNumpy(object):
"""Load an image from file.

Required keys are "img_prefix" and "img_info" (a dict that must contain the
key "filename"). Added or updated keys are "filename", "img", "img_shape",
"ori_shape" (same as `img_shape`), "pad_shape" (same as `img_shape`),
"scale_factor" (1.0) and "img_norm_cfg" (means=0 and stds=1).

Args:
    to_float32 (bool): Whether to convert the loaded image to a float32
        numpy array. If set to False, the loaded image is an uint8 array.
        Defaults to False.
    color_type (str): The flag argument for :func:`mmcv.imfrombytes`.
        Defaults to 'color'.
    file_client_args (dict): Arguments to instantiate a FileClient.
        See :class:`mmcv.fileio.FileClient` for details.
        Defaults to ``dict(backend='disk')``.
    imdecode_backend (str): Backend for :func:`mmcv.imdecode`. Default:
        'cv2'
"""

def __init__(self,
             to_float32=False,
             color_type='color',
             file_client_args=dict(backend='disk'),
             imdecode_backend='numpy',
             bands=[0,1,2],
             ):
    self.to_float32 = to_float32
    self.color_type = color_type
    self.file_client_args = file_client_args.copy()
    self.file_client = None
    self.imdecode_backend = imdecode_backend
    self.bands = bands

def __call__(self, results):
    """Call functions to load image and get image meta information.

    Args:
        results (dict): Result dict from :obj:`mmseg.CustomDataset`.

    Returns:
        dict: The dict contains loaded image and meta information.
    """

    if self.file_client is None:
        self.file_client = mmcv.FileClient(**self.file_client_args)

    if results.get('img_prefix') is not None:
        filename = osp.join(results['img_prefix'],
                            results['img_info']['filename'])
    else:
        filename = results['img_info']['filename']

    #img_bytes = np.load(filename.replace('.png','.npy'))
    #print(filename.replace('.png','.npy'))
    img_bytes = np.load(filename)
    img = img_bytes[:,:,self.bands]
    if self.to_float32:
        img = img.astype(np.float32)

    results['filename'] = filename
    results['ori_filename'] = results['img_info']['filename']
    results['img'] = img
    results['img_shape'] = img.shape
    results['ori_shape'] = img.shape
    # Set initial values for default meta_keys
    results['pad_shape'] = img.shape
    #results['scale_factor'] = 1.0
    num_channels = 1 if len(img.shape) < 3 else img.shape[2]

    return results

Environment
/home/pedro/anaconda3/envs/openmmlab/lib/python3.8/site-packages/mmcv/init.py:20: UserWarning: On January 1, 2023, MMCV will release v2.0.0, in which it will remove components related to the training process and add a data transformation module. In addition, it will rename the package names mmcv to mmcv-lite and mmcv-full to mmcv. See https://github.com/open-mmlab/mmcv/blob/master/docs/en/compatibility.md for more details.
warnings.warn(
fatal: not a git repository (or any parent up to mount point /)
Stopping at filesystem boundary (GIT_DISCOVERY_ACROSS_FILESYSTEM not set).
sys.platform: linux
Python: 3.8.19 | packaged by conda-forge | (default, Mar 20 2024, 12:47:35) [GCC 12.3.0]
CUDA available: True
GPU 0: NVIDIA GeForce RTX 3090 Ti
CUDA_HOME: /usr
NVCC: Cuda compilation tools, release 11.5, V11.5.119
GCC: gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0
PyTorch: 2.0.0+cu118
PyTorch compiling details: PyTorch built with:

• GCC 9.3
• C++ Version: 201703
• Intel(R) oneAPI Math Kernel Library Version 2022.2-Product Build 20220804 for Intel(R) 64 architecture applications
• Intel(R) MKL-DNN v2.7.3 (Git Hash 6dbeffbae1f23cbbeae17adb7b5b13f1f37c080e)
• OpenMP 201511 (a.k.a. OpenMP 4.5)
• LAPACK is enabled (usually provided by MKL)
• NNPACK is enabled
• CPU capability usage: AVX2
• CUDA Runtime 11.8
• NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86;-gencode;arch=compute_90,code=sm_90
• CuDNN 8.7
• Magma 2.6.1
• Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.8, CUDNN_VERSION=8.7.0, CXX_COMPILER=/opt/rh/devtoolset-9/root/usr/bin/c++, CXX_FLAGS= -D_GLIBCXX_USE_CXX11_ABI=0 -fabi-version=11 -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -DNDEBUG -DUSE_KINETO -DLIBKINETO_NOROCTRACER -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -O2 -fPIC -Wall -Wextra -Werror=return-type -Werror=non-virtual-dtor -Werror=bool-operation -Wnarrowing -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wunused-local-typedefs -Wno-unused-parameter -Wno-unused-function -Wno-unused-result -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Werror=cast-function-type -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_DISABLE_GPU_ASSERTS=ON, TORCH_VERSION=2.0.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=1, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF,

TorchVision: 0.15.1+cu118
OpenCV: 4.10.0
MMCV: 1.7.2
MMCV Compiler: GCC 9.3
MMCV CUDA Compiler: 11.8
MMDetection: 2.28.2+