| import os | |
| import h5py | |
| import numpy as np | |
| from tqdm import tqdm | |
| import DeepDeformationMapRegistration.utils.constants as C | |
| os.environ['CUDA_VISIBLE_DEVICES'] = '0' | |
| LITS_NONE = '/mnt/EncryptedData1/Users/javier/vessel_registration/LiTS/None' | |
| LITS_TRANS = '/mnt/EncryptedData1/Users/javier/vessel_registration/LiTS/Translation' | |
| LITS_AFFINE = '/mnt/EncryptedData1/Users/javier/vessel_registration/LiTS/Affine' | |
| IMG_SHAPE = (64, 64, 64, 1) | |
| for dataset in [LITS_NONE, LITS_AFFINE, LITS_TRANS]: | |
| dataset_files = [os.path.join(dataset, d) for d in os.listdir(dataset) if os.path.isfile(os.path.join(dataset, d))] | |
| f_iter = tqdm(dataset_files) | |
| f_iter.set_description('Analyzing ' + dataset) | |
| inv_shape_count = 0 | |
| inv_type_count = 0 | |
| for i, d in enumerate(f_iter): | |
| f = h5py.File(d, 'r') | |
| if f[C.H5_FIX_IMG][:].shape != IMG_SHAPE: | |
| print(d + ' Invalid FIX IMG. Shape: ' + str(f[C.H5_FIX_IMG][:].shape)) | |
| inv_shape_count += 1 | |
| if f[C.H5_MOV_IMG][:].shape != IMG_SHAPE: | |
| print(d + ' Invalid MOV IMG. Shape: ' + str(f[C.H5_MOV_IMG][:].shape)) | |
| inv_shape_count += 1 | |
| if f[C.H5_FIX_PARENCHYMA_MASK][:].shape != IMG_SHAPE: | |
| print(d + ' Invalid FIX PARENCHYMA. Shape: ' + str(f[C.H5_FIX_PARENCHYMA_MASK][:].shape)) | |
| inv_shape_count += 1 | |
| if f[C.H5_MOV_PARENCHYMA_MASK][:].shape != IMG_SHAPE: | |
| print(d + ' Invalid MOV PARENCHYMA. Shape: ' + str(f[C.H5_MOV_PARENCHYMA_MASK][:].shape)) | |
| inv_shape_count += 1 | |
| if f[C.H5_FIX_TUMORS_MASK][:].shape != IMG_SHAPE: | |
| print(d + ' Invalid FIX TUMORS. Shape: ' + str(f[C.H5_FIX_TUMORS_MASK][:].shape)) | |
| inv_shape_count += 1 | |
| if f[C.H5_MOV_TUMORS_MASK][:].shape != IMG_SHAPE: | |
| print(d + ' Invalid MOV TUMORS. Shape: ' + str(f[C.H5_MOV_TUMORS_MASK][:].shape)) | |
| inv_shape_count += 1 | |
| if f[C.H5_FIX_IMG][:].dtype != np.float32: | |
| print(d + ' Invalid FIX IMG. Type: ' + str(f[C.H5_FIX_IMG][:].dtype)) | |
| inv_type_count += 1 | |
| if f[C.H5_MOV_IMG][:].dtype != np.float32: | |
| print(d + ' Invalid MOV IMG. Type: ' + str(f[C.H5_MOV_IMG][:].dtype)) | |
| inv_type_count += 1 | |
| if f[C.H5_FIX_PARENCHYMA_MASK][:].dtype != np.float32: | |
| print(d + ' Invalid FIX PARENCHYMA. Type: ' + str(f[C.H5_FIX_PARENCHYMA_MASK][:].dtype)) | |
| inv_type_count += 1 | |
| if f[C.H5_MOV_PARENCHYMA_MASK][:].dtype != np.float32: | |
| print(d + ' Invalid MOV PARENCHYMA. Type: ' + str(f[C.H5_MOV_PARENCHYMA_MASK][:].dtype)) | |
| inv_type_count += 1 | |
| if f[C.H5_FIX_TUMORS_MASK][:].dtype != np.float32: | |
| print(d + ' Invalid FIX TUMORS. Type: ' + str(f[C.H5_FIX_TUMORS_MASK][:].dtype)) | |
| inv_type_count += 1 | |
| if f[C.H5_MOV_TUMORS_MASK][:].dtype != np.float32: | |
| print(d + ' Invalid MOV TUMORS. Type: ' + str(f[C.H5_MOV_TUMORS_MASK][:].dtype)) | |
| inv_type_count += 1 | |
| print('\n\n>>>>SUMMARY ' + dataset) | |
| print('\t\tInvalid shape: ' + str(inv_shape_count) + '\n\t\tInvalid type: ' + str(inv_type_count)) | |