medsegmentanything_finetuning.py

# Initialize dictionary for storing image and label paths
data_paths = {}

# Create directories and print the number of images and masks in each
for dataset in datasets:
    for data_type in data_types:
        # Construct the directory path
        dir_path = os.path.join(base_dir, f'{dataset}_{data_type}')
        
        # Find images and labels in the directory
        files = sorted(glob.glob(os.path.join(dir_path, "*.nii.gz")))
        
        # Store the image and label paths in the dictionary
        data_paths[f'{dataset}_{data_type.split("_")[1]}'] = files

print('Number of training images', len(data_paths['train_images']))
print('Number of validation images', len(data_paths['val_images']))
print('Number of test images', len(data_paths['test_images']))