| import numpy as np | |
| from data_generator import RockGlacierDataGenerator | |
| import traceback | |
| gen = RockGlacierDataGenerator('datacollection/output/dataset/train/features', 'datacollection/output/dataset/train/masks', batch_size=8, target_size=(128, 128), augment=False) | |
| try: | |
| feature, mask = gen._load_pair(gen.feature_files[0], gen.mask_files[0]) | |
| print(f"File 0 feature shape: {feature.shape}, mask shape: {mask.shape}") | |
| except Exception as e: | |
| print(e) | |