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| import os | |
| from typing import List, Tuple | |
| import cv2 | |
| import numpy as np | |
| from sklearn.model_selection import train_test_split | |
| import rasterio | |
| from pykelper.files_manager import DIRS | |
| # Define paths | |
| trainImagesPath = DIRS['TRAIN_FEATURES'] | |
| trainLabelsPath = DIRS['TRAIN_LABELS'] | |
| def read_tiff(file_path: str) -> np.ndarray: | |
| print('reading...') | |
| print(file_path) | |
| with rasterio.open(file_path) as src: | |
| image = src.read() | |
| # src.meta may hold interesting info not sure. | |
| return image | |
| def load_files_as_ndarray(folder_path, limit) -> List[Tuple[str, np.ndarray]]: | |
| # Load all images and labels | |
| # TODO: add preproc here or no? | |
| return [ | |
| (file_name, | |
| read_tiff( | |
| os.path.join(folder_path, file_name) | |
| ))for file_name in sorted(os.listdir(folder_path)[:limit]) | |
| ] | |
| def load_specific_file_as_ndarray(file_full_path): | |
| return read_tiff(file_full_path) | |