| |
| import os |
| import glob |
| import rasterio |
| from rasterio.windows import Window |
| import numpy as np |
| import pandas as pd |
|
|
| FEATURE_DIR = r"D:\RockGlacier_Project\features" |
| MASK_DIR = r"D:\RockGlacier_Project\masks" |
| H_FEATURE_DIR = r"D:\RockGlacier_Project\harmonized_features" |
| H_MASK_DIR = r"D:\RockGlacier_Project\harmonized_masks" |
|
|
| os.makedirs(H_FEATURE_DIR, exist_ok=True) |
| os.makedirs(H_MASK_DIR, exist_ok=True) |
|
|
| feature_files = sorted(glob.glob(os.path.join(FEATURE_DIR, 'feature_*.tif'))) |
| mask_files = sorted(glob.glob(os.path.join(MASK_DIR, 'mask_*.tif'))) |
|
|
| def get_idx(filepath): |
| return os.path.basename(filepath).split('_')[1].split('.')[0] |
|
|
| mask_lookup = {get_idx(p): p for p in mask_files} |
|
|
| results = [] |
|
|
| print(f"Found {len(feature_files)} feature files and {len(mask_files)} mask files.") |
| print("Starting harmonization process...") |
|
|
| for f_path in feature_files: |
| idx = get_idx(f_path) |
| m_path = mask_lookup.get(idx) |
| |
| if not m_path: |
| continue |
| |
| with rasterio.open(f_path) as f_src, rasterio.open(m_path) as m_src: |
| |
| min_h = min(f_src.shape[0], m_src.shape[0]) |
| min_w = min(f_src.shape[1], m_src.shape[1]) |
| |
| f_window = Window(0, 0, min_w, min_h) |
| m_window = Window(0, 0, min_w, min_h) |
| |
| f_data = f_src.read(window=f_window) |
| m_data = m_src.read(1, window=m_window) |
| |
| f_meta = f_src.meta.copy() |
| m_meta = m_src.meta.copy() |
| |
| |
| f_transform = f_src.window_transform(f_window) |
| |
| f_meta.update({ |
| 'height': min_h, |
| 'width': min_w, |
| 'transform': f_transform |
| }) |
| |
| m_meta.update({ |
| 'height': min_h, |
| 'width': min_w, |
| 'transform': f_transform |
| }) |
| |
| out_f = os.path.join(H_FEATURE_DIR, f"feature_{idx}.tif") |
| out_m = os.path.join(H_MASK_DIR, f"mask_{idx}.tif") |
| |
| with rasterio.open(out_f, 'w', **f_meta) as dest: |
| dest.write(f_data) |
| |
| with rasterio.open(out_m, 'w', **m_meta) as dest: |
| dest.write(m_data, 1) |
| |
| results.append({ |
| 'idx': idx, |
| 'orig_f_shape': f_src.shape, |
| 'orig_m_shape': m_src.shape, |
| 'harmonized_shape': (min_h, min_w), |
| 'CRS_match': f_src.crs == m_src.crs |
| }) |
|
|
| df = pd.DataFrame(results) |
| print("\n--- Harmonization Complete ---") |
| print(f"Total processed pairs: {len(df)}") |
| mismatch_count = len(df[df['orig_f_shape'] != df['orig_m_shape']]) |
| print(f"Pairs that required cropping: {mismatch_count}") |
| print("\nSample metadata summary:") |
| print(df.head()) |
|
|
| summary_csv = os.path.join("D:\\RockGlacier_Project", "harmonization_summary.csv") |
| df.to_csv(summary_csv, index=False) |
| print(f"\nFull metadata summary saved to {summary_csv}") |
|
|
