| import pandas as pd |
| import warnings |
| warnings.filterwarnings('ignore') |
|
|
| csv_path = "/data1/nasiruddink/rockglacier/RockGlacierNet/patch_dataset/patches_128/metadata/patch_metadata.csv" |
| df = pd.read_csv(csv_path) |
|
|
| |
| kept = df[df["kept_or_filtered"] == "kept"].copy() |
|
|
| |
| bins = [-1, 0.0, 0.1, 1.0, 2.0, 5.0, 10.0, 100.0] |
| labels = [ |
| "0% (Pure Background)", |
| "0.01% - 0.1% (Trace)", |
| "0.1% - 1.0%", |
| "1.0% - 2.0%", |
| "2.0% - 5.0%", |
| "5.0% - 10.0%", |
| "> 10.0% (Good Coverage)" |
| ] |
|
|
| kept['coverage_bin'] = pd.cut(kept['glacier_percentage'], bins=bins, labels=labels) |
| counts = kept['coverage_bin'].value_counts(sort=False) |
| percentages = (counts / len(kept)) * 100 |
|
|
| print("\nROCK GLACIER COVERAGE ANALYSIS OF KEPT PATCHES:") |
| print("=" * 65) |
| print(f"{'Coverage Range':<25} | {'Count':<10} | {'Percentage of Dataset':<20}") |
| print("-" * 65) |
| for label in labels: |
| print(f"{label:<25} | {counts[label]:<10} | {percentages[label]:.1f}%") |
| print("=" * 65) |
| print(f"Total Kept Patches: {len(kept)}\n") |
|
|
| |
| threshold = 1.0 |
| retained = len(kept[kept['glacier_percentage'] >= threshold]) + len(kept[kept['glacier_percentage'] == 0.0]) |
| print(f"If you set MIN_GLACIER_PERCENTAGE = {threshold}% in config.py:") |
| print(f"- You would drop {(len(kept) - retained)} patches with trace/negligible glacier pixels.") |
| print(f"- The new dataset size would be {retained} patches.") |
|
|
