| """ |
| Band-combination sweep: train + evaluate each combo, save checkpoints, collect |
| results. Runs on the patches in --data-dir (default all_data/patches). Patch size |
| is auto-detected by train.py / evaluate.py, so the SAME runner works for the |
| 64 px (30 m) set now and the 128 px (10 m) set later — just point --data-dir at |
| the new patches. |
| |
| python run_experiments.py --gpu 1 |
| python run_experiments.py --gpu 1 --only f17_proven,f17_standard,f17_optical |
| python run_experiments.py --gpu 1 --data-dir all_data/patches --force |
| |
| Each combo writes all_data/checkpoint_<name>/ and all_data/result_<name>/. |
| Already-finished combos are skipped (resume-friendly) unless --force. |
| At the end it prints + saves the comparison table (all_data/runs_comparison.csv). |
| """ |
|
|
| import os |
| import sys |
| import argparse |
| import subprocess |
|
|
| HERE = os.path.dirname(os.path.abspath(__file__)) |
| RUN_GPU = os.path.join(HERE, "run_gpu.sh") |
|
|
| |
| COMBOS = { |
| |
| "f17_proven": ["TPI", "ROUGHNESS", "LST_winter", "NDWI", "LST_summer", "REL_RELIEF", |
| "ASPECT", "LST_anomaly", "ELEV_COP", "B2", "HILLSHADE", "B8A", "NDMI", "B12", "B3", "B4", "B8"], |
| "f17_standard": ["TPI", "SLOPE", "LST_winter", "NDVI", "LST_summer", "REL_RELIEF", |
| "ASPECT", "LST_anomaly", "ELEV_COP", "B2", "HILLSHADE", "B8A", "NDMI", "B11", "B3", "B4", "B8"], |
| "f17_optical": ["B2", "B3", "B4", "B8", "B8A", "B11", "B12", "NDVI", "NDWI", "NDMI", "NDSI", "BSI", |
| "ELEV_COP", "SLOPE", "TPI", "LST_winter", "LST_summer"], |
| |
| "f17_terrain": ["TPI", "ROUGHNESS", "TRI", "SLOPE", "ASPECT", "HILLSHADE", "CURVATURE", "REL_RELIEF", |
| "ELEV_COP", "LST_winter", "LST_summer", "LST_anomaly", "B2", "B4", "B8", "NDWI", "NDVI"], |
| "f17_no_thermal": ["TPI", "ROUGHNESS", "SLOPE", "ASPECT", "REL_RELIEF", "HILLSHADE", "CURVATURE", |
| "ELEV_COP", "B2", "B3", "B4", "B8", "B8A", "B11", "B12", "NDWI", "NDVI"], |
| "f16_balanced": ["TPI", "ROUGHNESS", "REL_RELIEF", "ELEV_COP", "SLOPE", "ASPECT", "LST_winter", "LST_summer", |
| "NDWI", "NDVI", "NDMI", "B2", "B3", "B4", "B8", "B12"], |
| "f20_rich": ["TPI", "ROUGHNESS", "LST_winter", "NDWI", "LST_summer", "REL_RELIEF", "ASPECT", "LST_anomaly", |
| "ELEV_COP", "B2", "HILLSHADE", "B8A", "NDMI", "B12", "B3", "B4", "B8", "NDVI", "SLOPE", "B11"], |
| "f14_lean": ["TPI", "ROUGHNESS", "LST_winter", "NDWI", "LST_summer", "REL_RELIEF", "ASPECT", |
| "ELEV_COP", "B2", "B8A", "NDMI", "B12", "B4", "B8"], |
| "f12_core": ["TPI", "ROUGHNESS", "LST_winter", "LST_summer", "REL_RELIEF", "ASPECT", |
| "ELEV_COP", "B2", "B8", "NDWI", "NDMI", "B12"], |
| |
| "all": None, |
| } |
|
|
|
|
| def dirs_for(name): |
| ck = "all_data/checkpoint" if name == "all" else f"all_data/checkpoint_{name}" |
| rs = "all_data/result" if name == "all" else f"all_data/result_{name}" |
| return os.path.join(HERE, ck), os.path.join(HERE, rs) |
|
|
|
|
| def run_step(script, env, log_path): |
| os.makedirs(os.path.dirname(log_path), exist_ok=True) |
| with open(log_path, "w") as lf: |
| r = subprocess.run([RUN_GPU, script], cwd=HERE, env=env, |
| stdout=lf, stderr=subprocess.STDOUT) |
| return r.returncode |
|
|
|
|
| def run_one(name, bands, gpu, data_dir, force): |
| ckpt_dir, result_dir = dirs_for(name) |
| weights = os.path.join(ckpt_dir, "best_model.weights.h5") |
| metrics = os.path.join(result_dir, "metrics.json") |
|
|
| env = os.environ.copy() |
| env["CUDA_VISIBLE_DEVICES"] = str(gpu) |
| env["DATA_DIR"] = data_dir |
| env["RUN_NAME"] = name |
| env.pop("BANDS", None) |
| if bands is None: |
| env.pop("BAND_LIST", None) |
| else: |
| env["BAND_LIST"] = ",".join(bands) |
|
|
| nb = "all" if bands is None else len(bands) |
| if force or not os.path.exists(weights): |
| print(f"\n[TRAIN] {name} ({nb} bands) GPU {gpu}") |
| if run_step("train.py", env, os.path.join(ckpt_dir, "train_log.txt")) != 0: |
| print(f" TRAIN FAILED -> {ckpt_dir}/train_log.txt") |
| return False |
| else: |
| print(f"\n[skip train] {name} (weights exist)") |
|
|
| if force or not os.path.exists(metrics): |
| print(f"[EVAL ] {name}") |
| if run_step("evaluate.py", env, os.path.join(result_dir, "eval_log.txt")) != 0: |
| print(f" EVAL FAILED -> {result_dir}/eval_log.txt") |
| return False |
| else: |
| print(f"[skip eval ] {name} (metrics exist)") |
| return True |
|
|
|
|
| def main(): |
| ap = argparse.ArgumentParser() |
| ap.add_argument("--gpu", default="1", help="CUDA device index (default 1)") |
| ap.add_argument("--data-dir", default="all_data/patches", |
| help="patches root (default all_data/patches)") |
| ap.add_argument("--only", default=None, |
| help="comma list of combo names to run (default: all in COMBOS)") |
| ap.add_argument("--force", action="store_true", |
| help="re-run even if checkpoint/metrics already exist") |
| args = ap.parse_args() |
|
|
| names = list(COMBOS) |
| if args.only: |
| wanted = [n.strip() for n in args.only.split(",")] |
| bad = [n for n in wanted if n not in COMBOS] |
| if bad: |
| sys.exit(f"Unknown combo(s): {bad}\nAvailable: {list(COMBOS)}") |
| names = wanted |
|
|
| print(f"Running {len(names)} combo(s) on GPU {args.gpu}, data={args.data_dir}:") |
| print(" " + ", ".join(names)) |
| ok, failed = [], [] |
| for n in names: |
| (ok if run_one(n, COMBOS[n], args.gpu, args.data_dir, args.force) else failed).append(n) |
|
|
| print(f"\nDone. ok={ok} failed={failed}") |
| print("\n" + "=" * 60 + "\n RESULTS\n" + "=" * 60) |
| subprocess.run([sys.executable, os.path.join(HERE, "results_table.py")], cwd=HERE) |
|
|
|
|
| if __name__ == "__main__": |
| main() |
|
|
