| """Independently re-run COLMAP SfM on each part to verify the reported failure. |
| |
| Uses the colmap CLI (3.8, CPU SIFT). Records feature counts, match counts and |
| how many images the incremental mapper manages to register. |
| """ |
| import os, sys, json, shutil, subprocess, sqlite3 |
|
|
| SRC = "repo/input_images" |
| OUT = "work/colmap_verify" |
| PARTS = ["bracket", "connector_module", "flange_housing", "timing_pulley"] |
|
|
|
|
| def sh(cmd): |
| p = subprocess.run(cmd, capture_output=True, text=True) |
| return p.returncode, p.stdout + p.stderr |
|
|
|
|
| def db_stats(db): |
| con = sqlite3.connect(db); cur = con.cursor() |
| kp = cur.execute("SELECT image_id, rows FROM keypoints").fetchall() |
| nm = cur.execute("SELECT COUNT(*), SUM(rows) FROM matches WHERE rows>0").fetchone() |
| ntv = cur.execute("SELECT COUNT(*), SUM(rows) FROM two_view_geometries WHERE rows>0").fetchone() |
| con.close() |
| return {"keypoints_per_image": {str(i): r for i, r in kp}, |
| "match_pairs": nm[0], "total_matches": nm[1] or 0, |
| "verified_pairs": ntv[0], "verified_matches": ntv[1] or 0} |
|
|
|
|
| results = {} |
| for part in PARTS: |
| ws = os.path.join(OUT, part) |
| if os.path.exists(ws): shutil.rmtree(ws) |
| os.makedirs(os.path.join(ws, "sparse"), exist_ok=True) |
| imdir = os.path.join(ws, "images"); os.makedirs(imdir) |
| src = os.path.join(SRC, part, "input") |
| for f in sorted(os.listdir(src)): |
| shutil.copy(os.path.join(src, f), imdir) |
| db = os.path.join(ws, "database.db") |
|
|
| rc, o = sh(["colmap", "feature_extractor", "--database_path", db, |
| "--image_path", imdir, |
| "--SiftExtraction.use_gpu", "0", |
| "--SiftExtraction.estimate_affine_shape", "1", |
| "--SiftExtraction.domain_size_pooling", "1"]) |
| rc2, o2 = sh(["colmap", "exhaustive_matcher", "--database_path", db, |
| "--SiftMatching.use_gpu", "0", |
| "--SiftMatching.guided_matching", "1"]) |
| st = db_stats(db) |
|
|
| rc3, o3 = sh(["colmap", "mapper", "--database_path", db, "--image_path", imdir, |
| "--output_path", os.path.join(ws, "sparse"), |
| "--Mapper.init_min_num_inliers", "15", |
| "--Mapper.abs_pose_min_num_inliers", "10", |
| "--Mapper.min_num_matches", "8"]) |
| models = [d for d in sorted(os.listdir(os.path.join(ws, "sparse"))) |
| if os.path.isdir(os.path.join(ws, "sparse", d))] |
| reg = 0; npts = 0 |
| if models: |
| m = os.path.join(ws, "sparse", models[0]) |
| rc4, _ = sh(["colmap", "model_converter", "--input_path", m, |
| "--output_path", m, "--output_type", "TXT"]) |
| ip = os.path.join(m, "images.txt") |
| if os.path.exists(ip): |
| reg = sum(1 for l in open(ip) if l.strip() and not l.startswith("#")) // 2 |
| pp = os.path.join(m, "points3D.txt") |
| if os.path.exists(pp): |
| npts = sum(1 for l in open(pp) if l.strip() and not l.startswith("#")) |
| n_imgs = len(os.listdir(imdir)) |
| results[part] = {"n_images": n_imgs, **st, "n_models": len(models), |
| "registered": reg, "points3D": npts, |
| "mapper_tail": o3.strip().splitlines()[-6:]} |
| print(f"{part}: imgs={n_imgs} kpts={list(st['keypoints_per_image'].values())} " |
| f"verified_pairs={st['verified_pairs']} verified_matches={st['verified_matches']} " |
| f"-> models={len(models)} registered={reg} points={npts}") |
|
|
| os.makedirs(OUT, exist_ok=True) |
| json.dump(results, open(os.path.join(OUT, "colmap_verify.json"), "w"), indent=2) |
| print("\nwrote", os.path.join(OUT, "colmap_verify.json")) |
|
|
