| import os |
| import json |
| from barcode_scanner import scan_all_barcodes |
| from ocr import read_chassis, postprocess_with_hint |
|
|
| BARCODE_DIR = "images/barcode" |
| CHASSIS_DIR = "images/chassis" |
| RESULTS_DIR = "results" |
|
|
|
|
| def get_pairs(): |
| barcode_files = {os.path.splitext(f)[0]: f |
| for f in os.listdir(BARCODE_DIR) |
| if f.lower().endswith(('.jpg', '.jpeg', '.png'))} |
| chassis_files = {os.path.splitext(f)[0]: f |
| for f in os.listdir(CHASSIS_DIR) |
| if f.lower().endswith(('.jpg', '.jpeg', '.png'))} |
|
|
| common = sorted(set(barcode_files.keys()) & set(chassis_files.keys())) |
| pairs = [] |
| for key in common: |
| pairs.append({ |
| "key": key, |
| "barcode_path": os.path.join(BARCODE_DIR, barcode_files[key]), |
| "chassis_path": os.path.join(CHASSIS_DIR, chassis_files[key]), |
| }) |
| return pairs |
|
|
|
|
| def evaluate(): |
| os.makedirs(RESULTS_DIR, exist_ok=True) |
|
|
| print("=" * 60) |
| print("CHASSIS OCR EVALUATION") |
| print("=" * 60) |
|
|
| print("\n[1/3] Scanning barcodes for ground truth...") |
| barcode_results = scan_all_barcodes(BARCODE_DIR) |
|
|
| pairs = get_pairs() |
| print(f"\n[2/3] Found {len(pairs)} matching image pairs") |
|
|
| print(f"\n[3/3] Running OCR pipeline on chassis images...\n") |
|
|
| results = [] |
| exact_match = 0 |
| corrected_match = 0 |
| failed = 0 |
|
|
| for pair in pairs: |
| key = pair["key"] |
| expected = barcode_results.get(key) |
| chassis_path = pair["chassis_path"] |
|
|
| if not expected: |
| print(f" [WARN] {key} - barcode not decoded, skipping") |
| continue |
|
|
| ocr_text, conf = read_chassis(chassis_path, save_comparison=True) |
|
|
| corrected, is_match = postprocess_with_hint(ocr_text, expected) |
|
|
| if ocr_text == expected: |
| status = "[EXACT]" |
| exact_match += 1 |
| elif is_match: |
| status = "[CORRECTED]" |
| corrected_match += 1 |
| else: |
| status = "[FAILED]" |
| failed += 1 |
|
|
| print(f" {status} | {key}") |
| print(f" Expected : {expected}") |
| print(f" Got : {ocr_text} (conf: {conf:.0%})") |
| if is_match and ocr_text != expected: |
| print(f" Fixed to : {corrected}") |
| print() |
|
|
| results.append({ |
| "key": key, |
| "expected": expected, |
| "ocr_raw": ocr_text, |
| "corrected": corrected, |
| "confidence": round(conf, 3), |
| "match": is_match, |
| "exact": ocr_text == expected, |
| }) |
|
|
| total = len(results) |
| total_correct = exact_match + corrected_match |
| print("=" * 60) |
| print("RESULTS SUMMARY") |
| print("=" * 60) |
| print(f"Total pairs evaluated : {total}") |
| print(f"Exact matches : {exact_match}/{total} ({exact_match/total*100:.1f}%)") |
| print(f"Corrected matches : {corrected_match}/{total} ({corrected_match/total*100:.1f}%)") |
| print(f"Total correct : {total_correct}/{total} ({total_correct/total*100:.1f}%)") |
| print(f"Failed : {failed}/{total} ({failed/total*100:.1f}%)") |
| print("=" * 60) |
|
|
| if failed > 0: |
| print("\nFailed images (focus preprocessing tuning here):") |
| for r in results: |
| if not r["match"]: |
| print(f" - {r['key']}: expected '{r['expected']}', got '{r['ocr_raw']}'") |
|
|
| report_path = os.path.join(RESULTS_DIR, "report.json") |
| with open(report_path, "w") as f: |
| json.dump(results, f, indent=2) |
| print(f"\nFull report saved -> {report_path}") |
| print(f"Comparison images -> {RESULTS_DIR}/") |
|
|
|
|
| if __name__ == "__main__": |
| evaluate() |
|
|
