(detector: str, dataset: str, detailed: bool)
| 39 | |
| 40 | |
| 41 | def _detect_scenes(detector: str, dataset: str, detailed: bool): |
| 42 | pred_scenes = {} |
| 43 | for video_file, scene_file in tqdm(_DATASETS[dataset]): |
| 44 | start = time.time() |
| 45 | pred_scene_list = detect(video_file, _DETECTORS[detector]()) |
| 46 | elapsed = time.time() - start |
| 47 | filename = os.path.basename(video_file) |
| 48 | scenes = { |
| 49 | scene_file: { |
| 50 | "video_file": filename, |
| 51 | "elapsed": elapsed, |
| 52 | "pred_scenes": [scene[1].frame_num for scene in pred_scene_list], |
| 53 | } |
| 54 | } |
| 55 | result = Evaluator().evaluate_performance(scenes) |
| 56 | if detailed: |
| 57 | print(f"\n{filename} results:") |
| 58 | print(_RESULT_PRINT_FORMAT.format(**result) + "\n") |
| 59 | pred_scenes.update(scenes) |
| 60 | |
| 61 | return pred_scenes |
| 62 | |
| 63 | |
| 64 | def run_benchmark(detector: str, dataset: str, detailed: bool): |
no test coverage detected