Datasets:
Download evaluation/clips/eval.py from CVML-TueAI/grounding-YT-dataset: direct link, hf CLI and curl.
- Browser
- Download file 1.57 kB
-
https://huggingface.co/datasets/CVML-TueAI/grounding-YT-dataset/resolve/main/evaluation/clips/eval.py
- Command line
-
hf download hf://datasets/CVML-TueAI/grounding-YT-dataset/evaluation/clips/eval.py
-
curl -L -o eval.py https://huggingface.co/datasets/CVML-TueAI/grounding-YT-dataset/resolve/main/evaluation/clips/eval.py
1.57 kB
| import argparse | |
| import json | |
| from pathlib import Path | |
| import sys | |
| def point_in_box(px, py, x_min, y_min, x_max, y_max): | |
| return (x_min <= px < x_max) and (y_min <= py < y_max) | |
| def main(): | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument( | |
| "--predictions", type=str, required=True, help="Path to json file with predictions for each clip" | |
| ) | |
| args = parser.parse_args() | |
| try: | |
| with open("clips_gt.json", 'r', encoding='utf-8') as f: | |
| clips_gt = json.load(f) | |
| with open(args.predictions, 'r', encoding='utf-8') as f: | |
| preds = json.load(f) | |
| except FileNotFoundError as e: | |
| print(f"File not found: {e.filename}") | |
| sys.exit(1) | |
| except json.JSONDecodeError as e: | |
| print(f"Invalid JSON in file: {e}") | |
| sys.exit(1) | |
| except Exception as e: | |
| print(f"Unexpected error: {e}") | |
| sys.exit(1) | |
| total = 0 | |
| hits = 0 | |
| for clip, annots in preds.items(): | |
| if clips_gt.get(clip, None) is None: | |
| print(f'{clip} not present in GT') | |
| continue | |
| for frame, point in annots.items(): #point: (x,y) | |
| if clips_gt[clip].get(frame, None) is None: | |
| print(f'Frame {frame} in {clip} not present in GT') | |
| continue | |
| total+=1 | |
| GT_box = clips_gt[clip].get(frame) | |
| if point_in_box(*point, *GT_box): | |
| hits+=1 | |
| print(f"Total: {total}, hits: {hits}") | |
| print(f'Pointwise-Acc: {hits/total:.3f}') | |
| if __name__ == "__main__": | |
| main() | |