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| import numpy as np | |
| from typing import List, Dict | |
| class TimelineGenerator: | |
| def __init__(self, interval_duration: float = 2.0): | |
| self.interval_duration = interval_duration | |
| def create_timeline(self, video_duration: float) -> List[Dict]: | |
| num_intervals = int(np.ceil(video_duration / self.interval_duration)) | |
| timeline = [] | |
| for i in range(num_intervals): | |
| start_time = i * self.interval_duration | |
| end_time = min((i + 1) * self.interval_duration, video_duration) | |
| timeline.append({ | |
| 'interval_id': i, | |
| 'start': round(start_time, 2), | |
| 'end': round(end_time, 2), | |
| 'interval': f"{start_time:.1f}-{end_time:.1f}", | |
| 'duration': round(end_time - start_time, 2), | |
| 'video_data': [], | |
| 'audio_data': None, | |
| 'video_results': None, | |
| 'audio_results': None | |
| }) | |
| return timeline | |
| def get_interval_for_timestamp(self, timeline: List[Dict], timestamp: float) -> Dict: | |
| for interval in timeline: | |
| if interval['start'] <= timestamp < interval['end']: | |
| return interval | |
| return timeline[-1] |