forked from Github/frigate
20 lines
1.5 KiB
Markdown
20 lines
1.5 KiB
Markdown
---
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id: false_positives
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title: Reducing false positives
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---
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Tune your object filters to adjust false positives: `min_area`, `max_area`, `min_score`, `threshold`.
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For object filters in your configuration, any single detection below `min_score` will be ignored as a false positive. `threshold` is based on the median of the history of scores (padded to 3 values) for a tracked object. Consider the following frames when `min_score` is set to 0.6 and threshold is set to 0.85:
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| Frame | Current Score | Score History | Computed Score | Detected Object |
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| ----- | ------------- | --------------------------------- | -------------- | --------------- |
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| 1 | 0.7 | 0.0, 0, 0.7 | 0.0 | No |
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| 2 | 0.55 | 0.0, 0.7, 0.0 | 0.0 | No |
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| 3 | 0.85 | 0.7, 0.0, 0.85 | 0.7 | No |
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| 4 | 0.90 | 0.7, 0.85, 0.95, 0.90 | 0.875 | Yes |
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| 5 | 0.88 | 0.7, 0.85, 0.95, 0.90, 0.88 | 0.88 | Yes |
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| 6 | 0.95 | 0.7, 0.85, 0.95, 0.90, 0.88, 0.95 | 0.89 | Yes |
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In frame 2, the score is below the `min_score` value, so frigate ignores it and it becomes a 0.0. The computed score is the median of the score history (padding to at least 3 values), and only when that computed score crosses the `threshold` is the object marked as a true positive. That happens in frame 4 in the example.
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