mAP@.5 mAP@.5:.95:
时间: 2024-05-22 12:15:11 浏览: 18
mAP@.5 and mAP@.5:.95 are two common evaluation metrics used to assess the performance of object detection models.
mAP@.5 (mean average precision at IoU threshold of 0.5) measures the average precision of the model at a specific intersection over union (IoU) threshold of 0.5. This means that if the predicted bounding box overlaps with the ground truth bounding box by more than 50%, it is considered a correct detection. mAP@.5 is a commonly used metric because it balances precision and recall and is less sensitive to small variations in IoU thresholds.
mAP@.5:.95 (mean average precision across all IoU thresholds from 0.5 to 0.95) measures the average precision of the model at all IoU thresholds from 0.5 to 0.95. This metric is more comprehensive than mAP@.5 as it takes into account all levels of IoU thresholds and provides a more complete picture of the model's performance. However, it can also be more challenging to achieve high scores on this metric because it requires the model to perform well across a wider range of IoU thresholds.