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hotfix: mAP docs

This commit is contained in:
LinasKo 2024-08-28 20:59:54 +03:00
parent 3ddc4bd007
commit b4b941fe1b
1 changed files with 4 additions and 13 deletions
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17
supervision/metrics/mean_average_precision.py
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@ -86,19 +86,10 @@ class MeanAveragePrecision(Metric):
) -> MeanAveragePrecisionResult:
"""
Calculate Mean Average Precision based on predicted and ground-truth
detections at different threshold.
detections at different thresholds.
Args:
predictions (List[np.ndarray]): Each element of the list describes
a single image and has `shape = (M, 6)` where `M` is
the number of detected objects. Each row is expected to be
in `(x_min, y_min, x_max, y_max, class, conf)` format.
targets (List[np.ndarray]): Each element of the list describes a single
image and has `shape = (N, 5)` where `N` is the
number of ground-truth objects. Each row is expected to be in
`(x_min, y_min, x_max, y_max, class)` format.
Returns:
(MeanAveragePrecision): New instance of MeanAveragePrecision.
(MeanAveragePrecisionResult): New instance of MeanAveragePrecision.
Example:
```python
@ -219,7 +210,7 @@ class MeanAveragePrecision(Metric):
)
@staticmethod
def compute_average_precision(recall: np.ndarray, precision: np.ndarray) -> float:
def _compute_average_precision(recall: np.ndarray, precision: np.ndarray) -> float:
"""
Compute the average precision using 101-point interpolation (COCO), given
the recall and precision curves.
@ -323,7 +314,7 @@ class MeanAveragePrecision(Metric):
for iou_level_idx in range(matches.shape[1]):
average_precisions[class_idx, iou_level_idx] = (
MeanAveragePrecision.compute_average_precision(
MeanAveragePrecision._compute_average_precision(
recall[:, iou_level_idx], precision[:, iou_level_idx]
)
)