oa::vision::evaluate
Evaluate object-detection precision, recall, F1, AP, and mAP. Matching is class-aware, image-aware, greedy by descending score, and uses 101-point interpolated average precision. Classes without targets do not contribute to mAP. Scratch and outputs remain GPU-resident. Errors Returns an error when any shape, dtype, ownership, class-count, score-threshold, or 32-bit scratch-size contract is invalid.
Function Documentation
pub fn evaluate(
predicted_boxes: &Matrix,
predicted_scores: &Matrix,
predicted_classes: &Matrix,
predicted_image_ids: &Matrix,
target_boxes: &Matrix,
target_classes: &Matrix,
target_image_ids: &Matrix,
iou_thresholds: &Matrix,
class_count: i32,
score_threshold: f32
) -> Result<DetectionMetricsResult>Evaluate object-detection precision, recall, F1, AP, and mAP. Matching is class-aware, image-aware, greedy by descending score, and uses 101-point interpolated average precision. Classes without targets do not contribute to mAP. Scratch and outputs remain GPU-resident. Errors Returns an error when any shape, dtype, ownership, class-count, score-threshold, or 32-bit scratch-size contract is invalid.