cvtools.evaluation.mean_ap module

cvtools.evaluation.mean_ap.average_precision(recalls, precisions, mode='area')

Calculate average precision (for single or multiple scales).

参数:

• recalls (ndarray) -- shape (num_scales, num_dets) or (num_dets, )
• precisions (ndarray) -- shape (num_scales, num_dets) or (num_dets, )
• mode (str) -- 'area' or '11points', 'area' means calculating the area under precision-recall curve, '11points' means calculating the average precision of recalls at [0, 0.1, ..., 1]

返回:

calculated average precision

返回类型:

float or ndarray

cvtools.evaluation.mean_ap.eval_map(det_results, gt_bboxes, gt_labels, gt_ignore=None, scale_ranges=None, iou_thr=0.5, dataset=None, print_summary=True, calc_ious=<function bbox_overlaps>)

Evaluate mAP of a dataset.

参数:

• det_results (list) -- a list of list, [[cls1_det, cls2_det, ...], ...] cls1_det为np.array，包含K*5，包含得分, x1y1x2y2形式
• gt_bboxes (list) -- ground truth bboxes of each image, a list of K*4 array. x1y1x2y2形式
• gt_labels (list) -- ground truth labels of each image, a list of K array
• gt_ignore (list) -- gt ignore indicators of each image, a list of K array
• scale_ranges (list, optional) -- [(min1, max1), (min2, max2), ...]
• iou_thr (float) -- IoU threshold，目前还不支持polyiou
• dataset (None or str or list) -- dataset name or dataset classes, there are minor differences in metrics for different datsets, e.g. "voc07", "imagenet_det", etc.
• print_summary (bool) -- whether to print the mAP summary

返回:

(mAP, [dict, dict, ...])

返回类型:

tuple

cvtools.evaluation.mean_ap.get_cls_results(det_results, gt_bboxes, gt_labels, gt_ignore, class_id)

Get det results and gt information of a certain class.

cvtools.evaluation.mean_ap.print_map_summary(mean_ap, results, dataset=None)

Print mAP and results of each class.

参数:

• mean_ap (float) -- calculated from eval_map
• results (list) -- calculated from eval_map
• dataset (None or str or list) -- dataset name or dataset classes.

cvtools.evaluation.mean_ap.tpfp_default(det_bboxes, gt_bboxes, gt_ignore, iou_thr, area_ranges=None, calc_ious=<function bbox_overlaps>)

Check if detected bboxes are true positive or false positive.

参数:

• det_bbox (ndarray) -- the detected bbox
• gt_bboxes (ndarray) -- ground truth bboxes of this image
• gt_ignore (ndarray) -- indicate if gts are ignored for evaluation or not
• iou_thr (float) -- the iou thresholds
• calc_ious -- 自定义计算iou方法

返回:

(tp, fp), two arrays whose elements are 0 and 1

返回类型:

tuple

cvtools.evaluation.mean_ap.tpfp_imagenet(det_bboxes, gt_bboxes, gt_ignore, default_iou_thr, area_ranges=None, calc_ious=<function bbox_overlaps>)

Check if detected bboxes are true positive or false positive.

参数:

• det_bbox (ndarray) -- the detected bbox
• gt_bboxes (ndarray) -- ground truth bboxes of this image
• gt_ignore (ndarray) -- indicate if gts are ignored for evaluation or not
• default_iou_thr (float) -- the iou thresholds for medium and large bboxes
• area_ranges (list or None) -- gt bbox area ranges

返回:

two arrays (tp, fp) whose elements are 0 and 1

返回类型:

tuple