[7] - 边界框(bounding boxes)的检测和segmentation mask 的所有评测指标是一致的,除了 IoU 的计算. 边界框的 IoU 计算是关于 boxes的 ,而 segmentation mask 的 IoU 计算是关于 masks 的. 2. 评测指标实现 - cocoeval PythonAPI/pycocotools/cocoeval.py 评测参数如 :(括号里的默认值,一般不需要修改.) ...
mask = np.squeeze(mask, axis=2) masks.append(mask) # 转化为numpy数组 if masks: masks = np.stack(masks, axis=0) else: masks = np.zeros((0, img_h, img_w), dtype=np.uint8) # uint8类型图像 masks = np.where(masks > 0.5, True, False) # 不同颜色显示 img = np.array(img) #...
图4是GT物体mask生成incoherent mask的结果,如中间的列,可以看到incoherent region覆盖了鸟/长颈鹿的腿部及人的手指等细节区域。 图3-从信息压缩损失的角度定义Incoherent Regions 图4-GT Instance Mask生成的Incoherent Regions Masks (Root level) 在表1 中,我们对信息损失区域进行了实验分析,发现很大部分分割误差集中...
'gt_masks'] = segs # Uncomment if you need to compute gts based on segmentation masks # seg_boxes = _polys2boxes(segs) # roi_rec['mask_boxes'] = seg_boxes return roi_rec, flag defevaluate_detections(self, detections, ann_type='bbox', all_masks=None, extra_path=''): """ detec...
masks = masks > 0.5 scores = prediction["scores"].tolist() labels = prediction["labels"].tolist() rles = [ mask_util.encode(np.array(mask[0, :, :, np.newaxis], dtype=np.uint8, order="F"))[0] for mask in masks ] for rle in rles: rle["counts"] = rle["cou...
We evaluate fifty object detectors and find that models that predict visually sharper masks score higher on COCO-ReM, affirming that they were being incorrectly penalized due to errors in COCO-2017. Moreover, our models trained using COCO-ReM converge faster and score higher than their larger ...
The evaluation metrics fordetection with bounding boxesandsegmentation masksare identical in all respectsexcept for the IoU computation(which is performed over boxes or masks, respectively). 目标检测和分割评价指标仅是 IoU 的计算方式不同 Thesholding the IoU defines matches between the ground truth and...
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I will create a PR for this if you agree that this is a bug and should not behave this way. My proposed solution is to move the first condition ofann['area'] <= 0to further down in the code to where the mask information is added to gt_masks_ann. ...
# 需要导入模块: from pycocotools.cocoeval import COCOeval [as 别名]# 或者: from pycocotools.cocoeval.COCOeval importaccumulate[as 别名]defevaluate():cocoGt = COCO('annotations.json') cocoDt = cocoGt.loadRes('detections.json') cocoEval = COCOeval(cocoGt, cocoDt,'bbox') ...