Esempio n. 1
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    def evaluate(self, output, batch):
        detection = output['detection']
        score = detection[:, 4].detach().cpu().numpy()
        label = detection[:, 5].detach().cpu().numpy().astype(int)
        py = output['py'][-1].detach().cpu().numpy() * snake_config.down_ratio

        if len(py) == 0:
            return

        img_id = int(batch['meta']['img_id'][0])
        center = batch['meta']['center'][0].detach().cpu().numpy()
        scale = batch['meta']['scale'][0].detach().cpu().numpy()

        h, w = batch['inp'].size(2), batch['inp'].size(3)
        trans_output_inv = data_utils.get_affine_transform(center, scale, 0, [w, h], inv=1)
        img = self.coco.loadImgs(img_id)[0]
        ori_h, ori_w = img['height'], img['width']
        py = [data_utils.affine_transform(py_, trans_output_inv) for py_ in py]
        rles = snake_eval_utils.coco_poly_to_rle(py, ori_h, ori_w)

        coco_dets = []
        for i in range(len(rles)):
            detection = {
                'image_id': img_id,
                'category_id': self.contiguous_category_id_to_json_id[label[i]],
                'segmentation': rles[i],
                'score': float('{:.2f}'.format(score[i]))
            }
            coco_dets.append(detection)

        self.results.extend(coco_dets)
        self.img_ids.append(img_id)
Esempio n. 2
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def poly_rle_nms(polys, scores, img_size, nms_thresh=0.3):
    assert len(scores) == len(polys), 'poly.num != scores.num'
    _h, _w = img_size[0], img_size[1]
    rles = snake_eval_utils.coco_poly_to_rle(polys, _h, _w)
    iscrowd = [int(0) for k in range(len(polys))]
    ious = maskUtils.iou(rles, rles, iscrowd)
    order = scores.argsort()[::-1]
    keep = []
    while order.size > 0:
        i = order[0]
        keep.append(i)
        ovr = ious[i][order[1:]].astype(np.float32)
        inds = np.where(ovr <= nms_thresh)[0]
        order = order[inds + 1]
    return keep
Esempio n. 3
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def poly_rle_nms(img, polys, scores, nms_thresh=0.3):
    assert len(scores) ==  len(polys), 'poly.num != scores.num'
    org_h, org_w, _ = img.shape
    rles = snake_eval_utils.coco_poly_to_rle(polys, org_h, org_w)
    print('encoding rles done.')
    iscrowd = [int(0) for k in range(len(all_boundaries))]
    ious = maskUtils.iou(rles, rles, iscrowd)
    print('ious:', ious)

    order = scores.argsort()[::-1]
    keep = []
    while order.size>0:
        i = order[0]
        keep.append(i)
        ovr = ious[i][order[1:]].astype(np.float32)
        inds = np.where(ovr <= nms_thresh)[0]
        order = order[inds+1]
    return keep