MSDN_base.py 文件源码

def object_detection_gt_boxes(self, image_path, gt_boxes):
        min_score = 1/150.
        image = cv2.imread(image_path)
        # print 'image.shape', image.shape
        im_data, im_scales = self.get_image_blob_noscale(image)
        gt_boxes[:, :4] = gt_boxes[:, :4] * im_scales[0]
        # print 'im_data.shape', im_data.shape
        # print 'im_scales', im_scales
        im_info = np.array(
            [[im_data.shape[1], im_data.shape[2], im_scales[0]]],
            dtype=np.float32)
        object_result = self(im_data, im_info, gt_boxes)[0]
        cls_prob_object, bbox_object, object_rois = object_result[:]

        prob_object = F.softmax(cls_prob_object)
        prob = prob_object.cpu().data
        top_5_cls = torch.topk(prob[:, 1:], 5, dim=1)
        # print 'im_scales[0]', im_scales[0]
        return top_5_cls[1].numpy()