How to obtain instance segmentation results from Co-DETR?

[edwardnguyen1705]

Dear @TempleX98 , @Sense-X ,

I am trying to obtain instance segmentation results, but I have not been successful yet. I follow this instance-segmentation-using-mmdetection-on-colab-part-1

    def segm(self, img_brg:np.ndarray):
        result = inference_detector(self.model, img_brg)
        bboxes, labels, ret_mask = self._postprocess(result)
        exit()
        return bboxes, labels, ret_mask
    
    def _postprocess(self, preds):
        bbox_result, segm_result = preds
        segm_result = segm_result[1]
        bboxes = np.vstack(bbox_result)
        labels = [
            np.full(bbox.shape[0], i, dtype=np.int32)
            for i, bbox in enumerate(bbox_result)
        ]
        labels = np.concatenate(labels)
        
        #Get polygon points of all labels
        segms = segm_result
        if segm_result is not None and len(labels) > 0:# non empty
            segms = mmcv.concat_list(segm_result)
        if isinstance(segms[0], torch.Tensor):
            segms = torch.stack(segms, dim=0).detach().cpu().numpy()
        else:
            segms = np.stack(segms, axis=0)

        assert segms is None or segms.shape[0] == labels.shape[0], \
        'segms.shape[0] and labels.shape[0] should have the same length.'
        assert segms is not None or bboxes is not None, \
        'segms and bboxes should not be None at the same time.'

        #Polygon points
        ret_mask = []
        for i, mask in enumerate(segms):
            print(mask)
            contours, _ = bitmap_to_polygon(mask)
            ret_mask.append(contours)
  
        return bboxes, labels, ret_mask