Fix TypeError: can't convert cuda:0 device type tensor to numpy issue

python_utils/get_model.py

@@ -48,8 +48,10 @@ def load_model(using_final_model: bool = True):
         cfg.merge_from_file(tmp.name)
     if not torch.cuda.is_available():
         cfg.MODEL.DEVICE = "cpu"
+        print('No GPU available, using CPU')
     else:
         cfg.MODEL.DEVICE = 'cuda'
+        print('Using GPU')
 
     if using_final_model:
         ## when rerouting to use the final model (final_tz_segmentor) USE_FED_LOSS has to be set to False
@@ -123,7 +125,9 @@ def apply_nms(prediction, mask=False, cls_agnostic_nms=OPTIMAL_NMS_THRESHOLD):
     from detectron2.structures import Instances
     print(f'applying nms with threshold {cls_agnostic_nms} and mask {mask}... \n')
     if mask:
-        nms_indices = mask_nms(prediction["instances"].pred_masks.numpy(),
+        # print(prediction["instances"].pred_masks)
+        # print(prediction["instances"].pred_masks.cpu())
+        nms_indices = mask_nms(prediction["instances"].pred_masks.cpu().numpy(),
                                prediction["instances"]._fields["scores"], cls_agnostic_nms)
     else:
         nms_indices = nms(prediction["instances"].pred_boxes.tensor,