---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
~\AppData\Local\Temp\ipykernel_53796\2715512915.py in <module>
     26                 postprocess_type  = "NMS",
     27                 postprocess_match_metric = "IOU",
---> 28                 perform_standard_pred=False)
     29         result_len = result.to_coco_annotations()
     30         for pred in result_len:

~\anaconda3\envs\bird\lib\site-packages\sahi\predict.py in get_sliced_prediction(image, detection_model, slice_height, slice_width, overlap_height_ratio, overlap_width_ratio, perform_standard_pred, postprocess_type, postprocess_match_metric, postprocess_match_threshold, postprocess_class_agnostic, verbose, merge_buffer_length, auto_slice_resolution)
    243             full_shape=[
    244                 slice_image_result.original_image_height,
--> 245                 slice_image_result.original_image_width,
    246             ],
    247         )

~\anaconda3\envs\bird\lib\site-packages\sahi\predict.py in get_prediction(image, detection_model, shift_amount, full_shape, postprocess, verbose)
     89     # get prediction
     90     time_start = time.time()
---> 91     detection_model.perform_inference(np.ascontiguousarray(image_as_pil))
     92     time_end = time.time() - time_start
     93     durations_in_seconds["prediction"] = time_end

~\AppData\Local\Temp\ipykernel_53796\30530663.py in perform_inference(self, img, image_size)
     23         with torch.no_grad():
     24             # Run model
---> 25             (out, train_out), pdg = self.model(img, augment=True)  # inference and training outputs
     26          # Run NMS
     27         prediction_result = non_max_suppression(out, conf_thres=self.confidence_threshold, iou_thres=self.iou_thres, labels=[], multi_label=True)

~\anaconda3\envs\bird\lib\site-packages\torch\nn\modules\module.py in _call_impl(self, *input, **kwargs)
   1128         if not (self._backward_hooks or self._forward_hooks or self._forward_pre_hooks or _global_backward_hooks
   1129                 or _global_forward_hooks or _global_forward_pre_hooks):
-> 1130             return forward_call(*input, **kwargs)
   1131         # Do not call functions when jit is used
   1132         full_backward_hooks, non_full_backward_hooks = [], []

~\birds\DRENet\models\yolo.py in forward(self, x, augment, profile)
    121                 yi = self.forward_once(xi)[0]  # forward
    122                 # cv2.imwrite('img%g.jpg' % s, 255 * xi[0].numpy().transpose((1, 2, 0))[:, :, ::-1])  # save
--> 123                 yi[..., :4] /= si  # de-scale
    124                 if fi == 2:
    125                     yi[..., 1] = img_size[0] - yi[..., 1]  # de-flip ud

TypeError: tuple indices must be integers or slices, not tuple