Same input/output format as :meth:`SemanticSegmentor.forward`
(self, batched_inputs, current_step)
| 103 | return ret |
| 104 | |
| 105 | def __call__(self, batched_inputs, current_step): |
| 106 | """ |
| 107 | Same input/output format as :meth:`SemanticSegmentor.forward` |
| 108 | """ |
| 109 | self.current_step = current_step # redundant param for api compliance |
| 110 | def _maybe_read_image(dataset_dict): |
| 111 | ret = copy.copy(dataset_dict) |
| 112 | if "image" not in ret: |
| 113 | raise |
| 114 | if "height" not in ret and "width" not in ret: # TODO: BUG HERE |
| 115 | raise |
| 116 | # ret["height"] = ret["ori_image"].shape[1]#ret["image"].shape[1] |
| 117 | # ret["width"] = ret["ori_image"].shape[2] |
| 118 | return ret |
| 119 | |
| 120 | processed_results = [] |
| 121 | # for x in batched_inputs: |
| 122 | result = self._inference_one_image(_maybe_read_image(batched_inputs)) |
| 123 | processed_results.append(result) |
| 124 | return processed_results |
| 125 | |
| 126 | def _inference_one_image(self, input): |
| 127 | """ |
nothing calls this directly
no test coverage detected