: return: "AP", "MR", "JI", "Recall"
(self)
| 138 | return data_list |
| 139 | |
| 140 | def evaluate(self): |
| 141 | """ |
| 142 | : return: "AP", "MR", "JI", "Recall" |
| 143 | """ |
| 144 | if self._distributed: |
| 145 | link.synchronize() |
| 146 | predictions_list = self.all_gather(self._predictions) |
| 147 | if link.get_rank() != 0: |
| 148 | return |
| 149 | |
| 150 | proxy_number = time.time() |
| 151 | file_path = os.path.join('tmp', 'CrowdHuman', f'Iter-{proxy_number}.human') |
| 152 | self.save_results(self._predictions, file_path) |
| 153 | eval_results = self._evaluate_predictions_on_crowdhuman(self._gt_path, file_path) |
| 154 | |
| 155 | res = {} |
| 156 | metric_names = ["AP", "MR", "JI", "Recall"] |
| 157 | for k, v in zip(metric_names, eval_results): |
| 158 | print(f"{k}: {v}") |
| 159 | res[k] = v |
| 160 | results = OrderedDict({"pedestrain_detection": res}) |
| 161 | self._logger.info(results) |
| 162 | os.remove(file_path) |
| 163 | print(f"{file_path} deleted") |
| 164 | |
| 165 | return results |
| 166 | |
| 167 | def save_results(self, content, fpath): |
| 168 | os.makedirs(os.path.dirname(fpath), exist_ok=True) |
nothing calls this directly
no test coverage detected