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| 1 | +# Copyright (c) OpenMMLab. All rights reserved. |
| 2 | +import tempfile |
| 3 | +import warnings |
| 4 | + |
| 5 | +from mmcv.runner import DistEvalHook as BaseDistEvalHook |
| 6 | +from mmcv.runner import EvalHook as BaseEvalHook |
| 7 | + |
| 8 | +MMHUMAN3D_GREATER_KEYS = ['3dpck', 'pa-3dpck', '3dauc', 'pa-3dauc'] |
| 9 | +MMHUMAN3D_LESS_KEYS = ['mpjpe', 'pa-mpjpe', 'pve'] |
| 10 | + |
| 11 | + |
| 12 | +class EvalHook(BaseEvalHook): |
| 13 | + |
| 14 | + def __init__(self, |
| 15 | + dataloader, |
| 16 | + start=None, |
| 17 | + interval=1, |
| 18 | + by_epoch=True, |
| 19 | + save_best=None, |
| 20 | + rule=None, |
| 21 | + test_fn=None, |
| 22 | + greater_keys=MMHUMAN3D_GREATER_KEYS, |
| 23 | + less_keys=MMHUMAN3D_LESS_KEYS, |
| 24 | + **eval_kwargs): |
| 25 | + if test_fn is None: |
| 26 | + from mmhuman3d.apis import single_gpu_test |
| 27 | + test_fn = single_gpu_test |
| 28 | + |
| 29 | + # remove "gpu_collect" from eval_kwargs |
| 30 | + if 'gpu_collect' in eval_kwargs: |
| 31 | + warnings.warn( |
| 32 | + '"gpu_collect" will be deprecated in EvalHook.' |
| 33 | + 'Please remove it from the config.', DeprecationWarning) |
| 34 | + _ = eval_kwargs.pop('gpu_collect') |
| 35 | + |
| 36 | + # update "save_best" according to "key_indicator" and remove the |
| 37 | + # latter from eval_kwargs |
| 38 | + if 'key_indicator' in eval_kwargs or isinstance(save_best, bool): |
| 39 | + warnings.warn( |
| 40 | + '"key_indicator" will be deprecated in EvalHook.' |
| 41 | + 'Please use "save_best" to specify the metric key,' |
| 42 | + 'e.g., save_best="pa-mpjpe".', DeprecationWarning) |
| 43 | + |
| 44 | + key_indicator = eval_kwargs.pop('key_indicator', None) |
| 45 | + if save_best is True and key_indicator is None: |
| 46 | + raise ValueError('key_indicator should not be None, when ' |
| 47 | + 'save_best is set to True.') |
| 48 | + save_best = key_indicator |
| 49 | + |
| 50 | + super().__init__(dataloader, start, interval, by_epoch, save_best, |
| 51 | + rule, test_fn, greater_keys, less_keys, **eval_kwargs) |
| 52 | + |
| 53 | + def evaluate(self, runner, results): |
| 54 | + |
| 55 | + with tempfile.TemporaryDirectory() as tmp_dir: |
| 56 | + eval_res = self.dataloader.dataset.evaluate( |
| 57 | + results, |
| 58 | + res_folder=tmp_dir, |
| 59 | + logger=runner.logger, |
| 60 | + **self.eval_kwargs) |
| 61 | + |
| 62 | + for name, val in eval_res.items(): |
| 63 | + runner.log_buffer.output[name] = val |
| 64 | + runner.log_buffer.ready = True |
| 65 | + |
| 66 | + if self.save_best is not None: |
| 67 | + if self.key_indicator == 'auto': |
| 68 | + self._init_rule(self.rule, list(eval_res.keys())[0]) |
| 69 | + |
| 70 | + return eval_res[self.key_indicator] |
| 71 | + |
| 72 | + return None |
| 73 | + |
| 74 | + |
| 75 | +class DistEvalHook(BaseDistEvalHook): |
| 76 | + |
| 77 | + def __init__(self, |
| 78 | + dataloader, |
| 79 | + start=None, |
| 80 | + interval=1, |
| 81 | + by_epoch=True, |
| 82 | + save_best=None, |
| 83 | + rule=None, |
| 84 | + test_fn=None, |
| 85 | + greater_keys=MMHUMAN3D_GREATER_KEYS, |
| 86 | + less_keys=MMHUMAN3D_LESS_KEYS, |
| 87 | + broadcast_bn_buffer=True, |
| 88 | + tmpdir=None, |
| 89 | + gpu_collect=False, |
| 90 | + **eval_kwargs): |
| 91 | + |
| 92 | + if test_fn is None: |
| 93 | + from mmhuman3d.apis import multi_gpu_test |
| 94 | + test_fn = multi_gpu_test |
| 95 | + |
| 96 | + # update "save_best" according to "key_indicator" and remove the |
| 97 | + # latter from eval_kwargs |
| 98 | + if 'key_indicator' in eval_kwargs or isinstance(save_best, bool): |
| 99 | + warnings.warn( |
| 100 | + '"key_indicator" will be deprecated in EvalHook.' |
| 101 | + 'Please use "save_best" to specify the metric key,' |
| 102 | + 'e.g., save_best="pa-mpjpe".', DeprecationWarning) |
| 103 | + |
| 104 | + key_indicator = eval_kwargs.pop('key_indicator', None) |
| 105 | + if save_best is True and key_indicator is None: |
| 106 | + raise ValueError('key_indicator should not be None, when ' |
| 107 | + 'save_best is set to True.') |
| 108 | + save_best = key_indicator |
| 109 | + |
| 110 | + super().__init__(dataloader, start, interval, by_epoch, save_best, |
| 111 | + rule, test_fn, greater_keys, less_keys, |
| 112 | + broadcast_bn_buffer, tmpdir, gpu_collect, |
| 113 | + **eval_kwargs) |
| 114 | + |
| 115 | + def evaluate(self, runner, results): |
| 116 | + """Evaluate the results. |
| 117 | +
|
| 118 | + Args: |
| 119 | + runner (:obj:`mmcv.Runner`): The underlined training runner. |
| 120 | + results (list): Output results. |
| 121 | + """ |
| 122 | + with tempfile.TemporaryDirectory() as tmp_dir: |
| 123 | + eval_res = self.dataloader.dataset.evaluate( |
| 124 | + results, |
| 125 | + res_folder=tmp_dir, |
| 126 | + logger=runner.logger, |
| 127 | + **self.eval_kwargs) |
| 128 | + |
| 129 | + for name, val in eval_res.items(): |
| 130 | + runner.log_buffer.output[name] = val |
| 131 | + runner.log_buffer.ready = True |
| 132 | + |
| 133 | + if self.save_best is not None: |
| 134 | + if self.key_indicator == 'auto': |
| 135 | + # infer from eval_results |
| 136 | + self._init_rule(self.rule, list(eval_res.keys())[0]) |
| 137 | + return eval_res[self.key_indicator] |
| 138 | + |
| 139 | + return None |
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