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| import os.path as osp | |
| from annotator.uniformer.mmcv.runner import DistEvalHook as _DistEvalHook | |
| from annotator.uniformer.mmcv.runner import EvalHook as _EvalHook | |
| class EvalHook(_EvalHook): | |
| """Single GPU EvalHook, with efficient test support. | |
| Args: | |
| by_epoch (bool): Determine perform evaluation by epoch or by iteration. | |
| If set to True, it will perform by epoch. Otherwise, by iteration. | |
| Default: False. | |
| efficient_test (bool): Whether save the results as local numpy files to | |
| save CPU memory during evaluation. Default: False. | |
| Returns: | |
| list: The prediction results. | |
| """ | |
| greater_keys = ['mIoU', 'mAcc', 'aAcc'] | |
| def __init__(self, *args, by_epoch=False, efficient_test=False, **kwargs): | |
| super().__init__(*args, by_epoch=by_epoch, **kwargs) | |
| self.efficient_test = efficient_test | |
| def after_train_iter(self, runner): | |
| """After train epoch hook. | |
| Override default ``single_gpu_test``. | |
| """ | |
| if self.by_epoch or not self.every_n_iters(runner, self.interval): | |
| return | |
| from annotator.uniformer.mmseg.apis import single_gpu_test | |
| runner.log_buffer.clear() | |
| results = single_gpu_test( | |
| runner.model, | |
| self.dataloader, | |
| show=False, | |
| efficient_test=self.efficient_test) | |
| self.evaluate(runner, results) | |
| def after_train_epoch(self, runner): | |
| """After train epoch hook. | |
| Override default ``single_gpu_test``. | |
| """ | |
| if not self.by_epoch or not self.every_n_epochs(runner, self.interval): | |
| return | |
| from annotator.uniformer.mmseg.apis import single_gpu_test | |
| runner.log_buffer.clear() | |
| results = single_gpu_test(runner.model, self.dataloader, show=False) | |
| self.evaluate(runner, results) | |
| class DistEvalHook(_DistEvalHook): | |
| """Distributed EvalHook, with efficient test support. | |
| Args: | |
| by_epoch (bool): Determine perform evaluation by epoch or by iteration. | |
| If set to True, it will perform by epoch. Otherwise, by iteration. | |
| Default: False. | |
| efficient_test (bool): Whether save the results as local numpy files to | |
| save CPU memory during evaluation. Default: False. | |
| Returns: | |
| list: The prediction results. | |
| """ | |
| greater_keys = ['mIoU', 'mAcc', 'aAcc'] | |
| def __init__(self, *args, by_epoch=False, efficient_test=False, **kwargs): | |
| super().__init__(*args, by_epoch=by_epoch, **kwargs) | |
| self.efficient_test = efficient_test | |
| def after_train_iter(self, runner): | |
| """After train epoch hook. | |
| Override default ``multi_gpu_test``. | |
| """ | |
| if self.by_epoch or not self.every_n_iters(runner, self.interval): | |
| return | |
| from annotator.uniformer.mmseg.apis import multi_gpu_test | |
| runner.log_buffer.clear() | |
| results = multi_gpu_test( | |
| runner.model, | |
| self.dataloader, | |
| tmpdir=osp.join(runner.work_dir, '.eval_hook'), | |
| gpu_collect=self.gpu_collect, | |
| efficient_test=self.efficient_test) | |
| if runner.rank == 0: | |
| print('\n') | |
| self.evaluate(runner, results) | |
| def after_train_epoch(self, runner): | |
| """After train epoch hook. | |
| Override default ``multi_gpu_test``. | |
| """ | |
| if not self.by_epoch or not self.every_n_epochs(runner, self.interval): | |
| return | |
| from annotator.uniformer.mmseg.apis import multi_gpu_test | |
| runner.log_buffer.clear() | |
| results = multi_gpu_test( | |
| runner.model, | |
| self.dataloader, | |
| tmpdir=osp.join(runner.work_dir, '.eval_hook'), | |
| gpu_collect=self.gpu_collect) | |
| if runner.rank == 0: | |
| print('\n') | |
| self.evaluate(runner, results) | |