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