mmpretrain/tests/test_engine/test_hooks/test_visualization_hook.py

155 lines
5.5 KiB
Python

# Copyright (c) OpenMMLab. All rights reserved.
import os.path as osp
import tempfile
from unittest import TestCase
from unittest.mock import ANY, MagicMock, patch
import torch
from mmengine.runner import EpochBasedTrainLoop, IterBasedTrainLoop
from mmcls.engine import VisualizationHook
from mmcls.registry import HOOKS
from mmcls.structures import ClsDataSample
from mmcls.utils import register_all_modules
from mmcls.visualization import ClsVisualizer
register_all_modules()
class TestVisualizationHook(TestCase):
def setUp(self) -> None:
ClsVisualizer.get_instance('visualizer')
data_sample = ClsDataSample().set_gt_label(1).set_pred_label(2)
data_sample.set_metainfo({'img_path': 'tests/data/color.jpg'})
self.data_batch = [{
'inputs': torch.randint(0, 256, (3, 224, 224)),
'data_sample': data_sample
}] * 10
self.outputs = [data_sample] * 10
self.tmpdir = tempfile.TemporaryDirectory()
def test_initialize(self):
# test file_client
cfg = dict(type='VisualizationHook')
hook = HOOKS.build(cfg)
self.assertIsNone(hook.file_client)
cfg = dict(type='VisualizationHook', out_dir=self.tmpdir.name)
hook = HOOKS.build(cfg)
self.assertIsNotNone(hook.file_client)
# test draw_args
def test_draw_samples(self):
# test enable=False
cfg = dict(type='VisualizationHook', enable=False)
hook: VisualizationHook = HOOKS.build(cfg)
with patch.object(hook._visualizer, 'add_datasample') as mock:
hook._draw_samples(1, self.data_batch, self.outputs, step=1)
mock.assert_not_called()
# test enable=True
cfg = dict(type='VisualizationHook', enable=True, show=True)
hook: VisualizationHook = HOOKS.build(cfg)
with patch.object(hook._visualizer, 'add_datasample') as mock:
hook._draw_samples(0, self.data_batch, self.outputs, step=0)
mock.assert_called_once_with(
'color.jpg',
image=ANY,
data_sample=self.outputs[0],
step=0,
show=True)
# test samples without path
cfg = dict(type='VisualizationHook', enable=True)
hook: VisualizationHook = HOOKS.build(cfg)
with patch.object(hook._visualizer, 'add_datasample') as mock:
outputs = [ClsDataSample()] * 10
hook._draw_samples(0, self.data_batch, outputs, step=0)
mock.assert_called_once_with(
'0', image=ANY, data_sample=outputs[0], step=0, show=False)
# test out_dir
cfg = dict(
type='VisualizationHook', enable=True, out_dir=self.tmpdir.name)
hook: VisualizationHook = HOOKS.build(cfg)
with patch.object(hook._visualizer, 'add_datasample') as mock:
hook._draw_samples(0, self.data_batch, self.outputs, step=0)
mock.assert_called_once_with(
'color.jpg',
image=ANY,
data_sample=self.outputs[0],
step=0,
show=False,
out_file=osp.join(self.tmpdir.name, 'color.jpg_0.png'))
# test sample idx
cfg = dict(type='VisualizationHook', enable=True, interval=4)
hook: VisualizationHook = HOOKS.build(cfg)
with patch.object(hook._visualizer, 'add_datasample') as mock:
hook._draw_samples(1, self.data_batch, self.outputs, step=0)
mock.assert_called_with(
'color.jpg',
image=ANY,
data_sample=self.outputs[2],
step=0,
show=False)
mock.assert_called_with(
'color.jpg',
image=ANY,
data_sample=self.outputs[6],
step=0,
show=False)
def test_after_val_iter(self):
runner = MagicMock()
# test epoch-based
runner.train_loop = MagicMock(spec=EpochBasedTrainLoop)
runner.epoch = 5
cfg = dict(type='VisualizationHook', enable=True)
hook = HOOKS.build(cfg)
with patch.object(hook._visualizer, 'add_datasample') as mock:
hook.after_val_iter(runner, 0, self.data_batch, self.outputs)
mock.assert_called_once_with(
'color.jpg',
image=ANY,
data_sample=self.outputs[0],
step=5,
show=False)
# test iter-based
runner.train_loop = MagicMock(spec=IterBasedTrainLoop)
runner.iter = 300
cfg = dict(type='VisualizationHook', enable=True)
hook = HOOKS.build(cfg)
with patch.object(hook._visualizer, 'add_datasample') as mock:
hook.after_val_iter(runner, 0, self.data_batch, self.outputs)
mock.assert_called_once_with(
'color.jpg',
image=ANY,
data_sample=self.outputs[0],
step=300,
show=False)
def test_after_test_iter(self):
runner = MagicMock()
cfg = dict(type='VisualizationHook', enable=True)
hook = HOOKS.build(cfg)
with patch.object(hook._visualizer, 'add_datasample') as mock:
hook.after_test_iter(runner, 0, self.data_batch, self.outputs)
mock.assert_called_once_with(
'color.jpg',
image=ANY,
data_sample=self.outputs[0],
step=0,
show=False)
def tearDown(self) -> None:
self.tmpdir.cleanup()