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# Copyright (c) OpenMMLab. All rights reserved.
import os
import os.path as osp
import platform
import time
from pathlib import Path
from tempfile import TemporaryDirectory
import decord
import pytest
from mmaction.structures import ActionDataSample
from mmaction.utils import register_all_modules
from mmaction.visualization import ActionVisualizer
register_all_modules()
@pytest.mark.skipif(platform.system() == 'Windows', reason='Windows mem limit')
def test_local_visbackend():
video = decord.VideoReader('./demo/demo.mp4')
video = video.get_batch(range(32)).asnumpy()
data_sample = ActionDataSample()
data_sample.set_gt_label(2)
with TemporaryDirectory() as tmp_dir:
vis = ActionVisualizer(
save_dir=tmp_dir, vis_backends=[dict(type='LocalVisBackend')])
vis.add_datasample('demo', video, data_sample)
for k in range(32):
frame_path = osp.join(tmp_dir, 'vis_data/demo/frames_0/%d.png' % k)
assert Path(frame_path).exists()
vis.add_datasample('demo', video, data_sample, step=1)
for k in range(32):
frame_path = osp.join(tmp_dir, 'vis_data/demo/frames_1/%d.png' % k)
assert Path(frame_path).exists()
return
@pytest.mark.skipif(platform.system() == 'Windows', reason='Windows mem limit')
def test_tensorboard_visbackend():
video = decord.VideoReader('./demo/demo.mp4')
video = video.get_batch(range(32)).asnumpy()
data_sample = ActionDataSample()
data_sample.set_gt_label(2)
with TemporaryDirectory() as tmp_dir:
vis = ActionVisualizer(
save_dir=tmp_dir,
vis_backends=[dict(type='TensorboardVisBackend')])
vis.add_datasample('demo', video, data_sample, step=1)
assert Path(osp.join(tmp_dir, 'vis_data')).exists()
flag = False
for item in os.listdir(osp.join(tmp_dir, 'vis_data')):
if item.startswith('events.out.tfevents.'):
flag = True
break
assert flag, 'Cannot find tensorboard file!'
# wait tensorboard store asynchronously
time.sleep(1)
return
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