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[Fix] Fix SegLocalVisualizer UT #1851

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merged 1 commit into from Aug 1, 2022
Merged

[Fix] Fix SegLocalVisualizer UT #1851

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22 changes: 12 additions & 10 deletions tests/test_visualization/test_local_visualizer.py
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Expand Up @@ -7,7 +7,6 @@
import cv2
import mmcv
import numpy as np
import pytest
import torch
from mmengine.data import PixelData

Expand All @@ -29,14 +28,11 @@ def test_add_datasample(self):
gt_sem_seg_data = dict(data=torch.randint(0, num_class, (1, h, w)))
gt_sem_seg = PixelData(**gt_sem_seg_data)

@pytest.mark.skipif(
not torch.cuda.is_available(), reason='CUDA not available')
@pytest.mark.parametrize('gt_sem_seg', (gt_sem_seg, gt_sem_seg.cuda()))
def test_add_datasample_forward(gt_sem_seg):
gt_seg_data_sample = SegDataSample()
gt_seg_data_sample.gt_sem_seg = gt_sem_seg

with tempfile.TemporaryDirectory(dir='temp_dir') as tmp_dir:
with tempfile.TemporaryDirectory() as tmp_dir:
seg_local_visualizer = SegLocalVisualizer(
vis_backends=[dict(type='LocalVisBackend')],
save_dir=tmp_dir)
Expand Down Expand Up @@ -81,6 +77,10 @@ def test_add_datasample_forward(gt_sem_seg):
osp.join(tmp_dir, 'vis_data', 'vis_image',
out_file + '_0.png'), (h, w, 3))

if torch.cuda.is_available():
test_add_datasample_forward(gt_sem_seg.cuda())
test_add_datasample_forward(gt_sem_seg)

def test_cityscapes_add_datasample(self):
h = 128
w = 256
Expand All @@ -103,16 +103,14 @@ def test_cityscapes_add_datasample(self):
gt_sem_seg_data = dict(data=sem_seg)
gt_sem_seg = PixelData(**gt_sem_seg_data)

@pytest.mark.skipif(
not torch.cuda.is_available(), reason='CUDA not available')
@pytest.mark.parametrize('gt_sem_seg', (gt_sem_seg, gt_sem_seg.cuda()))
def test_cityscapes_add_datasample_forward(gt_sem_seg):
gt_seg_data_sample = SegDataSample()
gt_seg_data_sample.gt_sem_seg = gt_sem_seg
with tempfile.TemporaryDirectory(dir='temp_dir') as tmp_dir:

with tempfile.TemporaryDirectory() as tmp_dir:
seg_local_visualizer = SegLocalVisualizer(
vis_backends=[dict(type='LocalVisBackend')],
save_dir='temp_dir')
save_dir=tmp_dir)
seg_local_visualizer.dataset_meta = dict(
classes=('road', 'sidewalk', 'building', 'wall', 'fence',
'pole', 'traffic light', 'traffic sign',
Expand Down Expand Up @@ -165,6 +163,10 @@ def test_cityscapes_add_datasample_forward(gt_sem_seg):
osp.join(tmp_dir, 'vis_data', 'vis_image',
out_file + '_0.png'), (h, w, 3))

if torch.cuda.is_available():
test_cityscapes_add_datasample_forward(gt_sem_seg.cuda())
test_cityscapes_add_datasample_forward(gt_sem_seg)

def _assert_image_and_shape(self, out_file, out_shape):
assert os.path.exists(out_file)
drawn_img = cv2.imread(out_file)
Expand Down