mirror of
https://github.com/open-mmlab/mmsegmentation.git
synced 2025-06-03 22:03:48 +08:00
58 lines
1.8 KiB
Python
58 lines
1.8 KiB
Python
# Copyright (c) OpenMMLab. All rights reserved.
|
|
import os.path as osp
|
|
|
|
import mmcv
|
|
import numpy as np
|
|
import pytest
|
|
from PIL import Image
|
|
|
|
from mmseg.datasets.pipelines import PhotoMetricDistortion, RandomCrop
|
|
|
|
|
|
def test_random_crop():
|
|
# test assertion for invalid random crop
|
|
with pytest.raises(AssertionError):
|
|
RandomCrop(crop_size=(-1, 0))
|
|
|
|
results = dict()
|
|
img = mmcv.imread(osp.join('tests/data/color.jpg'), 'color')
|
|
seg = np.array(Image.open(osp.join('tests/data/seg.png')))
|
|
results['img'] = img
|
|
results['gt_semantic_seg'] = seg
|
|
results['seg_fields'] = ['gt_semantic_seg']
|
|
results['img_shape'] = img.shape
|
|
results['ori_shape'] = img.shape
|
|
# Set initial values for default meta_keys
|
|
results['pad_shape'] = img.shape
|
|
results['scale_factor'] = 1.0
|
|
|
|
h, w, _ = img.shape
|
|
pipeline = RandomCrop(crop_size=(h - 20, w - 20))
|
|
|
|
results = pipeline(results)
|
|
assert results['img'].shape[:2] == (h - 20, w - 20)
|
|
assert results['img_shape'][:2] == (h - 20, w - 20)
|
|
assert results['gt_semantic_seg'].shape[:2] == (h - 20, w - 20)
|
|
|
|
|
|
def test_photo_metric_distortion():
|
|
|
|
results = dict()
|
|
img = mmcv.imread(osp.join('tests/data/color.jpg'), 'color')
|
|
seg = np.array(Image.open(osp.join('tests/data/seg.png')))
|
|
results['img'] = img
|
|
results['gt_semantic_seg'] = seg
|
|
results['seg_fields'] = ['gt_semantic_seg']
|
|
results['img_shape'] = img.shape
|
|
results['ori_shape'] = img.shape
|
|
# Set initial values for default meta_keys
|
|
results['pad_shape'] = img.shape
|
|
results['scale_factor'] = 1.0
|
|
|
|
pipeline = PhotoMetricDistortion()
|
|
results = pipeline(results)
|
|
|
|
assert not ((results['img'] == img).all())
|
|
assert (results['gt_semantic_seg'] == seg).all()
|
|
assert results['img_shape'] == img.shape
|