mirror of
https://github.com/modelscope/modelscope.git
synced 2025-12-17 00:37:43 +01:00
94ce1ebd7a
* Add loftr image local feature matching. * add pipeline doc str and remove example data as examples exists in data/test * update pipeline doc str. * add pipeline doc str add pipeline doc str --------- Co-authored-by: 翼生 <heyisheng.hys@alibaba-inc.com> Co-authored-by: wenmeng zhou <wenmeng.zwm@alibaba-inc.com>
40 lines
1.3 KiB
Python
40 lines
1.3 KiB
Python
# Copyright (c) Alibaba, Inc. and its affiliates.
|
|
|
|
import unittest
|
|
from pathlib import Path
|
|
|
|
import cv2
|
|
import matplotlib.cm as cm
|
|
import numpy as np
|
|
|
|
from modelscope.outputs import OutputKeys
|
|
from modelscope.pipelines import pipeline
|
|
from modelscope.utils.constant import Tasks
|
|
from modelscope.utils.cv.image_utils import match_pair_visualization
|
|
from modelscope.utils.test_utils import test_level
|
|
|
|
|
|
class ImageLocalFeatureMatchingTest(unittest.TestCase):
|
|
|
|
def setUp(self) -> None:
|
|
self.task = 'image-local-feature-matching'
|
|
self.model_id = 'Damo_XR_Lab/cv_resnet-transformer_local-feature-matching_outdoor-data'
|
|
|
|
@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
|
|
def test_image_local_feature_matching(self):
|
|
input_location = [[
|
|
'data/test/images/image_matching1.jpg',
|
|
'data/test/images/image_matching2.jpg'
|
|
]]
|
|
estimator = pipeline(Tasks.image_local_feature_matching, model=self.model_id)
|
|
result = estimator(input_location)
|
|
kpts0, kpts1, conf = result[0][OutputKeys.MATCHES]
|
|
vis_img = result[0][OutputKeys.OUTPUT_IMG]
|
|
cv2.imwrite("vis_demo.jpg", vis_img)
|
|
|
|
print('test_image_local_feature_matching DONE')
|
|
|
|
|
|
if __name__ == '__main__':
|
|
unittest.main()
|