mirror of
https://github.com/modelscope/modelscope.git
synced 2025-12-22 19:19:21 +01:00
50 lines
1.8 KiB
Python
50 lines
1.8 KiB
Python
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# Copyright (c) Alibaba, Inc. and its affiliates.
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import pdb
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import unittest
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import cv2
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import numpy as np
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from PIL import Image
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from modelscope.outputs import OutputKeys
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from modelscope.pipelines import pipeline
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from modelscope.pipelines.base import Pipeline
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from modelscope.utils.constant import Tasks
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from modelscope.utils.test_utils import test_level
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class Body3DKeypointsTest(unittest.TestCase):
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def setUp(self) -> None:
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self.model_id = 'damo/cv_canonical_body-3d-keypoints_video'
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self.test_video = 'data/test/videos/Walking.54138969.mp4'
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def pipeline_inference(self, pipeline: Pipeline, pipeline_input):
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output = pipeline(pipeline_input)
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poses = np.array(output[OutputKeys.POSES])
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print(f'result 3d points shape {poses.shape}')
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@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
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def test_run_modelhub_with_video_file(self):
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body_3d_keypoints = pipeline(
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Tasks.body_3d_keypoints, model=self.model_id)
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self.pipeline_inference(body_3d_keypoints, self.test_video)
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@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
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def test_run_modelhub_with_video_stream(self):
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body_3d_keypoints = pipeline(Tasks.body_3d_keypoints)
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cap = cv2.VideoCapture(self.test_video)
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if not cap.isOpened():
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raise Exception('modelscope error: %s cannot be decoded by OpenCV.'
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% (self.test_video))
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self.pipeline_inference(body_3d_keypoints, cap)
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@unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
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def test_run_modelhub_default_model(self):
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body_3d_keypoints = pipeline(Tasks.body_3d_keypoints)
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self.pipeline_inference(body_3d_keypoints, self.test_video)
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if __name__ == '__main__':
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unittest.main()
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