mirror of https://github.com/alibaba/EasyCV.git
50 lines
1.8 KiB
Python
50 lines
1.8 KiB
Python
# Copyright (c) Alibaba, Inc. and its affiliates.
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import unittest
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import cv2
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from tests.ut_config import PRETRAINED_MODEL_FACE_2D_KEYPOINTS
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from easycv.predictors.face_keypoints_predictor import FaceKeypointsPredictor
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class FaceKeypointsPredictorWithoutDetectorTest(unittest.TestCase):
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def setUp(self):
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print(('Testing %s.%s' % (type(self).__name__, self._testMethodName)))
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self.image_path = './data/test/face_2d_keypoints/data/002258.png'
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self.save_image_path = './data/test/face_2d_keypoints/data/result_002258.png'
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self.model_path = PRETRAINED_MODEL_FACE_2D_KEYPOINTS
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self.model_config_path = './configs/face/face_96x96_wingloss.py'
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def test_single(self):
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predict_pipeline = FaceKeypointsPredictor(
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model_path=self.model_path, config_file=self.model_config_path)
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output = predict_pipeline(self.image_path)[0]
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output_keypoints = output['point']
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output_pose = output['pose']
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img = cv2.imread(self.image_path)
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image_show = predict_pipeline.show_result(
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img, output_keypoints, scale=2, save_path=self.save_image_path)
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self.assertEqual(output_keypoints.shape[0], 106)
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self.assertEqual(output_keypoints.shape[1], 2)
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self.assertEqual(output_pose.shape[0], 3)
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def test_batch(self):
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predict_pipeline = FaceKeypointsPredictor(
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model_path=self.model_path,
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config_file=self.model_config_path,
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batch_size=2)
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total_samples = 3
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output = predict_pipeline([self.image_path] * total_samples)
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self.assertEqual(len(output), total_samples)
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for out in output:
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self.assertEqual(out['point'].shape, (106, 2))
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self.assertEqual(out['pose'].shape, (3, ))
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if __name__ == '__main__':
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unittest.main()
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