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50 lines
1.7 KiB
Python
50 lines
1.7 KiB
Python
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# Copyright 2021-2022 The Alibaba Fundamental Vision Team Authors. All rights reserved.
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import unittest
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import cv2
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import numpy as np
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import torch
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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.logger import get_logger
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from modelscope.utils.test_utils import test_level
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logger = get_logger()
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class ImageViewTransformTest(unittest.TestCase):
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def setUp(self) -> None:
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self.model_id = 'damo/cv_image-view-transform'
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image = Image.open(
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'data/test/images/image_view_transform_source_img.png')
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self.input = {
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'source_img': image,
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'target_view': [50.0, 0.0, 0.0, True, 3.0, 4, 50, 1.0]
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}
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def pipeline_inference(self, pipeline: Pipeline, input: str):
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result = pipeline(input)
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logger.info(result)
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cv2.imwrite('result.jpg', result[OutputKeys.OUTPUT_IMGS][0])
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print(np.sum(np.abs(result[OutputKeys.OUTPUT_IMGS][0])))
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@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
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def test_run_modelhub(self):
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image_view_transform = pipeline(
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Tasks.image_view_transform, model=self.model_id, revision='v1.0.3')
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self.pipeline_inference(image_view_transform, self.input)
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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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image_view_transform = pipeline(Tasks.image_view_transform)
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self.pipeline_inference(image_view_transform, self.input)
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if __name__ == '__main__':
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unittest.main()
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