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61 lines
2.5 KiB
Python
61 lines
2.5 KiB
Python
# Copyright (c) Alibaba, Inc. and its affiliates.
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import unittest
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from modelscope.hub.snapshot_download import snapshot_download
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from modelscope.models import Model
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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.cv import ImageDenoisePipeline
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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 ImageDenoiseTest(unittest.TestCase):
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def setUp(self) -> None:
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self.task = Tasks.image_denoising
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self.model_id = 'damo/cv_nafnet_image-denoise_sidd'
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demo_image_path = 'https://modelscope.oss-cn-beijing.aliyuncs.com/test/images/noisy-demo-0.png'
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@unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
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def test_run_by_direct_model_download(self):
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cache_path = snapshot_download(self.model_id)
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pipeline = ImageDenoisePipeline(cache_path)
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pipeline.group_key = self.task
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denoise_img = pipeline(
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input=self.demo_image_path)[OutputKeys.OUTPUT_IMG] # BGR
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h, w = denoise_img.shape[:2]
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print('pipeline: the shape of output_img is {}x{}'.format(h, w))
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@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
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def test_run_with_model_from_modelhub(self):
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model = Model.from_pretrained(self.model_id)
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pipeline_ins = pipeline(task=Tasks.image_denoising, model=model)
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denoise_img = pipeline_ins(
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input=self.demo_image_path)[OutputKeys.OUTPUT_IMG] # BGR
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h, w = denoise_img.shape[:2]
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print('pipeline: the shape of output_img is {}x{}'.format(h, w))
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@unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
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def test_run_with_model_name(self):
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pipeline_ins = pipeline(
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task=Tasks.image_denoising, model=self.model_id)
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denoise_img = pipeline_ins(
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input=self.demo_image_path)[OutputKeys.OUTPUT_IMG] # BGR
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h, w = denoise_img.shape[:2]
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print('pipeline: the shape of output_img is {}x{}'.format(h, w))
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@unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
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def test_run_with_default_model(self):
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pipeline_ins = pipeline(task=Tasks.image_denoising)
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denoise_img = pipeline_ins(
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input=self.demo_image_path)[OutputKeys.OUTPUT_IMG] # BGR
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h, w = denoise_img.shape[:2]
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print('pipeline: the shape of output_img is {}x{}'.format(h, w))
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if __name__ == '__main__':
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unittest.main()
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