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- # Copyright (c) Alibaba, Inc. and its affiliates.
-
- import unittest
-
- from PIL import Image
-
- from modelscope.hub.snapshot_download import snapshot_download
- from modelscope.models import Model
- from modelscope.outputs import OutputKeys
- from modelscope.pipelines import pipeline
- from modelscope.pipelines.cv import ImageDenoisePipeline
- from modelscope.utils.constant import Tasks
- from modelscope.utils.test_utils import test_level
-
-
- class ImageDenoiseTest(unittest.TestCase):
- model_id = 'damo/cv_nafnet_image-denoise_sidd'
- demo_image_path = 'data/test/images/noisy-demo-1.png'
-
- @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
- def test_run_by_direct_model_download(self):
- cache_path = snapshot_download(self.model_id)
- pipeline = ImageDenoisePipeline(cache_path)
- denoise_img = pipeline(
- input=self.demo_image_path)[OutputKeys.OUTPUT_IMG]
- denoise_img = Image.fromarray(denoise_img)
- w, h = denoise_img.size
- print('pipeline: the shape of output_img is {}x{}'.format(h, w))
-
- @unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
- def test_run_with_model_from_modelhub(self):
- model = Model.from_pretrained(self.model_id)
- pipeline_ins = pipeline(task=Tasks.image_denoise, model=model)
- denoise_img = pipeline_ins(
- input=self.demo_image_path)[OutputKeys.OUTPUT_IMG]
- denoise_img = Image.fromarray(denoise_img)
- w, h = denoise_img.size
- print('pipeline: the shape of output_img is {}x{}'.format(h, w))
-
- @unittest.skipUnless(test_level() >= 1, 'skip test in current test level')
- def test_run_with_model_name(self):
- pipeline_ins = pipeline(task=Tasks.image_denoise, model=self.model_id)
- denoise_img = pipeline_ins(
- input=self.demo_image_path)[OutputKeys.OUTPUT_IMG]
- denoise_img = Image.fromarray(denoise_img)
- w, h = denoise_img.size
- print('pipeline: the shape of output_img is {}x{}'.format(h, w))
-
- @unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
- def test_run_with_default_model(self):
- pipeline_ins = pipeline(task=Tasks.image_denoise)
- denoise_img = pipeline_ins(
- input=self.demo_image_path)[OutputKeys.OUTPUT_IMG]
- denoise_img = Image.fromarray(denoise_img)
- w, h = denoise_img.size
- print('pipeline: the shape of output_img is {}x{}'.format(h, w))
-
-
- if __name__ == '__main__':
- unittest.main()
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