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88 lines
3.5 KiB
Python
88 lines
3.5 KiB
Python
# Copyright (c) Alibaba, Inc. and its affiliates.
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import unittest
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from modelscope.pipelines import pipeline
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from modelscope.utils.constant import Tasks
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from modelscope.utils.regress_test_utils import MsRegressTool
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from modelscope.utils.test_utils import test_level
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class GeneralImageClassificationTest(unittest.TestCase):
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def setUp(self) -> None:
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self.task = Tasks.image_classification
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self.model_id = 'damo/cv_vit-base_image-classification_Dailylife-labels'
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self.regress_tool = MsRegressTool(baseline=False)
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@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
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def test_run_ImageNet(self):
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general_image_classification = pipeline(
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Tasks.image_classification,
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model='damo/cv_vit-base_image-classification_ImageNet-labels')
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result = general_image_classification('data/test/images/bird.JPEG')
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print(result)
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@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
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def test_run_Dailylife(self):
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general_image_classification = pipeline(
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Tasks.image_classification,
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model='damo/cv_vit-base_image-classification_Dailylife-labels')
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with self.regress_tool.monitor_module_single_forward(
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general_image_classification.model,
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'vit_base_image_classification'):
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result = general_image_classification('data/test/images/bird.JPEG')
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print(result)
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@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
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def test_run_nextvit(self):
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nexit_image_classification = pipeline(
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Tasks.image_classification,
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model='damo/cv_nextvit-small_image-classification_Dailylife-labels'
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)
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result = nexit_image_classification('data/test/images/bird.JPEG')
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print(result)
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@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
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def test_run_convnext(self):
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convnext_image_classification = pipeline(
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Tasks.image_classification,
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model='damo/cv_convnext-base_image-classification_garbage')
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result = convnext_image_classification('data/test/images/banana.jpg')
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print(result)
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@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
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def test_run_beitv2(self):
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beitv2_image_classification = pipeline(
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Tasks.image_classification,
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model=
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'damo/cv_beitv2-base_image-classification_patch16_224_pt1k_ft22k_in1k'
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)
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result = beitv2_image_classification('data/test/images/bird.JPEG')
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print(result)
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@unittest.skipUnless(test_level() >= 2,
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'skip test for timm compatbile need 0.5.4')
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def test_run_easyrobust(self):
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robust_image_classification = pipeline(
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Tasks.image_classification, model='aaig/easyrobust-models')
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result = robust_image_classification('data/test/images/bird.JPEG')
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print(result)
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def test_run_bnext(self):
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nexit_image_classification = pipeline(
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Tasks.image_classification,
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model='damo/cv_bnext-small_image-classification_ImageNet-labels')
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result = nexit_image_classification('data/test/images/bird.JPEG')
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print(result)
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@unittest.skipUnless(test_level() >= 2, 'skip test in current test level')
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def test_run_Dailylife_default(self):
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general_image_classification = pipeline(Tasks.image_classification)
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result = general_image_classification('data/test/images/bird.JPEG')
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print(result)
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if __name__ == '__main__':
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unittest.main()
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