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64 lines
2.6 KiB
Python
64 lines
2.6 KiB
Python
# Copyright (c) Alibaba, Inc. and its affiliates.
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import os
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import os.path as osp
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import unittest
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import cv2
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import modelscope
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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.models.cv.image_driving_perception import YOLOPv2
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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.pipelines.cv import ImageDrivingPerceptionPipeline
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from modelscope.preprocessors.image import LoadImage
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from modelscope.utils.constant import Tasks
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from modelscope.utils.cv.image_utils import \
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show_image_driving_perception_result
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from modelscope.utils.test_utils import test_level
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class ImageDrivingPerceptionTest(unittest.TestCase):
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def setUp(self) -> None:
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self.model_id = 'damo/cv_yolopv2_image-driving-perception_bdd100k'
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self.img_path = 'data/test/images/image_driving_perception.jpg'
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def pipeline_inference(self, pipeline: Pipeline, img_path: str):
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result = pipeline(img_path)
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img = LoadImage.convert_to_ndarray(img_path)
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img = cv2.resize(img, (1280, 720), interpolation=cv2.INTER_LINEAR)
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show_image_driving_perception_result(
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img, result, out_file='result.jpg', if_draw=[1, 1, 1])
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print(f'Output written to {osp.abspath("result.jpg")}')
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@unittest.skipUnless(test_level() >= 0, 'skip test in current test level')
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def test_run_with_model_name(self):
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image_driving_perception_pipeline = pipeline(
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Tasks.image_driving_perception, model=self.model_id)
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self.pipeline_inference(image_driving_perception_pipeline,
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self.img_path)
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@unittest.skipUnless(test_level() >= 1, '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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image_driving_perception_pipeline = pipeline(
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task=Tasks.image_driving_perception, model=model)
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self.pipeline_inference(image_driving_perception_pipeline,
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self.img_path)
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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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model = YOLOPv2(cache_path)
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image_driving_perception_pipeline = ImageDrivingPerceptionPipeline(
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model, preprocessor=None)
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self.pipeline_inference(image_driving_perception_pipeline,
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self.img_path)
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if __name__ == '__main__':
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unittest.main()
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