import unittest import cv2 import PIL from modelscope.outputs import OutputKeys from modelscope.pipelines import pipeline from modelscope.utils.constant import Tasks from modelscope.utils.cv.image_utils import semantic_seg_masks_to_image from modelscope.utils.logger import get_logger from modelscope.utils.test_utils import test_level class ImageSemanticSegmentationTest(unittest.TestCase): @unittest.skipUnless(test_level() >= 0, 'skip test in current test level') def test_image_semantic_segmentation_panmerge(self): input_location = 'data/test/images/image_semantic_segmentation.jpg' model_id = 'damo/cv_swinL_semantic-segmentation_cocopanmerge' segmenter = pipeline(Tasks.image_segmentation, model=model_id) result = segmenter(input_location) draw_img = semantic_seg_masks_to_image(result[OutputKeys.MASKS]) cv2.imwrite('result.jpg', draw_img) print('test_image_semantic_segmentation_panmerge DONE') PIL_array = PIL.Image.open(input_location) result = segmenter(PIL_array) draw_img = semantic_seg_masks_to_image(result[OutputKeys.MASKS]) cv2.imwrite('result.jpg', draw_img) print('test_image_semantic_segmentation_panmerge_from_PIL DONE') @unittest.skipUnless(test_level() >= 0, 'skip test in current test level') def test_image_semantic_segmentation_vitadapter(self): input_location = 'data/test/images/image_semantic_segmentation.jpg' model_id = 'damo/cv_vitadapter_semantic-segmentation_cocostuff164k' segmenter = pipeline(Tasks.image_segmentation, model=model_id) result = segmenter(input_location) draw_img = semantic_seg_masks_to_image(result[OutputKeys.MASKS]) cv2.imwrite('result.jpg', draw_img) print('test_image_semantic_segmentation_vitadapter DONE') PIL_array = PIL.Image.open(input_location) result = segmenter(PIL_array) draw_img = semantic_seg_masks_to_image(result[OutputKeys.MASKS]) cv2.imwrite('result.jpg', draw_img) print('test_image_semantic_segmentation_vitadapter_from_PIL DONE') if __name__ == '__main__': unittest.main()