# Copyright (c) Alibaba, Inc. and its affiliates. import os.path as osp import unittest import cv2 from modelscope.msdatasets import MsDataset from modelscope.pipelines import pipeline from modelscope.utils.constant import Tasks from modelscope.utils.cv.image_utils import draw_face_detection_result from modelscope.utils.demo_utils import DemoCompatibilityCheck from modelscope.utils.test_utils import test_level class FaceDetectionTest(unittest.TestCase, DemoCompatibilityCheck): def setUp(self) -> None: self.task = Tasks.face_detection self.model_id = 'damo/cv_resnet_facedetection_scrfd10gkps' def show_result(self, img_path, detection_result): img = draw_face_detection_result(img_path, detection_result) cv2.imwrite('result.png', img) print(f'output written to {osp.abspath("result.png")}') @unittest.skipUnless(test_level() >= 1, 'skip test in current test level') def test_run_with_dataset(self): input_location = ['data/test/images/face_detection2.jpeg'] dataset = MsDataset.load(input_location, target='image') face_detection = pipeline(Tasks.face_detection, model=self.model_id) # note that for dataset output, the inference-output is a Generator that can be iterated. result = face_detection(dataset) result = next(result) self.show_result(input_location[0], result) @unittest.skipUnless(test_level() >= 0, 'skip test in current test level') def test_run_modelhub(self): face_detection = pipeline(Tasks.face_detection, model=self.model_id) img_path = 'data/test/images/face_detection2.jpeg' result = face_detection(img_path) self.show_result(img_path, result) @unittest.skipUnless(test_level() >= 2, 'skip test in current test level') def test_run_modelhub_default_model(self): face_detection = pipeline(Tasks.face_detection) img_path = 'data/test/images/face_detection2.jpeg' result = face_detection(img_path) self.show_result(img_path, result) @unittest.skipUnless(test_level() >= 0, 'skip test in current test level') def test_demo_compatibility(self): self.compatibility_check() if __name__ == '__main__': unittest.main()