# Copyright (c) Alibaba, Inc. and its affiliates. import io import os import os.path as osp import sys import unittest import cv2 from moviepy.editor import ImageSequenceClip from modelscope.hub.snapshot_download import snapshot_download from modelscope.models.cv.face_reconstruction.utils import write_obj from modelscope.outputs import OutputKeys from modelscope.pipelines import pipeline from modelscope.pipelines.base import Pipeline from modelscope.utils.constant import Tasks from modelscope.utils.test_utils import test_level sys.path.append('.') class FaceReconstructionTest(unittest.TestCase): def setUp(self) -> None: self.task = Tasks.face_reconstruction self.model_id = 'damo/cv_resnet50_face-reconstruction' self.test_image = 'data/test/images/face_reconstruction.jpg' def save_results(self, result, save_root): os.makedirs(save_root, exist_ok=True) # export obj and texture mesh = result[OutputKeys.OUTPUT]['mesh'] texture_map = result[OutputKeys.OUTPUT_IMG] mesh['texture_map'] = texture_map write_obj(os.path.join(save_root, 'hrn_mesh_mid.obj'), mesh) # export rotation video frame_list = result[OutputKeys.OUTPUT]['frame_list'] video = ImageSequenceClip(sequence=frame_list, fps=30) video.write_videofile( os.path.join(save_root, 'rotate.mp4'), fps=30, audio=False) del frame_list # save visualization image vis_image = result[OutputKeys.OUTPUT]['vis_image'] cv2.imwrite(os.path.join(save_root, 'vis_image.jpg'), vis_image) print(f'Output written to {osp.abspath(save_root)}') def pipeline_inference(self, pipeline: Pipeline, input_location: str): result = pipeline(input_location) self.save_results(result, './face_reconstruction_results') @unittest.skipUnless(test_level() >= 2, 'skip test in current test level') def test_run_by_direct_model_download(self): model_dir = snapshot_download(self.model_id, revision='v2.0.0-HRN') face_reconstruction = pipeline( Tasks.face_reconstruction, model=model_dir) self.pipeline_inference(face_reconstruction, self.test_image) @unittest.skipUnless(test_level() >= 2, 'skip test in current test level') def test_run_modelhub(self): face_reconstruction = pipeline( Tasks.face_reconstruction, model=self.model_id, model_revision='v2.0.0-HRN') self.pipeline_inference(face_reconstruction, self.test_image) if __name__ == '__main__': unittest.main()