import os import shutil import urllib import pytest from mmdet.apis import init_detector from mmocr.apis.inference import model_inference def test_model_inference(): project_dir = os.path.abspath(os.path.dirname(os.path.dirname(__file__))) print(project_dir) config_file = os.path.join( project_dir, '../configs/textrecog/sar/sar_r31_parallel_decoder_academic.py') checkpoint_file = os.path.join( project_dir, '../checkpoints/sar_r31_parallel_decoder_academic-dba3a4a3.pth') if not os.path.exists(checkpoint_file): url = ('https://download.openmmlab.com/mmocr' '/textrecog/sar/' 'sar_r31_parallel_decoder_academic-dba3a4a3.pth') print(f'Downloading {url} ...') local_filename, _ = urllib.request.urlretrieve(url) os.makedirs(os.path.dirname(checkpoint_file), exist_ok=True) shutil.move(local_filename, checkpoint_file) print(f'Saved as {checkpoint_file}') else: print(f'Using existing checkpoint {checkpoint_file}') device = 'cpu' model = init_detector( config_file, checkpoint=checkpoint_file, device=device) if model.cfg.data.test['type'] == 'ConcatDataset': model.cfg.data.test.pipeline = model.cfg.data.test['datasets'][ 0].pipeline img = os.path.join(project_dir, '../demo/demo_text_recog.jpg') with pytest.raises(AssertionError): model_inference(model, 1) model_inference(model, img)