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https://github.com/open-mmlab/mmocr.git
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18c54afbdc
* Add support for numpy arrays in model_inference * Add test for numpy ndarray inference * Fix linting problems * Add support for batch inference * Add batch inference demo script * Fix comment * Test batch inference with paths and arrays * lint code * Update model_inference docstring * Refactor model inference tests * Change inference function to make text detectors and recognizers use the same input data types * Change single state text detector model to support batch inference * Lint code * simplify inference tests * Remove psenet from batch inference test cases to prevent the pytest being killed * Update batch_image_demo.py * fix bug when test with dataset fix bug when test with dataset, for example, `./tools/dist_test.sh configs/textrecog/sar/sar_r31_parallel_decoder_academic.py <checkpoint> 1 --eval acc` Co-authored-by: Hongbin Sun <hongbin306@gmail.com>
121 lines
4.0 KiB
Python
121 lines
4.0 KiB
Python
import os
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import pytest
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from mmcv.image import imread
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from mmdet.apis import init_detector
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from mmocr.apis.inference import model_inference
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from mmocr.datasets import build_dataset # noqa: F401
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from mmocr.models import build_detector # noqa: F401
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def build_model(config_file):
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device = 'cpu'
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model = init_detector(config_file, checkpoint=None, device=device)
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if model.cfg.data.test['type'] == 'ConcatDataset':
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model.cfg.data.test.pipeline = model.cfg.data.test['datasets'][
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0].pipeline
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return model
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def disable_aug_test(model):
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model.cfg.data.test.pipeline = [
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model.cfg.data.test.pipeline[0],
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*model.cfg.data.test.pipeline[1].transforms
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]
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return model
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@pytest.mark.parametrize('cfg_file', [
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'../configs/textrecog/sar/sar_r31_parallel_decoder_academic.py',
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'../configs/textrecog/crnn/crnn_academic_dataset.py',
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'../configs/textrecog/nrtr/nrtr_r31_1by16_1by8_academic.py',
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'../configs/textrecog/robust_scanner/robustscanner_r31_academic.py',
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'../configs/textrecog/seg/seg_r31_1by16_fpnocr_academic.py',
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'../configs/textdet/psenet/psenet_r50_fpnf_600e_icdar2017.py'
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])
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def test_model_inference(cfg_file):
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tmp_dir = os.path.abspath(os.path.dirname(os.path.dirname(__file__)))
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config_file = os.path.join(tmp_dir, cfg_file)
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model = build_model(config_file)
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with pytest.raises(AssertionError):
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model_inference(model, 1)
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sample_img_path = os.path.join(tmp_dir, '../demo/demo_text_det.jpg')
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model_inference(model, sample_img_path)
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# numpy inference
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img = imread(sample_img_path)
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model_inference(model, img)
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@pytest.mark.parametrize('cfg_file', [
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'../configs/textrecog/crnn/crnn_academic_dataset.py',
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'../configs/textrecog/seg/seg_r31_1by16_fpnocr_academic.py'
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])
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def test_model_batch_inference(cfg_file):
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tmp_dir = os.path.abspath(os.path.dirname(os.path.dirname(__file__)))
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config_file = os.path.join(tmp_dir, cfg_file)
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model = build_model(config_file)
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sample_img_path = os.path.join(tmp_dir, '../demo/demo_text_det.jpg')
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results = model_inference(model, [sample_img_path, sample_img_path])
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assert len(results) == 2
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# numpy inference
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img = imread(sample_img_path)
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results = model_inference(model, [img, img])
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assert len(results) == 2
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@pytest.mark.parametrize('cfg_file', [
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'../configs/textrecog/sar/sar_r31_parallel_decoder_academic.py',
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'../configs/textrecog/nrtr/nrtr_r31_1by16_1by8_academic.py',
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'../configs/textrecog/robust_scanner/robustscanner_r31_academic.py',
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])
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def test_model_batch_inference_raises_assertion_error_if_unsupported(cfg_file):
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tmp_dir = os.path.abspath(os.path.dirname(os.path.dirname(__file__)))
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config_file = os.path.join(tmp_dir, cfg_file)
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model = build_model(config_file)
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with pytest.raises(
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AssertionError,
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match='aug test does not support inference with batch size'):
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sample_img_path = os.path.join(tmp_dir, '../demo/demo_text_det.jpg')
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model_inference(model, [sample_img_path, sample_img_path])
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with pytest.raises(
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AssertionError,
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match='aug test does not support inference with batch size'):
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img = imread(sample_img_path)
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model_inference(model, [img, img])
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@pytest.mark.parametrize('cfg_file', [
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'../configs/textrecog/sar/sar_r31_parallel_decoder_academic.py',
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'../configs/textrecog/nrtr/nrtr_r31_1by16_1by8_academic.py',
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'../configs/textrecog/robust_scanner/robustscanner_r31_academic.py',
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])
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def test_model_batch_inference_recog(cfg_file):
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tmp_dir = os.path.abspath(os.path.dirname(os.path.dirname(__file__)))
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config_file = os.path.join(tmp_dir, cfg_file)
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model = build_model(config_file)
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model = disable_aug_test(model)
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sample_img_path = os.path.join(tmp_dir, '../demo/demo_text_det.jpg')
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results = model_inference(model, [sample_img_path, sample_img_path])
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assert len(results) == 2
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# numpy inference
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img = imread(sample_img_path)
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results = model_inference(model, [img, img])
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assert len(results) == 2
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