mirror of
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250 lines
6.6 KiB
Python
250 lines
6.6 KiB
Python
# -*- encoding: utf-8 -*-
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# @Author: SWHL
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# @Contact: liekkaskono@163.com
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import sys
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from pathlib import Path
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import cv2
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import numpy as np
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import pytest
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from base_module import BaseModule
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root_dir = Path(__file__).resolve().parent.parent
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sys.path.append(str(root_dir))
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from rapidocr_paddle import LoadImageError, RapidOCR
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engine = RapidOCR()
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tests_dir = root_dir / "tests" / "test_files"
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img_path = tests_dir / "ch_en_num.jpg"
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package_name = "rapidocr_paddle"
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def test_mode_one_img():
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img_path = tests_dir / "issue_170.png"
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result, _ = engine(img_path)
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assert result[0][1] == "TEST"
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@pytest.mark.parametrize(
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"img_name,gt",
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[
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(
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"black_font_color_transparent.png",
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"我是中国人",
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),
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(
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"white_font_color_transparent.png",
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"我是中国人",
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),
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],
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)
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def test_transparent_img(img_name: str, gt: str):
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img_path = tests_dir / img_name
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result, _ = engine(img_path)
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assert result[0][1] == gt
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@pytest.mark.parametrize(
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"img_name,gt_len,gt_first_len",
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[
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(
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"test_letterbox_like.jpg",
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2,
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"A：：取决于所使用的执行提供者，它可能没有完全支持模型中的所有操作。回落到CPU操作可能会导致性能速度的下降。此外，即使一个操作是由CUDAeXecution",
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),
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("test_without_det.jpg", 1, "在中国作家协会第三届儿童文学"),
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],
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)
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def test_letterbox_like(img_name, gt_len, gt_first_len):
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img_path = tests_dir / img_name
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result, _ = engine(img_path)
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assert len(result) == gt_len
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assert result[0][1] == gt_first_len
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def test_only_det():
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result, _ = engine(img_path, use_det=True, use_cls=False, use_rec=False)
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assert len(result) == 18
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assert result[0][0] == [5.0, 2.0]
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def test_only_cls():
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img_path = tests_dir / "text_cls.jpg"
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result, _ = engine(img_path, use_det=False, use_cls=True, use_rec=False)
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assert len(result) == 1
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assert result[0][0] == "0"
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def test_only_rec():
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img_path = tests_dir / "text_rec.jpg"
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result, _ = engine(img_path, use_det=False, use_cls=False, use_rec=True)
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assert len(result) == 1
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assert result[0][0] == "韩国小馆"
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def test_det_rec():
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result, _ = engine(img_path, use_det=True, use_cls=False, use_rec=True)
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assert result[0][1] == "正品促销"
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assert len(result) == 18
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def test_cls_rec():
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img_path = tests_dir / "text_cls.jpg"
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result, _ = engine(img_path, use_det=False, use_cls=True, use_rec=True)
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assert len(result) == 1
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assert result[0][0] == "韩国小馆"
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def test_det_cls_rec():
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img = cv2.imread(str(img_path))
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result, _ = engine(img)
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assert result[0][1] == "正品促销"
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assert len(result) == 18
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def test_empty():
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img = None
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with pytest.raises(LoadImageError) as exc_info:
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engine(img)
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raise LoadImageError
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assert exc_info.type is LoadImageError
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def test_zeros():
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img = np.zeros([640, 640, 3], np.uint8)
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result, _ = engine(img)
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assert result is None
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def test_input_str():
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result, _ = engine(str(img_path))
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assert result[0][1] == "正品促销"
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assert len(result) == 18
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def test_input_bytes():
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with open(img_path, "rb") as f:
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result, _ = engine(f.read())
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assert result[0][1] == "正品促销"
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assert len(result) == 18
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def test_input_path():
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result, _ = engine(img_path)
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assert result[0][1] == "正品促销"
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assert len(result) == 18
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def test_input_parameters():
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img_path = tests_dir / "ch_en_num.jpg"
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engine = RapidOCR(text_score=1)
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result, _ = engine(img_path)
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assert result is None
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def test_input_det_parameters():
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with pytest.raises(FileNotFoundError) as exc_info:
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engine = RapidOCR(det_model_path="1.onnx")
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result, _ = engine(img_path)
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raise FileNotFoundError()
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assert exc_info.type is FileNotFoundError
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def test_input_cls_parameters():
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with pytest.raises(FileNotFoundError) as exc_info:
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engine = RapidOCR(cls_model_path="1.onnx")
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result, _ = engine(img_path)
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raise FileNotFoundError()
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assert exc_info.type is FileNotFoundError
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def test_input_rec_parameters():
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with pytest.raises(FileNotFoundError) as exc_info:
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engine = RapidOCR(rec_model_path="1.onnx")
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result, _ = engine(img_path)
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raise FileNotFoundError()
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assert exc_info.type is FileNotFoundError
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def test_input_three_ndim_two_channel():
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img_npy = tests_dir / "two_dim_image.npy"
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image_array = np.load(str(img_npy))
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result, _ = engine(image_array)
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assert len(result) == 1
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assert result[0][1] == "TREND PLOT REPORT"
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def test_input_three_ndim_one_channel():
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img = cv2.imread(str(img_path))
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img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
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img = img[:, :, 0]
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img = img[..., None] # (H, W, 1)
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result, _ = engine(img)
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assert result[0][1] == "正品促销"
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assert len(result) == 17
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def test_det():
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module_name = "ch_ppocr_v3_det"
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class_name = "TextDetector"
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base = BaseModule(package_name)
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TextDetector = base.init_module(module_name, class_name)
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yaml_path = base.package_dir / module_name / "config.yaml"
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config = base.read_yaml(str(yaml_path))
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config["model_path"] = str(base.package_dir / config["model_path"])
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text_det = TextDetector(config)
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img_path = base.tests_dir / "test_files" / "text_det.jpg"
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img = cv2.imread(str(img_path))
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dt_boxes, elapse = text_det(img)
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assert dt_boxes.shape == (18, 4, 2)
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def test_cls():
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module_name = "ch_ppocr_v2_cls"
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class_name = "TextClassifier"
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base = BaseModule(package_name=package_name)
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TextClassifier = base.init_module(module_name, class_name)
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yaml_path = base.package_dir / module_name / "config.yaml"
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config = base.read_yaml(str(yaml_path))
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config["model_path"] = str(base.package_dir / config["model_path"])
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text_cls = TextClassifier(config)
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img_path = base.tests_dir / "test_files" / "text_cls.jpg"
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img = cv2.imread(str(img_path))
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result = text_cls([img])
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assert result[1][0][0] == "180"
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def test_rec():
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module_name = "ch_ppocr_v3_rec"
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class_name = "TextRecognizer"
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base = BaseModule(package_name)
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TextRecognizer = base.init_module(module_name, class_name)
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yaml_path = base.package_dir / module_name / "config.yaml"
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config = base.read_yaml(str(yaml_path))
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config["model_path"] = str(base.package_dir / config["model_path"])
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text_rec = TextRecognizer(config)
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img_path = base.tests_dir / "test_files" / "text_rec.jpg"
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img = cv2.imread(str(img_path))
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rec_res, elapse = text_rec(img)
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assert rec_res[0][0] == "韩国小馆"
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