Files

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Python

# -*- encoding: utf-8 -*-
# @Author: SWHL
# @Contact: liekkaskono@163.com
import ctypes
import sys
from pathlib import Path
import cv2
import numpy as np
import pytest
from pytest import mark
root_dir = Path(__file__).resolve().parent.parent
sys.path.append(str(root_dir))
from rapidocr import (
EngineType,
LangRec,
LoadImageError,
ModelType,
OCRVersion,
RapidOCR,
)
from rapidocr.utils.load_image import LoadImage, MemoryImage, RawMemoryImage
from rapidocr.utils.parse_parameters import ParseParams
test_dir = root_dir / "tests" / "test_files"
img_path = test_dir / "ch_en_num.jpg"
config_path = root_dir / "rapidocr" / "config.yaml"
@pytest.fixture()
def engine():
engine = RapidOCR(
params={
"Det.ocr_version": OCRVersion.PPOCRV4,
"Det.model_type": ModelType.MOBILE,
"Det.engine_type": EngineType.ONNXRUNTIME,
"Cls.ocr_version": OCRVersion.PPOCRV4,
"Cls.model_type": ModelType.MOBILE,
"Cls.engine_type": EngineType.ONNXRUNTIME,
"Rec.ocr_version": OCRVersion.PPOCRV4,
"Rec.model_type": ModelType.MOBILE,
"Rec.engine_type": EngineType.ONNXRUNTIME,
"Rec.lang_type": LangRec.CH,
}
)
return engine
def test_exif_transpose(engine):
img_path = test_dir / "img_exif_orientation.jpg"
result = engine(img_path, use_cls=False)
assert result.txts[0] == "我是中国人"
@mark.parametrize(
"img_name,gt",
[
(
"black_font_color_transparent.png",
"我是中国人",
),
(
"white_font_color_transparent.png",
"我是中国人",
),
],
)
def test_transparent_img(engine, img_name: str, gt: str):
img_path = test_dir / img_name
result = engine(img_path)
assert result.txts[0] == gt
def test_long_img(engine):
img_url = "https://www.modelscope.cn/models/RapidAI/RapidOCR/resolve/master/resources/test_files/long.jpeg"
result = engine(img_url)
assert result is not None
assert len(result.boxes) >= 53
def test_full_black_img(engine):
img_path = test_dir / "empty_black.jpg"
result = engine(img_path)
assert result.img is None
assert result.boxes is None
def test_img_url_input(engine):
img_url = "https://www.modelscope.cn/models/RapidAI/RapidOCR/resolve/master/resources/test_files/ch_en_num.jpg"
result = engine(img_url)
assert result.txts is not None
assert result.txts[0] == "正品促销"
def test_empty(engine):
img = None
with pytest.raises(LoadImageError) as exc_info:
engine(img)
raise LoadImageError
assert exc_info.type is LoadImageError
def test_zeros(engine):
img = np.zeros([640, 640, 3], np.uint8)
result = engine(img)
assert result.boxes is None
def test_input_str(engine):
result = engine(str(img_path))
assert len(result) == 18
assert result.txts[0] == "正品促销"
def test_input_bytes(engine):
with open(img_path, "rb") as f:
result = engine(f.read())
assert len(result) == 18
assert result.txts[0] == "正品促销"
def test_input_memory_image(engine):
"""An encoded image can be passed by address and byte length."""
encoded = img_path.read_bytes()
buffer = ctypes.create_string_buffer(encoded)
memory_img = MemoryImage(ctypes.addressof(buffer), len(encoded))
result = engine(memory_img)
assert len(result) == 18
assert result.txts[0] == "正品促销"
def test_input_memory_image_matches_bytes(engine):
encoded = img_path.read_bytes()
buffer = ctypes.create_string_buffer(encoded)
memory_img = MemoryImage(ctypes.addressof(buffer), len(encoded))
expected = engine(encoded)
actual = engine(memory_img)
assert actual.txts == expected.txts
assert actual.scores == expected.scores
np.testing.assert_allclose(actual.boxes, expected.boxes)
@pytest.mark.parametrize(
"address,length",
[(0, 1), (-1, 1), (1, 0), (1, -1)],
)
def test_input_memory_image_invalid_address_or_length(address, length):
loader = LoadImage()
with pytest.raises(LoadImageError, match="MemoryImage loading failed"):
loader(MemoryImage(address, length))
def test_input_memory_image_invalid_encoded_data():
encoded = b"not an image"
buffer = ctypes.create_string_buffer(encoded)
loader = LoadImage()
with pytest.raises(LoadImageError, match="MemoryImage loading failed"):
loader(MemoryImage(ctypes.addressof(buffer), len(encoded)))
def make_raw_memory_image(img, pixel_format, stride=None, bottom_up=False):
height, width = img.shape[:2]
row_bytes = img.shape[1] * (1 if img.ndim == 2 else img.shape[2])
stride = row_bytes if stride is None else stride
rows = img[::-1] if bottom_up else img
raw = bytearray(stride * height)
for row_index, row in enumerate(rows):
row_data = row.tobytes()
raw[row_index * stride : row_index * stride + row_bytes] = row_data
buffer = ctypes.create_string_buffer(bytes(raw))
memory_img = RawMemoryImage(
ctypes.addressof(buffer),
len(raw),
width,
height,
pixel_format=pixel_format,
stride=stride,
bottom_up=bottom_up,
)
return memory_img, buffer
def test_input_raw_memory_image(engine):
img = cv2.imread(str(img_path))
memory_img, buffer = make_raw_memory_image(img, "BGR")
result = engine(memory_img)
assert buffer is not None # Keep the backing memory alive through inference.
assert len(result) == 18
assert result.txts[0] == "正品促销"
@pytest.mark.parametrize(
"pixel_format,source",
[
("BGR", np.array([[[1, 2, 3], [4, 5, 6]]], dtype=np.uint8)),
("RGB", np.array([[[3, 2, 1], [6, 5, 4]]], dtype=np.uint8)),
("BGRA", np.array([[[1, 2, 3, 0], [4, 5, 6, 255]]], dtype=np.uint8)),
("BGRX", np.array([[[1, 2, 3, 8], [4, 5, 6, 9]]], dtype=np.uint8)),
("RGBA", np.array([[[3, 2, 1, 0], [6, 5, 4, 255]]], dtype=np.uint8)),
("RGBX", np.array([[[3, 2, 1, 8], [6, 5, 4, 9]]], dtype=np.uint8)),
],
)
def test_raw_memory_image_converts_to_bgr(pixel_format, source):
memory_img, buffer = make_raw_memory_image(source, pixel_format)
result = LoadImage()(memory_img)
assert buffer is not None
np.testing.assert_array_equal(
result, np.array([[[1, 2, 3], [4, 5, 6]]], dtype=np.uint8)
)
def test_raw_memory_image_supports_gray_stride_and_bottom_up():
gray = np.array([[10, 20], [30, 40]], dtype=np.uint8)
memory_img, buffer = make_raw_memory_image(
gray, "GRAY8", stride=4, bottom_up=True
)
result = LoadImage()(memory_img)
assert buffer is not None
expected = cv2.cvtColor(gray, cv2.COLOR_GRAY2BGR)
np.testing.assert_array_equal(result, expected)
@pytest.mark.parametrize(
"kwargs,error",
[
({"address": 0}, "invalid memory address"),
({"width": 0}, "width and height must be positive"),
({"pixel_format": "YUV"}, "unsupported pixel format"),
({"stride": 5}, "stride .* is smaller than row size"),
({"length": 8}, "buffer is too small"),
],
)
def test_raw_memory_image_rejects_invalid_metadata(kwargs, error):
raw = bytes(12)
buffer = ctypes.create_string_buffer(raw)
params = {
"address": ctypes.addressof(buffer),
"length": len(raw),
"width": 2,
"height": 2,
"pixel_format": "BGR",
"stride": 6,
}
params.update(kwargs)
with pytest.raises(LoadImageError, match=error):
LoadImage()(RawMemoryImage(**params))
def test_input_path(engine):
result = engine(img_path)
assert len(result) == 18
assert result.txts[0] == "正品促销"
def test_input_parameters(engine):
result = engine(img_path, text_score=1.0)
assert result.boxes is None
@mark.parametrize("params", [{"text_score": 0.5}, {"Global": 0.5}, {"Unknown.key": 1}])
def test_invalid_init_parameters(params):
cfg = ParseParams.load(config_path)
with pytest.raises(ValueError):
ParseParams.update_batch(cfg, params)
def test_nested_init_parameters():
cfg = ParseParams.load(config_path)
ParseParams.update_batch(cfg, {"EngineConfig.onnxruntime.use_cuda": True})
assert cfg.EngineConfig.onnxruntime.use_cuda is True
def test_input_three_ndim_two_channel(engine):
img_npy = test_dir / "two_dim_image.npy"
image_array = np.load(str(img_npy))
result = engine(image_array)
assert result is not None
assert len(result) == 1
assert result.txts[0] == "TREND PLOT REPORT"
def test_input_three_ndim_one_channel(engine):
img = cv2.imread(str(img_path))
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
img = img[:, :, 0]
img = img[..., None] # (H, W, 1)
result = engine(img)
assert len(result) >= 17
def test_mode_one_img(engine):
img_path = test_dir / "issue_170.png"
result = engine(img_path)
assert result.txts[0] == "TEST"
@mark.parametrize(
"img_name,gt_len,gt_first_len",
[
(
"test_letterbox_like.jpg",
2,
"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",
),
("test_without_det.jpg", 1, "在中国作家协会第三届儿童文学"),
],
)
def test_letterbox_like(engine, img_name, gt_len, gt_first_len):
img_path = test_dir / img_name
result = engine(img_path)
assert len(result) == gt_len
assert result.txts[0].lower() == gt_first_len.lower()