paddleOCR的onnx实现
Project description
paddle-onnxocr
安装
pip install --no-cache-dir paddle-onnxocr
使用示例
单次推理
from paddleONNXOCR import PredictSystem
from paddleONNXOCR.predict.ocr_dataclass import OCRResult
async def main():
"""
推理在线图片
:return:
"""
async with PredictSystem() as predictor_system:
ocr_result: OCRResult = await predictor_system.predict(
"https://wx2.sinaimg.cn/mw690/005AKOR6ly1hvv14x3e1rj30j615hwfl.jpg"
)
print(ocr_result.text)
print(ocr_result.json)
if __name__ == '__main__':
import asyncio
asyncio.run(main())
批量推理
import cv2
from PIL import Image
from typing import AsyncGenerator
from paddleONNXOCR import PredictSystem
from paddleONNXOCR.predict.ocr_dataclass import OCRResult
async def main():
"""
推理在线图片
:return:
"""
async with PredictSystem() as predictor_system:
ocr_result: AsyncGenerator[OCRResult, None] = predictor_system.predict_batch([
"https://wx2.sinaimg.cn/mw690/005AKOR6ly1hvv14x3e1rj30j615hwfl.jpg",
cv2.imread("test.png"),
Image.open("test.png")
])
async for result in ocr_result:
if result is not None:
print(result.text)
print(result.json)
if __name__ == '__main__':
import asyncio
asyncio.run(main())
默认情况下,会自动从modelscope下载以下模型:
PP-LCNet_x0_25_text_line_ori_infer.onnx-->文本行方向检测模型
PP-LCNet_x1_0_doc_ori.onnx->文档方向分类
PP-OCRv5_mobile_det_infer.onnx->文本检测mobile模型
PP-OCRv5_mobile_rec_infer.onnx->文本识别mobile模型
更改模型
from paddleONNXOCR import PredictSystem
from paddleONNXOCR.models_enum import DetModels, RecModels
# 切换成server版本
PredictSystem(det_model_name=DetModels.SERVER, rec_model_name=RecModels.SERVER)
传递本地模型路径
from paddleONNXOCR import PredictSystem
PredictSystem(det_model_path="testDir/xxx.onnx")
模型启用
from paddleONNXOCR import PredictSystem
PredictSystem()
# use_angle_cls: 启用文本放方向检测,默认True
# use_deskew: 启用倾斜图像旋转矫正,默认False
# use_uvdoc: 启用图像矫正,默认False
# use_doc_cls: 启用图像方向分类,默认True
PS:具体参数请点到每一个方法内,有完整解释。
api接口服务
提供了dokcer构建启动的方式. 执行bash命令,自动构建docker服务启动. windows下请使用wsl子系统.
bash run.sh
依赖项目
opencv-python-headless
shapely
pyclipper
onnxruntime
pillow
validators
aiohttp
psutil
deskew
modelscope
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