hr-ocr-regbook/server.py

from fastapi import FastAPI, Request
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
from paddleocr import PaddleOCR
import cv2
from core.direction import AngleDetector
from utils.image import *
from utils.time import timeit
from utils.web import web_try
from core.ocr import IdCardOcr
import os

app = FastAPI()

origins = ["*"]

app.add_middleware(
    CORSMiddleware,
    allow_origins=origins,
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)
use_gpu = os.getenv('USE_CUDA') == 'gpu'
print(f'use gpu: {use_gpu}')

# 初始化ocr模型和后处理模型
ocr = PaddleOCR(use_angle_cls=True,
                rec_model_dir="./models/rec/",
                det_model_dir="./models/det/",
                cls_model_dir="./models/cls/",
                rec_algorithm='CRNN',
                ocr_version='PP-OCRv2',
                lang="ch",
                use_gpu=use_gpu,
                det_db_unclip_ratio=1.7,
                warmup=True)

# 初始化 角度检测器 对象
ad = AngleDetector(ocr)

m = IdCardOcr(ocr, ad)


@app.get("/ping")
def ping():
    return "pong!"

class ParamInfo(BaseModel):
    image: str
    image_type: str


@app.post("/ocr_system/regbook")
@web_try()
@timeit
def detect(request: Request, param: ParamInfo):
    image = base64_to_np(param.image)
    if image.size > 36000000:
        image = cv2.resize(image, (int(image.shape[0]*0.8), int(image.shape[1]*0.8)), interpolation=cv2.INTER_CUBIC)
    return m.predict(image, param.image_type)


if __name__ == '__main__':
    import uvicorn
    import argparse

    parser = argparse.ArgumentParser()
    parser.add_argument('--host', default='0.0.0.0')
    parser.add_argument('--port', default=8080)
    opt = parser.parse_args()

    app_str = 'server:app'  # make the app string equal to whatever the name of this file is
    uvicorn.run(app_str, host=opt.host, port=int(opt.port), reload=True)