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- from fastapi import FastAPI, Request
- from fastapi.middleware.cors import CORSMiddleware
- from pydantic import BaseModel
- from paddleocr import PaddleOCR
- from core.ocr import *
- from utils.image import *
- from utils.time import timeit
- from utils.web import web_try
- import os
- # 导入一些包
- app = FastAPI()
- origins = ["*"]
- # CORS 跨源资源共享
- 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}')
- ocr = PaddleOCR(use_angle_cls=True,
- rec_model_dir='models/rec/',
- det_model_dir='models/det/',
- cls_model_dir='models/cls/',
- rec_char_type='ch',
- use_gpu=use_gpu,
- warmup=True)
- p = Ocr(ocr)
- class PPOcrInfo(BaseModel):
- image: str
- # Get 健康检查
- @app.get("/ping")
- def ping():
- return "pong!"
- @app.post("/ppocr")
- @timeit
- @web_try()
- def cet(request: Request, ppocr: PPOcrInfo):
- return p.predict(base64_to_np(ppocr.image))
- 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)
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