OCR server

gistfile1.txt

import io, time
from typing import Optional
import easyocr, numpy as np
from PIL import Image
from fastapi import FastAPI, File, UploadFile, HTTPException
from fastapi.middleware.cors import CORSMiddleware
import uvicorn
app = FastAPI(title="GPU OCR Server")
app.add_middleware(CORSMiddleware, allow_origins=["*"], allow_credentials=True, allow_methods=["*"], allow_headers=["*"])
ocr_reader: Optional[easyocr.Reader] = None
@app.on_event("startup")
async def load_model():
    global ocr_reader
    print("[OCR] Loading model with GPU...")
    start = time.time()
    ocr_reader = easyocr.Reader(['en'], gpu=True, verbose=False)
    print(f"[OCR] Ready in {time.time()-start:.1f}s")
@app.get("/health")
async def health(): return {"status": "ok", "gpu": ocr_reader is not None}
@app.post("/ocr")
async def ocr(file: UploadFile = File(...)):
    if not ocr_reader: raise HTTPException(503, "Model not loaded")
    t0 = time.time()
    img = np.array(Image.open(io.BytesIO(await file.read())))
    t1 = time.time()
    results = ocr_reader.readtext(img)
    t2 = time.time()
    return {
        "results": [{"text": t, "confidence": float(c), "bbox": [[int(p[0]),int(p[1])] for p in b], "center": [(int(b[0][0])+int(b[2][0]))//2, (int(b[0][1])+int(b[2][1]))//2]} for b,t,c in results],
        "timing": {"read_ms": int((t1-t0)*1000), "ocr_ms": int((t2-t1)*1000), "total_ms": int((t2-t0)*1000)},
        "count": len(results)
    }
if __name__ == "__main__":
    uvicorn.run(app, host="0.0.0.0", port=8765)