api-demo.py

import aiohttp
import asyncio
import uvicorn
from fastai import *
from fastai.vision import *
from fastai.vision.all import *
from io import BytesIO
from starlette.applications import Starlette
from starlette.middleware.cors import CORSMiddleware
from starlette.responses import HTMLResponse, JSONResponse
from starlette.staticfiles import StaticFiles
from PIL import Image
import urllib.request

app = Starlette()
app.add_middleware(CORSMiddleware, allow_origins=['*'], allow_headers=['X-Requested-With', 'Content-Type'])

learn = load_learner('export.pkl')

@app.route('/analyze', methods=['POST'])
async def analyze(request):
    img_data = await request.form()
    img = Image.open(requests.get(img_data['file'], stream=True, timeout = 10).raw) 
    pil_img = PILImage.create(img)
    prediction = learn.predict(pil_img)[0]
    return JSONResponse({'result': str(prediction)})


if __name__ == '__main__':
    if 'serve' in sys.argv:
        uvicorn.run(app=app, host='0.0.0.0', port=5500, log_level="info")