cars.py

import sys
from io import BytesIO
from pathlib import Path

import aiohttp
import numpy as np
import scipy.io
import uvicorn
from fastai.vision import (
    load_learner,
    open_image,
)
from starlette.applications import Starlette
from starlette.responses import JSONResponse, HTMLResponse, RedirectResponse


async def get_bytes(url):
    async with aiohttp.ClientSession() as session:
        async with session.get(url) as response:
            return await response.read()


app = Starlette()

car_images_path = Path("/")
car_learner = load_learner(car_images_path, file='export-rn101_train_stage2-50e.pkl')


@app.route("/upload", methods=["POST"])
async def upload(request):
    data = await request.form()
    bytes = await (data["file"].read())
    return predict_image_from_bytes(bytes)


@app.route("/classify-url", methods=["GET"])
async def classify_url(request):
    bytes = await get_bytes(request.query_params["url"])
    return predict_image_from_bytes(bytes)


def predict_image_from_bytes(bytes):
    img = open_image(BytesIO(bytes))
    pred_class, pred_idx, confidence = car_learner.predict(img)
    cars_meta = scipy.io.loadmat('devkit/cars_meta')
    class_names = cars_meta['class_names']  # shape=(1, 196)
    class_names = np.transpose(class_names)
    return JSONResponse({
        "prediction_class": class_names[pred_idx.item()][0][0],
        "confidence": confidence[pred_idx.item()].item()
    })


@app.route("/")
def form(request):
    return HTMLResponse(
        """
        <form action="/upload" method="post" enctype="multipart/form-data">
            Select image to upload:
            <input type="file" name="file">
            <input type="submit" value="Upload Image">
        </form>
        Or submit a URL:
        <form action="/classify-url" method="get">
            <input type="url" name="url">
            <input type="submit" value="Fetch and analyze image">
        </form>
    """)


@app.route("/form")
def redirect_to_homepage(request):
    return RedirectResponse("/")


if __name__ == "__main__":
    if "serve" in sys.argv:
        uvicorn.run(app, host="0.0.0.0", port=8008)