from flask import Flask, request, jsonify
import os
from pyplatex import ANPR
import torch
from ultralytics.nn.tasks import DetectionModel
import asyncio

torch.serialization.add_safe_globals({"DetectionModel": DetectionModel})

# Web Server
app = Flask(__name__)

# Saving images locally
UPLOAD_FOLDER = "uploads"
os.makedirs(UPLOAD_FOLDER, exist_ok=True)


# Default app route
@app.route("/")
def home():
    return "Hello, World!"


# API to process vehicle
@app.route("/api", methods=["POST"])
def data():
    # Check if image is present
    if "image" not in request.files:
        return jsonify({"error": "No file part"}), 400

    file = request.files["image"]  # get the image from the packet

    if file.filename == "" or not file.filename:
        return jsonify({"error": "No selected file"}), 400

    # Check if image ends in .jpg
    if file.filename.lower().endswith(".jpg"):
        filepath = os.path.join(UPLOAD_FOLDER, file.filename)
        file.save(filepath)
        print(asyncio.run(process_image(filepath)))
        return jsonify(
            {
                "message": "File uploaded successfully",
                "filename": file.filename,
                "status": True,
            }
        )

    return jsonify({"error": "Only JPEG files allowed"}), 400


async def process_image(file: str):
    anpr = ANPR()
    plates = await anpr.detect(file)
    return plates


if __name__ == "__main__":
    app.run(host="192.168.137.1", port=2222, debug=True)