mirror of
https://github.com/StefBuwalda/ProjectIOT.git
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Stef
5e4b1acca0
Sped up ANPR by only creating one ANPR instance, rather than initializing a new one every function call.
66 lines
1.5 KiB
Python
66 lines
1.5 KiB
Python
from flask import request, jsonify
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from pyplatex import ANPR # type: ignore
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from ultralytics.nn.tasks import DetectionModel # type: ignore
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import os
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import torch
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import asyncio
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from application import app, db
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from models import LoggedItem, AllowedPlate
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from datetime import datetime
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torch.serialization.add_safe_globals( # type: ignore
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{"DetectionModel": DetectionModel} # type: ignore
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)
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anpr = ANPR()
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# Saving images locally
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UPLOAD_FOLDER = "uploads"
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os.makedirs(UPLOAD_FOLDER, exist_ok=True)
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# Default app route
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@app.route("/")
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def home():
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return "Hello, World!"
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# API to process vehicle
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@app.route("/api", methods=["POST"])
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def data():
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data = request.data
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with open("image.jpg", "wb") as f:
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f.write(data)
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status = asyncio.run(process_image(file="image.jpg", anpr=anpr))
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return jsonify(
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{
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"message": "Image sent succesfully",
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"status": status,
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}
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)
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async def process_image(file: str, anpr: ANPR) -> bool:
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print("Processing image")
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anpr_info = await anpr.detect(file) # type: ignore
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number_plate = anpr_info["plate_number"]
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if number_plate:
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allowed = (
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AllowedPlate.query.filter_by(plate=number_plate).first()
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is not None
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)
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db.session.add(
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LoggedItem(
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plate=number_plate, allowed=allowed, datetime=datetime.now()
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)
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)
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db.session.commit()
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return allowed
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return False
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if __name__ == "__main__":
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app.run(host="192.168.137.1", port=2222, debug=True)
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