app.py

import sys

sys.path.append("./src")

from kidney_classification.pipeline.prediction import PredictionPipeline
from kidney_classification.utils.common import decodeImage
from flask_cors import CORS, cross_origin
import os
from flask import Flask, request, jsonify, render_template


os.putenv("LANG", "en_US.UTF-8")
os.putenv("LC_ALL", "en_US.UTF-8")

app = Flask(__name__)
CORS(app)


class ClientApp:
    def __init__(self):
        self.filename = "inputImage.jpg"
        self.classifier = PredictionPipeline(self.filename)


@app.route("/", methods=["GET"])
@cross_origin()
def home():
    return render_template("index.html")


@app.route("/train", methods=["GET", "POST"])
@cross_origin()
def trainRoute():
    os.system("dvc repro")
    return "Training done successfully!"


@app.route("/predict", methods=["POST"])
@cross_origin()
def predictRoute():
    image = request.json["image"]
    decodeImage(image, clApp.filename)
    result = clApp.classifier.predict()
    return jsonify(result)


if __name__ == "__main__":
    clApp = ClientApp()

    app.run(host="0.0.0.0", port=8080)  # for AWS