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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
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