application.py

from flask import Flask
from flask import render_template
from flask import request
import os
import cv2
from predict import modcrop,shave,predict
from prepare_images import psnr,mse,compare_images,prepare_images
from PIL import Image
app=Flask(__name__)
#UPLOAD_FOLDER = '/home/aanisha/Desktop/SuperResolution-master/static/input/'

#OUTPUT_FOLDER = '/home/aanisha/Desktop/SuperResolution-master/static/output/'

UPLOAD_FOLDER = '/app/static/input/'

OUTPUT_FOLDER = '/app/static/output/'

pred=0.0
@app.route("/",methods=['GET','POST'])
def upload_predict():
    if request.method == 'POST':
        image_file = request.files["image"]
        if image_file:
            #print(type(image_file))
            
            image_location = os.path.join(UPLOAD_FOLDER,image_file.filename)
            image_file.save(image_location)
            img=prepare_images(image_location,2)
            ref, degraded, output, scores=predict(img,image_file.filename)
            output_image = cv2.cvtColor(output, cv2.COLOR_BGR2RGB)
            output_image = Image.fromarray(output_image)
            output_location = os.path.join(OUTPUT_FOLDER,image_file.filename)

            output_image.save(output_location)
            return render_template('index.html',image_name=image_file.filename,psnr=scores[1][0],mse=scores[1][1],ssim=scores[1][2])
            
    return render_template('index.html',image_name=None,psnr=0,mse=0,ssim=0)

if __name__ == "__main__": 
    app.run(host ='0.0.0.0', port = 5001, debug = True)