Delete app.py

app.py

-from flask import Flask,render_template,request
-from werkzeug.utils import secure_filename
-import cv2
-from PIL import Image
-import pytesseract
-import os
-import re
-import joblib
-
-pytesseract.pytesseract.tesseract_cmd='C://Program Files/Tesseract-OCR/tesseract.exe'
-
-
-app=Flask(__name__)
-print("J")
-
-@app.route('/')
-def index():
-
-	return render_template('sideeffect.html')
-
-@app.route('/prediction',methods=['POST', 'GET'])
-def prediction():
-
-	diseases={0:"neurofibromatosis",1:"carcinoma syndrome",2:"von Hippel-Lindau",3:"Glioblastoma multiforme",4:"tuberous sclerosis"}
-	
-	input_data = request.form 
-	
-	firstname=input_data['firstname']
-	lastname=input_data['Lastname']
-	age=input_data['Age']
-	gender=input_data['gender']
-	email=input_data['E-mail']
-
-	f = request.files['Upload Report']
-	f.save(secure_filename(f.filename))
-
-	image=cv2.imread(f.filename)
-
-	gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
-	thresh = cv2.threshold(gray,128, 255,cv2.THRESH_BINARY)[1]
-	#thresh = cv2.threshold(gray, 0, 255,cv2.THRESH_BINARY | cv2.THRESH_OTSU)[1]
-
-	text = pytesseract.image_to_string(thresh)
-
-	
-	numbers=re.findall(r"[-+]?\d*\.\d+|\d+",text)
-	print(numbers,gender)
-	himo=float(numbers[36])
-	rbc=float(numbers[37])
-	wbc=float(numbers[45]+numbers[46])
-	neu=float(numbers[47])
-	lym=float(numbers[49])
-
-	if(gender=='male'):
-
-		model=joblib.load('male.sav')
-	else:
-		model=joblib.load('female.sav')
-	print([[himo,rbc,wbc,neu,lym]])
-	result=model.predict([[himo,rbc,wbc,neu,lym]])[0]
-
-	disease=diseases[result]
-
-	return render_template('result.html',disease=disease)
-
-	#{{disease}}
-app.run(debug=True)
\ No newline at end of file