editing req files

Procfile

@@ -1 +1 @@
-web: python app.py
+web: python app.py

To-Do

@@ -0,0 +1,3 @@
+Add auto-deleter for images
+optimize model
+add useful tips

app.py

@@ -1,28 +1,23 @@
 from flask import Flask, request, render_template, jsonify
-from flask_cors import CORS
-
 from utils import *
 
 
 app = Flask(__name__)
-CORS(app)
-
 __model = None
 
 
 @app.route("/")
 def home():
     return render_template("index.html")
 
-
 @app.route("/predict", methods=['POST'])
 def predict():
    try:
-    data = request.files["myFile"]
-    data.save(f"data/{data.filename}")
-    result = predict_the_pic(f"data/{data.filename}", model=__model)
-    result = make_final_result(result=result)
-    return jsonify({"Result": result})
+     data = request.files["myFile"]
+     data.save(f"data/{data.filename}")
+     result = predict_the_pic(f"data/{data.filename}", model=__model)
+     result = make_final_result(result=result)
+     return jsonify({"Result": result})
    except:
       return jsonify({"Result" : "An Error Occurred"})
 
@@ -31,4 +26,4 @@ def predict():
 
     __model = return_model()
 
-    app.run(host='0.0.0.0', port=5000)
+    app.run()

requirements.txt

@@ -1,8 +1,7 @@
+gunicorn
 Flask
-flask_cors
-pandas
-keras
 numpy
 opencv-python
 pillow
-tensorflow
+keras
+opencv-python-headless

utils.py

@@ -1,10 +1,7 @@
-from keras.models import load_model
 import cv2
 from PIL import Image
 import numpy
-
-
-
+from keras.models import load_model
 
 def return_model():
      model = load_model("BrainTumorDetection.h5")
@@ -16,7 +13,6 @@ def  make_final_result(result):
    else:
       return "OK"
 
-
 def predict_the_pic(picture,model):
 
    image = cv2.imread(picture)