Delete app.py

app.py

@@ -1,32 +0,0 @@
-#!/usr/bin/env python
-# coding: utf-8
-#dosyayı py olarak kaydet ve komut satırını kullanarak streamlit run streamlit.py 
-import streamlit as st
-from tensorflow.keras.models import load_model
-from PIL import Image
-import numpy as np
-import cv2
-model=load_model("animal_model.h5")
-def process_image(img):
-    img=img.resize((224,224))
-    img=np.array(img)
-    img=img[:,:, :3]  # Remove the alpha channel
-    img=img/255.0
-    img=np.expand_dims(img,axis=0)
-    return img
-st.title('Animal Classification')
-st.write('Please choose an image so that the AI model can predict the type of animal.')
-file=st.file_uploader('Pick an image', type= ['jpg','jpeg','png'])
-
-with open("name of the animals.txt") as f:
-    class_names = [x.strip() for x in f.readlines()]
-
-if file is not None:
-    img=Image.open(file)
-    st.image(img,caption='The image: ')
-    image=process_image(img)
-    prediction=model.predict(image)
-    predicted_class=np.argmax(prediction)
-    st.write('Probability Distribution')
-    st.write(prediction)
-    st.write("Prediction: ",class_names[predicted_class])