Upload 3 files

app.py

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+import streamlit as st
+from tensorflow.keras.models import load_model
+from PIL import Image
+import numpy as np
+
+model=load_model('potato_leaf_disease.h5', compile=False)
+
+def process_image(img):
+    img=img.resize((170,170))  #boyutunu 170*170 pixel yaptık
+    img=np.array(img)
+    img=img/255.0  #Normalize ettik
+    img=np.expand_dims(img,axis=0)
+    return img
+
+st.title('Potato Leaf Disease Classification:potato:')
+st.write('Pick an image and It will predict the disease')
+
+file=st.file_uploader('Upload an image', type=['jpg','jpeg','png'])
+
+if file is not None:
+    img=Image.open(file)
+    st.image(img,caption='Uploaded image')
+    image=process_image(img)
+    prediction=model.predict(image)
+    predicted_class=np.argmax(prediction)
+
+    class_names=['Early_Blight','Healthy','Late_Blight']
+    st.write(class_names[predicted_class])

potato_leaf_disease.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f1967bd4b9aa031170d6440d8bfad7564a24a3da1b6e37bbe4f71a163772b0e7
+size 165527408

requirements.txt

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+streamlit 
+tensorflow