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("fistik.h5")
+
+def process_image(img):
+    img=img.resize((96,96))
+    img=np.array(img)
+    img=img/255.0
+    img=np.expand_dims(img,axis=0)
+    return img
+
+st.title("Fistik siniflandirma modeli")
+st.write("Resim sec model hangi Fistik oldugunu tahmin etsin")
+
+file=st.file_uploader("Bir resim sec",type=["jpeg","jpg","png"])
+
+if file is not None:
+    img=Image.open(file)
+    st.image(img,caption="yuklenen resim")
+    image=process_image(img)
+    prediction=model.predict(image)
+    predicted_class=np.argmax(prediction)
+
+class_names={ 0: 'Kirmizi_Pistachio',
+              1: 'Siirt_Pistachio'
+            }
+
+st.write(class_names[predicted_class])

fistik.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:20c4888d4d8bac93c45a81e5bd769e30cf4000f127ee38cfa177989984f2451c
+size 48874864

requirements.txt

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+streamlit
+tensorflow