Upload 3 files

app.py

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+import streamlit as st
+import tensorflow as tf
+from tensorflow.keras.models import load_model
+from PIL  import Image
+import numpy as np
+
+model = load_model("./my_cnn_model.h5")
+
+def process_image(img):
+    img = img.resize((170,170))
+    img = np.array(img)
+    img = img / 255.0 # normalize etme resmi 0 1 yapma
+    img = np.expand_dims(img, axis=0)
+    return img
+
+st.title("Kanser Resmi Sınıflandırma :cancer:")
+st.write("Resim seç ve model kanser olup olmadığını tahmin etsin")
+
+file= st.file_uploader("Bir Resim Seç", type=["jpg", "jpeg", "png"])
+
+if file is not None:
+    img = Image.open(file)
+    st.image(img, caption="yüklenen resim")
+    image = process_image(img)
+    prediction = model.predict(image)
+    predicted_class = np.argmax(prediction)
+
+    class_names = ["Kanser Değil", "Kanser"]
+    st.write(class_names[predicted_class])
+

my_cnn_model.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:368a0951488c6af67bc976cb1f0fc623d3378929227a8582fba0047285842c41
+size 165525616

requirements.txt

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+streamlit
+tensorflow