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
+import cv2
+
+model = load_model('C:/Users/mucahit/Desktop/day13/my_cnn_model.h5')
+
+def process_image(img):
+    img = cv2.resize(img, (170, 170))
+    img = img / 255.0
+    img = np.expand_dims(img, axis=0)
+    return img
+
+st.title('Kanser Resmi Siniflandirma :cancer:')
+st.write('Resim seç ve model kanser olup olmadigini tahmin etsin')
+
+file = st.file_uploader('Bir Resim Seç', type=['jpeg', 'jpg', 'png'])
+
+if file is not None:
+    img = Image.open(file)
+    st.image(img, caption='Yuklenen resim')
+    img = np.array(img)  
+    if img.shape[2] == 4:  
+        img = cv2.cvtColor(img, cv2.COLOR_BGRA2BGR)  
+    
+    image = process_image(img)
+    prediction = model.predict(image)
+    prediction_class = np.argmax(prediction) 
+
+    class_names = ['Kanser Değil', 'Kanser']
+    st.write(class_names[prediction_class])

my_cnn_model.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:854a96dc8d0b6b7e43b4c75e036a34a15d8998eb24663405af844c8aa2bfd467
+size 165516528

requirements.txt

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+tensorflow
+streamlit