Upload untitled3.py

untitled3.py

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+# -*- coding: utf-8 -*-
+"""Untitled3.ipynb
+
+Automatically generated by Colab.
+
+Original file is located at
+    https://colab.research.google.com/drive/1OS-UaGZUegFfwJmaELsau9--kGmq_8wz
+"""
+
+!pip install streamlit
+import streamlit as st
+from tensorflow.keras.models import load_model
+from PIL import Image
+import numpy as np
+import cv2
+
+# Eğitilmiş modeli yükle
+model = load_model('skin_cancer_model.h5')
+
+def process_image(image):
+  img=np.array(image)
+  img=cv2.resize(img,(224,224))
+  img=img/255.0
+  img=np.expand_dims(img,axis=0)
+  return img
+
+st.title('Traffic Sign Image Classifier')
+st.write('Upload a image and model will predict which traffic sign it is.')
+
+file = st.file_uploader('Choose a 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 = ['Not Cancer', 'Cancer']
+    st.write(class_names[predicted_class])
+