| import streamlit as st |
| 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 |
| img=np.expand_dims(img,axis=0) |
| return img |
|
|
| st.title("Kanser Resmi Siniflandirma :cancer:") |
| st.write("Resim sec ve model kanser olup olmadigini tahmin etsin") |
|
|
| file=st.file_uploader('Bir Resim Sec',type=['jpg','jpeg','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=['Kanser Degil','Kanser'] |
| st.write(class_names[predicted_class]) |
|
|
