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Update Dockerfile
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Update src/streamlit_app.py
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Upload skin_cancer_model.h5
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Update requirements.txt
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Upload skin_cancer_model.h5
Verified signatureimport streamlit as st from tensorflow.keras.models import load_model from PIL import Image import numpy as np model=load_model('skin_cancer_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('Deri Kanser resmi sınıflandırma :cancer:') st.write('Resim seç, model kanser olup olmadığını tahmin etsin!') file=st.file_uploader('Bir resim yükle',type=['jpg','jpeg','png']) if file is not None: # Resim yuklenmisse burasi calisacak img=Image.open(file) st.image(img, caption='Yuklenen Resim') image=process_image(img) prediction=model.predict(image) predicted_class = 1 if prediction > 0.5 else 0 class_names=['Kanser değil','Kanser'] st.write(class_names[predicted_class])17f797f -
initial commit
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Duplicate from streamlit/streamlit-template-space
Co-authored-by: Franck Abgrall <FranckAbgrall@users.noreply.huggingface.co>a713616
