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import streamlit as st | |
import tensorflow as tf | |
st.title("Skin Disease Classification App") | |
# Load model | |
model = tf.keras.models.load_model('TvachaAI.h5') | |
# Create sidebar for uploading images | |
st.sidebar.title("Upload Image") | |
image = st.sidebar.file_uploader("Upload an image", type=['png', 'jpg']) | |
if image is not None: | |
# Process & predict | |
img = process_image(image) | |
preds = model.predict(img) | |
# Display image & predictions | |
st.image(img, use_column_width=True) | |
st.write(f"Prediction: {decode_predictions(preds)}") |