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| import streamlit as st | |
| import tensorflow as tf | |
| import numpy as np | |
| # Load the model | |
| model = tf.keras.models.load_model('HumanFaceGenerator.h5') | |
| # Create a button | |
| button_clicked = st.button("Generate") | |
| # Check if the button is clicked | |
| if button_clicked: | |
| # Generate an image | |
| seed = tf.random.normal((1, 100)) | |
| pred = model.predict(seed) | |
| pred = pred * 0.5 + 0.5 # Normalize the pixel values | |
| pred = np.squeeze(pred) # Remove singleton dimensions if any | |
| # Display the generated image | |
| st.image(pred, caption='Generated Image', use_column_width=True) |