Update app.py

app.py

@@ -18,7 +18,6 @@ def load_image(image_path, max_dim):
 
 
 def deprocess_inception_image(img):
-    img = np.array(img).astype(np.uint8)
     img = 255 * (img + 1) / 2
     return np.array(img, np.uint8)
 
@@ -90,8 +89,8 @@ centered_text = """
         """
 
 # Streamlit App
-st.title("Deep Dream")
-st.write("Upload an image to generate mesmerising Deep Dream images. Adjust the parameters in the sidebar to get "
+st.title("Deep Dream Streamlit App")
+st.write("Upload an image to generate mesmerizing Deep Dream images. Adjust the parameters in the sidebar to get "
          "different effects.")
 st.write("Image generation may take a while depending on the parameters chosen, kindly be patient.")
 
@@ -113,7 +112,7 @@ weight = st.sidebar.slider("Weight", 0.01, 0.1, 0.02, step=0.01, help="Weight fo
 
 if uploaded_file is not None:
     # Load and preprocess the uploaded image
-    input_image = load_image(uploaded_file, max_dim=150)
+    input_image = load_image(uploaded_file, max_dim=250)
     preprocessed_image = inception_v3.preprocess_input(input_image)
 
     # Create Inception model and modify for deep dream
@@ -123,17 +122,15 @@ if uploaded_file is not None:
     selected_layers = [f'mixed{i}' for i, checkbox in enumerate(layer_checkboxes, start=1) if checkbox]
     dream_model = deep_dream_model(inception, selected_layers)
 
-    # Run gradient ascent with progress bar
     progress_bar = st.progress(0.0)  # Initialize progress bar
-    
     # Run gradient ascent
-    image_array = run_gradient_ascent(dream_model, preprocessed_image, progress_bar, epochs=epochs, steps_per_epoch=steps_per_epoch, weight=weight)
+    (image_array, progress_bar) = run_gradient_ascent(dream_model, preprocessed_image, progress_bar, epochs=epochs, steps_per_epoch=steps_per_epoch, weight=weight)
 
     # Convert numpy arrays to PIL images
     dream_pil_image = array_to_img(deprocess_inception_image(image_array))
 
     # Display the Deep Dream image
-    st.image(dream_pil_image, caption='Deep Dream Image', width=300)
+    st.image(dream_pil_image, caption='Deep Dream Image', width=400)
 
 st.markdown("<hr>", unsafe_allow_html=True)
 st.markdown(centered_text, unsafe_allow_html=True)