Update app.py

app.py

@@ -10,22 +10,30 @@ import tensorflow as tf
 
 model = keras.models.load_model("model.keras")
 
-uploaded_img = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
+# uploaded_img = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
 
+# options = ['1st Convolution', '2nd Convolution', '3rd Convolution']
+# selected_option = st.selectbox('Choose an option:', options)
+
+st.sidebar.title("Controls")
+uploaded_img = st.sidebar.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
 options = ['1st Convolution', '2nd Convolution', '3rd Convolution']
-selected_option = st.selectbox('Choose an option:', options)
+selected_option = st.sidebar.selectbox('Select convolution layer:', options)
+
 
 conv_layers = [layer for layer in model.layers if isinstance(layer, Conv2D)]
+layer_ind = options.index(selected_option)
+selected_layer = conv_layers[layer_ind]
 
 fig = plt.figure(figsize=(12, 4))
 
-layer_ind = options.index(selected_option)
+#layer_ind = options.index(selected_option)
 # selected_layer = conv_layers[layer_ind]
 scaler = MinMaxScaler()
 
 # for i in range(3):
 for j in range(6):
-    layer=conv_layers[layer_ind]
+    layer=selected_layer
     weights=layer.get_weights()[0][:,:,0,j]
     norm_weights = scaler.fit_transform(weights)
     plt.subplot(2,3,j+1)
@@ -49,7 +57,7 @@ if uploaded_img is not None:
     st.image(img_norm, caption="Uploaded Image (Resized to 28x28)", use_container_width =True, channels="GRAY")
 
     #layer_ind = options.index(selected_option)
-    selected_layer = conv_layers[layer_ind]
+    # selected_layer = conv_layers[layer_ind]
 
     #func_model = Model(inputs = model.layers[0].input, outputs = model.selected_layer.output)
     func_model = Model(inputs = model.layers[0].input, outputs = selected_layer.output)