add advanced compare models

app.py

@@ -874,8 +874,12 @@ def load_alignedthreemodel():
     model = ThreeAttnNodes(align_weights)
     
     return model
-# pre-load the alignedthree model in case it fails to load
-load_alignedthreemodel()
+
+try:
+    # pre-load the alignedthree model in case it fails to load
+    load_alignedthreemodel()
+except Exception as e:
+    pass
 
 promptable_diffusion_models = ["Diffusion(stabilityai/stable-diffusion-2)", "Diffusion(CompVis/stable-diffusion-v1-4)"]
 promptable_segmentation_models = ["LISA(xinlai/LISA-7B-v1)"]
@@ -2029,6 +2033,81 @@ with demo:
         buttons[-1].click(fn=lambda x: gr.update(visible=True), outputs=rows[-1])
         buttons[-1].click(fn=lambda x: gr.update(visible=False), outputs=buttons[-1])
     
+    with gr.Tab('Compare Models (Advanced)', visible=False) as tab_compare_models_advanced: 
+        def add_one_model(i_model=1):
+            with gr.Column(scale=5, min_width=200) as col:
+                gr.Markdown(f'### Output Images')
+                output_gallery = gr.Gallery(format='png', value=[], label="NCUT Embedding", show_label=True, elem_id=f"ncut{i_model}", columns=[3], rows=[1], object_fit="contain", height="auto", show_fullscreen_button=True, interactive=False)
+                submit_button = gr.Button("🔴 RUN", elem_id=f"submit_button{i_model}", variant='primary')
+                add_output_images_buttons(output_gallery)
+                norm_gallery = gr.Gallery(value=[], label="Eigenvector Magnitude", show_label=True, elem_id=f"eig_norm{i_model}", columns=[3], rows=[1], object_fit="contain", height="auto", show_share_button=True, preview=False, interactive=False)
+                cluster_gallery = gr.Gallery(value=[], label="Clusters", show_label=True, elem_id=f"clusters{i_model}", columns=[2], rows=[4], object_fit="contain", height=600, show_share_button=True, preview=True, interactive=False)
+                [
+                    model_dropdown, layer_slider, node_type_dropdown, num_eig_slider, 
+                    affinity_focal_gamma_slider, num_sample_ncut_slider, ncut_knn_slider, ncut_indirect_connection, ncut_make_orthogonal, 
+                    embedding_method_dropdown, embedding_metric_dropdown, num_sample_tsne_slider, knn_tsne_slider, 
+                    perplexity_slider, n_neighbors_slider, min_dist_slider, 
+                    sampling_method_dropdown, ncut_metric_dropdown, positive_prompt, negative_prompt
+                ] = make_parameters_section()
+                # logging text box
+                logging_text = gr.Textbox("Logging information", label="Logging", elem_id="logging", type="text", placeholder="Logging information")
+                false_placeholder = gr.Checkbox(label="False", value=False, elem_id="false_placeholder", visible=False)
+                no_prompt = gr.Textbox("", label="", elem_id="empty_placeholder", type="text", placeholder="", visible=False)
+                
+                submit_button.click(
+                    partial(run_fn, n_ret=3, plot_clusters=True, alignedcut_eig_norm_plot=True, advanced=True),
+                    inputs=[
+                        input_gallery, model_dropdown, layer_slider, num_eig_slider, node_type_dropdown, 
+                        positive_prompt, negative_prompt,
+                        false_placeholder, no_prompt, no_prompt, no_prompt,
+                        affinity_focal_gamma_slider, num_sample_ncut_slider, ncut_knn_slider, ncut_indirect_connection, ncut_make_orthogonal, 
+                        embedding_method_dropdown, embedding_metric_dropdown, num_sample_tsne_slider, knn_tsne_slider, 
+                        perplexity_slider, n_neighbors_slider, min_dist_slider, sampling_method_dropdown, ncut_metric_dropdown
+                    ],
+                    outputs=[output_gallery, cluster_gallery, norm_gallery, logging_text]
+                )
+                
+                return col
+
+        with gr.Row():
+            with gr.Column(scale=5, min_width=200):
+                input_gallery, submit_button, clear_images_button = make_input_images_section()
+                clear_images_button.click(lambda x: [], outputs=[input_gallery])
+                submit_button.visible = False
+                dataset_dropdown, num_images_slider, random_seed_slider, load_images_button = make_dataset_images_section(advanced=True)
+
+                
+            for i in range(2):
+                add_one_model()
+                
+        # Create rows and buttons in a loop
+        rows = []
+        buttons = []
+
+        for i in range(4):
+            row = gr.Row(visible=False)
+            rows.append(row)
+            
+            with row:
+                for j in range(3):
+                    with gr.Column(scale=5, min_width=200):
+                        add_one_model()
+
+            button = gr.Button("➕ Add Compare", elem_id=f"add_button_{i}", visible=False if i > 0 else True, scale=3)
+            buttons.append(button)
+            
+            if i > 0:
+                # Reveal the current row and next button
+                buttons[i - 1].click(fn=lambda x: gr.update(visible=True), outputs=row)
+                buttons[i - 1].click(fn=lambda x: gr.update(visible=True), outputs=button)
+                
+                # Hide the current button
+                buttons[i - 1].click(fn=lambda x: gr.update(visible=False), outputs=buttons[i - 1])
+
+        # Last button only reveals the last row and hides itself
+        buttons[-1].click(fn=lambda x: gr.update(visible=True), outputs=rows[-1])
+        buttons[-1].click(fn=lambda x: gr.update(visible=False), outputs=buttons[-1])
+    
     
     with gr.Tab('📄About'):
         with gr.Column():
@@ -2087,6 +2166,7 @@ with demo:
         hidden_button.change(unlock_tabs_with_info, n_smiles, tab_alignedcut_advanced)
         hidden_button.change(unlock_tabs, n_smiles, tab_model_aligned_advanced)
         hidden_button.change(unlock_tabs, n_smiles, tab_recursivecut_advanced)
+        hidden_button.change(unlock_tabs, n_smiles, tab_compare_models_advanced)
                 
     with gr.Row():
         with gr.Column():