change output type

app.py

@@ -229,30 +229,39 @@ def preprocess_image(image, output_size=(300, 300)):
 def update_display(image):
     processed_image = preprocess_image(image) 
     instruction = "Image ready. Please switch to the 'Specimen Workbench' tab to check out further analysis and outputs."
-    model_name = gr.Dropdown(
-                    ["Mummified 170", "Rock 170","Fossils 142","Fossils new"],
-                    multiselect=False,
-                    value="Fossils new", # default option
-                    label="Model",
-                    interactive=True,
-                    info="Choose the model you'd like to use"
-                )
-    explain_method = gr.Dropdown(
-        ["Sobol", "HSIC","Rise","Saliency"],
-        multiselect=False,
-        value="Rise", # default option
-        label="Explain method",
-        interactive=True,
-        info="Choose one method to explain the model"
-    )
-    sampling_size = gr.Slider(1, 5000, value=2000, label="Sampling Size in Rise",interactive=True,visible=True,
-                                          info="Choose between 1 and 5000")
+    model_name = "Fossils new"
+    
+    # gr.Dropdown(
+    #                 ["Mummified 170", "Rock 170","Fossils 142","Fossils new"],
+    #                 multiselect=False,
+    #                 value="Fossils new", # default option
+    #                 label="Model",
+    #                 interactive=True,
+    #                 info="Choose the model you'd like to use"
+    #             )
+    explain_method = "Rise"
+    
+    # gr.Dropdown(
+    #     ["Sobol", "HSIC","Rise","Saliency"],
+    #     multiselect=False,
+    #     value="Rise", # default option
+    #     label="Explain method",
+    #     interactive=True,
+    #     info="Choose one method to explain the model"
+    # )
+    sampling_size = 2000
+    # gr.Slider(1, 5000, value=2000, label="Sampling Size in Rise",interactive=True,visible=True,
+    #                                       info="Choose between 1 and 5000")
                 
-    top_k = gr.Slider(10,200,value=50,label="Number of Closest Samples for Distribution Chart",interactive=True,info="Choose between 10 and 200")
+    top_k = 50
+    # gr.Slider(10,200,value=50,label="Number of Closest Samples for Distribution Chart",interactive=True,info="Choose between 10 and 200")
     class_predicted = "Class Predicted" # gr.Label(label='Class Predicted',num_top_classes=10)
-    exp_gallery = gr.Gallery(label="Explanation Heatmaps for top 5 predicted classes", show_label=False,elem_id="gallery",columns=[5], rows=[1],height='auto', allow_preview=True, preview=None)
-    closest_gallery = gr.Gallery(label="Closest Images", show_label=False,elem_id="gallery",columns=[5], rows=[1],height='auto', allow_preview=True, preview=None)
-    diagram= gr.Image(label = 'Bar Chart')
+    exp_gallery = []
+    # gr.Gallery(label="Explanation Heatmaps for top 5 predicted classes", show_label=False,elem_id="gallery",columns=[5], rows=[1],height='auto', allow_preview=True, preview=None)
+    closest_gallery = []
+    # gr.Gallery(label="Closest Images", show_label=False,elem_id="gallery",columns=[5], rows=[1],height='auto', allow_preview=True, preview=None)
+    diagram= ""
+    # gr.Image(label = 'Bar Chart')
     return processed_image,processed_image,instruction,model_name,explain_method,sampling_size,top_k,exp_gallery,closest_gallery,diagram
 def update_slider_visibility(explain_method):
     bool = explain_method=="Rise"