update input image to original

README.md

@@ -4,7 +4,7 @@ emoji: 🦀
 colorFrom: indigo
 colorTo: purple
 sdk: gradio
-sdk_version: 3.38.0
+sdk_version: 4.36.0
 app_file: app.py
 pinned: false
 models:

app.py

@@ -227,6 +227,7 @@ def preprocess_image(image, output_size=(300, 300)):
     return image_resized
 
 def update_display(image):
+    original_image = 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 = "Fossils new"
@@ -249,7 +250,7 @@ def update_display(image):
     #     interactive=True,
     #     info="Choose one method to explain the model"
     # )
-    sampling_size = 2000
+    sampling_size = 5
     # gr.Slider(1, 5000, value=2000, label="Sampling Size in Rise",interactive=True,visible=True,
     #                                       info="Choose between 1 and 5000")
                 
@@ -262,7 +263,7 @@ def update_display(image):
     # gr.Gallery(label="Closest Images", show_label=False,elem_id="gallery",columns=[5], rows=[1],height='auto', allow_preview=True, preview=None)
     diagram= None
     # gr.Image(label = 'Bar Chart')
-    return processed_image,processed_image,instruction,model_name,explain_method,sampling_size,top_k,class_predicted,exp_gallery,closest_gallery,diagram
+    return original_image,processed_image,processed_image,instruction,model_name,explain_method,sampling_size,top_k,class_predicted,exp_gallery,closest_gallery,diagram
 def update_slider_visibility(explain_method):
     bool = explain_method=="Rise"
     return {sampling_size: gr.Slider(1, 5000, value=2000, label="Sampling Size in Rise", visible=bool, interactive=True)}
@@ -288,6 +289,7 @@ with gr.Blocks(theme='sudeepshouche/minimalist') as demo:
     with gr.Tab("Specimen Workbench"):
         with gr.Row():
             with gr.Column():
+                original_image = gr.Image(visible = True)
                 workbench_image = gr.Image(label="Workbench Image")
                 classify_image_button = gr.Button("Classify Image")
             
@@ -319,8 +321,8 @@ with gr.Blocks(theme='sudeepshouche/minimalist') as demo:
                 #                                   value="Rise",
                 #                                   multiselect=False,
                 #                                   interactive=True,)
-                sampling_size = gr.Slider(1, 5000, value=2000, label="Sampling Size in Rise",interactive=True,visible=True,
-                                          info="Choose between 1 and 5000")
+                sampling_size = gr.Slider(1, 30, value=5, label="Sampling Size in Rise",interactive=True,visible=True,
+                                          info="Choose between 1 and 30")
                 
                 top_k = gr.Slider(10,200,value=50,label="Number of Closest Samples for Distribution Chart",interactive=True,info="Choose between 10 and 200")
                 explain_method.change(
@@ -381,7 +383,7 @@ with gr.Blocks(theme='sudeepshouche/minimalist') as demo:
                     find_closest_btn = gr.Button("Find Closest Images")
                     
                 #segment_button.click(segment_image, inputs=input_image, outputs=segmented_image)
-                classify_image_button.click(classify_image, inputs=[input_image,model_name], outputs=class_predicted)
+                classify_image_button.click(classify_image, inputs=[original_image,model_name], outputs=class_predicted)
                 # generate_exp.click(exp_image, inputs=[input_image,model_name,explain_method,sampling_size], outputs=[exp1,exp2,exp3,exp4,exp5]) #
                 with gr.Accordion('Closest Leaves Images'):
                     gr.Markdown("5 closest leaves")
@@ -414,7 +416,7 @@ with gr.Blocks(theme='sudeepshouche/minimalist') as demo:
                 image_caption.append((images[i],"Predicted Class "+str(i)+": "+labels[i]))
             return image_caption
 
-        generate_explanations.click(fn=update_exp_outputs, inputs=[input_image,model_name,explain_method,sampling_size], outputs=[exp_gallery])
+        generate_explanations.click(fn=update_exp_outputs, inputs=[original_image,model_name,explain_method,sampling_size], outputs=[exp_gallery])
 
         #find_closest_btn.click(find_closest, inputs=[input_image,model_name], outputs=[label_closest_image_0,label_closest_image_1,label_closest_image_2,label_closest_image_3,label_closest_image_4,closest_image_0,closest_image_1,closest_image_2,closest_image_3,closest_image_4])
         def update_closest_outputs(input_image,model_name):
@@ -426,15 +428,15 @@ with gr.Blocks(theme='sudeepshouche/minimalist') as demo:
                 image_caption.append((images[i],labels[i]))
             return image_caption
 
-        find_closest_btn.click(fn=update_closest_outputs, inputs=[input_image,model_name], outputs=[closest_gallery])
+        find_closest_btn.click(fn=update_closest_outputs, inputs=[original_image,model_name], outputs=[closest_gallery])
         #classify_segmented_button.click(classify_image, inputs=[segmented_image,model_name], outputs=class_predicted)
 
-        generate_diagram.click(generate_diagram_closest, inputs=[input_image,model_name,top_k], outputs=diagram)
+        generate_diagram.click(generate_diagram_closest, inputs=[original_image,model_name,top_k], outputs=diagram)
 
     process_button.click(
                         fn=update_display,
                         inputs=input_image,
-                        outputs=[input_image,workbench_image,instruction_text,model_name,explain_method,sampling_size,top_k,class_predicted,exp_gallery,closest_gallery,diagram]
+                        outputs=[original_image,input_image,workbench_image,instruction_text,model_name,explain_method,sampling_size,top_k,class_predicted,exp_gallery,closest_gallery,diagram]
                     )