Update app.py

app.py

@@ -243,217 +243,9 @@ async def process_single_dog(image):
         return explanation, image, buttons[0], buttons[1], buttons[2], gr.update(visible=True), initial_state
 
 
-# async def predict(image):
-#     if image is None:
-#         return "Please upload an image to start.", None, gr.update(visible=False, choices=[]), None
-
-#     try:
-#         if isinstance(image, np.ndarray):
-#             image = Image.fromarray(image)
-
-#         dogs = await detect_multiple_dogs(image)
-        
-#         color_list = ['#FF0000', '#00FF00', '#0000FF', '#FFFF00', '#00FFFF', '#FF00FF', '#800080', '#FFA500']
-#         buttons = []
-#         annotated_image = image.copy()
-#         draw = ImageDraw.Draw(annotated_image)
-#         font = ImageFont.load_default()
-
-#         dogs_info = ""
-
-#         for i, (cropped_image, detection_confidence, box) in enumerate(dogs):
-#             buttons_html = ""  
-#             top1_prob, topk_breeds, topk_probs_percent = await predict_single_dog(cropped_image)
-#             color = color_list[i % len(color_list)]
-#             draw.rectangle(box, outline=color,, width=3)
-#             draw.text((box[0] + 5, box[1] + 5) f"Dog {i+1}", fill=color, font=font)
-        
-#             combined_confidence = detection_confidence * top1_prob
-#             dogs_info += f'<div class="dog-info" style="border-left: 5px solid {color}; margin-bottom: 20px; padding: 15px;">'
-#             dogs_info += f'<h2>Dog {i+1}</h2>'
-        
-#             if top1_prob >= 0.45:
-#                 breed = topk_breeds[0]
-#                 description = get_dog_description(breed)
-#                 dogs_info += format_description_html(description, breed)
-        
-#             elif combined_confidence >= 0.15:
-#                 dogs_info += f"<p>Top 3 possible breeds:</p><ul>"
-#                 for j, (breed, prob) in enumerate(zip(topk_breeds[:3], topk_probs_percent[:3])):
-#                     prob = float(prob.replace('%', ''))
-#                     dogs_info += f"<li><strong>{breed}</strong> ({prob:.2f}% confidence)</li>"
-#                 dogs_info += "</ul>"
-        
-#                 for breed in topk_breeds[:3]:
-#                     button_id = f"Dog {i+1}: More about {breed}"
-#                     buttons_html += f'<button class="breed-button" onclick="handle_button_click(\'{button_id}\')">{breed}</button>'
-#                     buttons.append(button_id)
-        
-#             else:
-#                 dogs_info += "<p>The image is unclear or the breed is not in the dataset. Please upload a clearer image.</p>"
-        
-#             dogs_info += '</div>'    
-
-        
-#         buttons_html = ""  
-      
-#         html_output = f"""
-#         <style>
-#         .dog-info {{ border: 1px solid #ddd; margin-bottom: 20px; padding: 15px; border-radius: 5px; box-shadow: 0 2px 5px rgba(0,0,0,0.1); }}
-#         .dog-info h2 {{ background-color: #f0f0f0; padding: 10px; margin: -15px -15px 15px -15px; border-radius: 5px 5px 0 0; }}
-#         .breed-buttons {{ margin-top: 10px; }}
-#         .breed-button {{ margin-right: 10px; margin-bottom: 10px; padding: 5px 10px; background-color: #4CAF50; color: white; border: none; border-radius: 3px; cursor: pointer; }}
-#         </style>
-#         {dogs_info}
-#         """     
-
-#         if buttons:
-#             html_output += """
-#             <script>
-#             function handle_button_click(button_id) {
-#                 const radio = document.querySelector('input[type=radio][value="' + button_id + '"]');
-#                 if (radio) {
-#                     radio.click();
-#                 } else {
-#                     console.error("Radio button not found:", button_id);
-#                 }
-#             }
-#             </script>
-#             """
-#             initial_state = {
-#                 "dogs_info": dogs_info,
-#                 "buttons": buttons,
-#                 "show_back": True,
-#                 "image": annotated_image,
-#                 "is_multi_dog": len(dogs) > 1,
-#                 "html_output": html_output  
-#             }
-#             return html_output, annotated_image, gr.update(visible=True, choices=buttons), initial_state
-#         else:
-#             initial_state = {
-#                 "dogs_info": dogs_info,
-#                 "buttons": [],
-#                 "show_back": False,
-#                 "image": annotated_image,
-#                 "is_multi_dog": len(dogs) > 1,
-#                 "html_output": html_output  
-#             }
-#             return html_output, annotated_image, gr.update(visible=False, choices=[]), initial_state
-
-
-#     except Exception as e:
-#         error_msg = f"An error occurred: {str(e)}\n\nTraceback:\n{traceback.format_exc()}"
-#         print(error_msg)
-#         return error_msg, None, gr.update(visible=False, choices=[]), None
-
-
-# def show_details_html(choice, previous_output, initial_state):
-#     if not choice:
-#         return previous_output, gr.update(visible=True), initial_state
-
-#     try:
-#         breed = choice.split("More about ")[-1]
-#         description = get_dog_description(breed)
-#         formatted_description = format_description_html(description, breed)
-        
-#         html_output = f"""
-#         <div class="dog-info">
-#             <h2>{breed}</h2>
-#             {formatted_description}
-#         </div>
-#         """
-        
-#         initial_state["current_description"] = html_output
-#         initial_state["original_buttons"] = initial_state.get("buttons", [])
-        
-#         return html_output, gr.update(visible=True), initial_state
-#     except Exception as e:
-#         error_msg = f"An error occurred while showing details: {e}"
-#         print(error_msg)
-#         return f"<p style='color: red;'>{error_msg}</p>", gr.update(visible=True), initial_state
-
-
-# def format_description_html(description, breed):
-#     html = "<ul style='list-style-type: none; padding-left: 0;'>"
-#     if isinstance(description, dict):
-#         for key, value in description.items():
-#             html += f"<li style='margin-bottom: 10px;'><strong>{key}:</strong> {value}</li>"
-#     elif isinstance(description, str):
-#         html += f"<li>{description}</li>"
-#     else:
-#         html += f"<li>No description available for {breed}</li>"
-#     html += "</ul>"
-#     akc_link = get_akc_breeds_link()
-#     html += f'<p><a href="{akc_link}" target="_blank">Learn more about {breed} on the AKC website</a></p>'
-#     return html
-
-
-# def go_back(state):
-#     buttons = state.get("buttons", [])
-#     return (
-#         state["html_output"],
-#         state["image"],
-#         gr.update(visible=True, choices=buttons),
-#         gr.update(visible=False),
-#         state
-#     )
-
-
-# with gr.Blocks() as iface:
-#     gr.HTML("<h1 style='text-align: center;'>🐶 Dog Breed Classifier 🔍</h1>")
-#     gr.HTML("<p style='text-align: center;'>Upload a picture of a dog, and the model will predict its breed, provide detailed information, and include an extra information link!</p>")
-    
-#     with gr.Row():
-#         input_image = gr.Image(label="Upload a dog image", type="pil")
-#         output_image = gr.Image(label="Annotated Image")
-    
-#     output = gr.HTML(label="Prediction Results")  
-    
-#     breed_buttons = gr.Radio(choices=[], label="More Information", visible=False)
-    
-#     back_button = gr.Button("Back", visible=False)
-    
-#     initial_state = gr.State()
-    
-#     input_image.change(
-#         predict,
-#         inputs=input_image,
-#         outputs=[output, output_image, breed_buttons, initial_state]
-#     )
-
-#     breed_buttons.change(
-#         show_details_html,
-#         inputs=[breed_buttons, output, initial_state],
-#         outputs=[output, back_button, initial_state]
-#     )
-
-#     back_button.click(
-#         go_back,
-#         inputs=[initial_state],
-#         outputs=[output, output_image, breed_buttons, back_button, initial_state]
-#     )
-    
-#     gr.Examples(
-#         examples=['Border_Collie.jpg', 'Golden_Retriever.jpeg', 'Saint_Bernard.jpeg', 'French_Bulldog.jpeg', 'Samoyed.jpg'],
-#         inputs=input_image
-#     )
-
-#     gr.HTML('For more details on this project and other work, feel free to visit my GitHub <a href="https://github.com/Eric-Chung-0511/Learning-Record/tree/main/Data%20Science%20Projects/Dog_Breed_Classifier">Dog Breed Classifier</a>')
-
-
-
-# if __name__ == "__main__":
-#     iface.launch()
-
-
-
-
-
-
-
 async def predict(image):
     if image is None:
-        return "Please upload an image to start.", None, gr.update(visible=False), gr.update(visible=False)
+        return "Please upload an image to start.", None, gr.update(visible=False, choices=[]), None
 
     try:
         if isinstance(image, np.ndarray):
@@ -462,18 +254,19 @@ async def predict(image):
         dogs = await detect_multiple_dogs(image)
         
         color_list = ['#FF0000', '#00FF00', '#0000FF', '#FFFF00', '#00FFFF', '#FF00FF', '#800080', '#FFA500']
+        buttons = []
         annotated_image = image.copy()
         draw = ImageDraw.Draw(annotated_image)
         font = ImageFont.load_default()
 
         dogs_info = ""
-        buttons = []
 
         for i, (cropped_image, detection_confidence, box) in enumerate(dogs):
+            buttons_html = ""  
             top1_prob, topk_breeds, topk_probs_percent = await predict_single_dog(cropped_image)
             color = color_list[i % len(color_list)]
-            draw.rectangle(box, outline=color, width=3)
-            draw.text((box[0] + 5, box[1] + 5), f"Dog {i+1}", fill=color, font=font)
+            draw.rectangle(box, outline=color,, width=3)
+            draw.text((box[0] + 5, box[1] + 5) f"Dog {i+1}", fill=color, font=font)
         
             combined_confidence = detection_confidence * top1_prob
             dogs_info += f'<div class="dog-info" style="border-left: 5px solid {color}; margin-bottom: 20px; padding: 15px;">'
@@ -483,38 +276,80 @@ async def predict(image):
                 breed = topk_breeds[0]
                 description = get_dog_description(breed)
                 dogs_info += format_description_html(description, breed)
+        
             elif combined_confidence >= 0.15:
                 dogs_info += f"<p>Top 3 possible breeds:</p><ul>"
                 for j, (breed, prob) in enumerate(zip(topk_breeds[:3], topk_probs_percent[:3])):
                     prob = float(prob.replace('%', ''))
-                    button_id = f"Dog {i+1}: More about {breed}"
-                    buttons.append(button_id)
                     dogs_info += f"<li><strong>{breed}</strong> ({prob:.2f}% confidence)</li>"
                 dogs_info += "</ul>"
+        
+                for breed in topk_breeds[:3]:
+                    button_id = f"Dog {i+1}: More about {breed}"
+                    buttons_html += f'<button class="breed-button" onclick="handle_button_click(\'{button_id}\')">{breed}</button>'
+                    buttons.append(button_id)
+        
             else:
                 dogs_info += "<p>The image is unclear or the breed is not in the dataset. Please upload a clearer image.</p>"
         
-            dogs_info += '</div>'
+            dogs_info += '</div>'    
 
+        
+        buttons_html = ""  
+      
         html_output = f"""
         <style>
         .dog-info {{ border: 1px solid #ddd; margin-bottom: 20px; padding: 15px; border-radius: 5px; box-shadow: 0 2px 5px rgba(0,0,0,0.1); }}
         .dog-info h2 {{ background-color: #f0f0f0; padding: 10px; margin: -15px -15px 15px -15px; border-radius: 5px 5px 0 0; }}
+        .breed-buttons {{ margin-top: 10px; }}
+        .breed-button {{ margin-right: 10px; margin-bottom: 10px; padding: 5px 10px; background-color: #4CAF50; color: white; border: none; border-radius: 3px; cursor: pointer; }}
         </style>
-        
         {dogs_info}
-        """
+        """     
+
+        if buttons:
+            html_output += """
+            <script>
+            function handle_button_click(button_id) {
+                const radio = document.querySelector('input[type=radio][value="' + button_id + '"]');
+                if (radio) {
+                    radio.click();
+                } else {
+                    console.error("Radio button not found:", button_id);
+                }
+            }
+            </script>
+            """
+            initial_state = {
+                "dogs_info": dogs_info,
+                "buttons": buttons,
+                "show_back": True,
+                "image": annotated_image,
+                "is_multi_dog": len(dogs) > 1,
+                "html_output": html_output  
+            }
+            return html_output, annotated_image, gr.update(visible=True, choices=buttons), initial_state
+        else:
+            initial_state = {
+                "dogs_info": dogs_info,
+                "buttons": [],
+                "show_back": False,
+                "image": annotated_image,
+                "is_multi_dog": len(dogs) > 1,
+                "html_output": html_output  
+            }
+            return html_output, annotated_image, gr.update(visible=False, choices=[]), initial_state
 
-        return html_output, annotated_image, gr.update(visible=True, choices=buttons), gr.update(visible=False)
 
     except Exception as e:
         error_msg = f"An error occurred: {str(e)}\n\nTraceback:\n{traceback.format_exc()}"
         print(error_msg)
-        return error_msg, None, gr.update(visible=False), gr.update(visible=False)
+        return error_msg, None, gr.update(visible=False, choices=[]), None
 
-def show_breed_info(choice):
+
+def show_details_html(choice, previous_output, initial_state):
     if not choice:
-        return "", gr.update(visible=False)
+        return previous_output, gr.update(visible=True), initial_state
 
     try:
         breed = choice.split("More about ")[-1]
@@ -528,13 +363,42 @@ def show_breed_info(choice):
         </div>
         """
         
-        return html_output, gr.update(visible=True)
+        initial_state["current_description"] = html_output
+        initial_state["original_buttons"] = initial_state.get("buttons", [])
+        
+        return html_output, gr.update(visible=True), initial_state
     except Exception as e:
         error_msg = f"An error occurred while showing details: {e}"
         print(error_msg)
-        return f"<p style='color: red;'>{error_msg}</p>", gr.update(visible=True)
+        return f"<p style='color: red;'>{error_msg}</p>", gr.update(visible=True), initial_state
+
+
+def format_description_html(description, breed):
+    html = "<ul style='list-style-type: none; padding-left: 0;'>"
+    if isinstance(description, dict):
+        for key, value in description.items():
+            html += f"<li style='margin-bottom: 10px;'><strong>{key}:</strong> {value}</li>"
+    elif isinstance(description, str):
+        html += f"<li>{description}</li>"
+    else:
+        html += f"<li>No description available for {breed}</li>"
+    html += "</ul>"
+    akc_link = get_akc_breeds_link()
+    html += f'<p><a href="{akc_link}" target="_blank">Learn more about {breed} on the AKC website</a></p>'
+    return html
+
+
+def go_back(state):
+    buttons = state.get("buttons", [])
+    return (
+        state["html_output"],
+        state["image"],
+        gr.update(visible=True, choices=buttons),
+        gr.update(visible=False),
+        state
+    )
+
 
-# Main Gradio interface
 with gr.Blocks() as iface:
     gr.HTML("<h1 style='text-align: center;'>🐶 Dog Breed Classifier 🔍</h1>")
     gr.HTML("<p style='text-align: center;'>Upload a picture of a dog, and the model will predict its breed, provide detailed information, and include an extra information link!</p>")
@@ -543,29 +407,30 @@ with gr.Blocks() as iface:
         input_image = gr.Image(label="Upload a dog image", type="pil")
         output_image = gr.Image(label="Annotated Image")
     
-    output = gr.HTML(label="Prediction Results")
-    breed_info = gr.HTML(label="Breed Information")
+    output = gr.HTML(label="Prediction Results")  
     
     breed_buttons = gr.Radio(choices=[], label="More Information", visible=False)
     
-    back_button = gr.Button("Back to Results", visible=False)
+    back_button = gr.Button("Back", visible=False)
+    
+    initial_state = gr.State()
     
     input_image.change(
         predict,
-        inputs=[input_image],
-        outputs=[output, output_image, breed_buttons, back_button]
+        inputs=input_image,
+        outputs=[output, output_image, breed_buttons, initial_state]
     )
 
     breed_buttons.change(
-        show_breed_info,
-        inputs=[breed_buttons],
-        outputs=[breed_info, back_button]
+        show_details_html,
+        inputs=[breed_buttons, output, initial_state],
+        outputs=[output, back_button, initial_state]
     )
 
     back_button.click(
-        lambda: (gr.update(visible=True), gr.update(visible=True), gr.update(visible=True), 
-                 gr.update(visible=False), gr.update(visible=False)),
-        outputs=[output, output_image, breed_buttons, breed_info, back_button]
+        go_back,
+        inputs=[initial_state],
+        outputs=[output, output_image, breed_buttons, back_button, initial_state]
     )
     
     gr.Examples(
@@ -575,5 +440,7 @@ with gr.Blocks() as iface:
 
     gr.HTML('For more details on this project and other work, feel free to visit my GitHub <a href="https://github.com/Eric-Chung-0511/Learning-Record/tree/main/Data%20Science%20Projects/Dog_Breed_Classifier">Dog Breed Classifier</a>')
 
+
+
 if __name__ == "__main__":
     iface.launch()