Update app.py

app.py

@@ -204,78 +204,157 @@ def get_akc_breeds_link():
 #     except Exception as e:
 #         return f"An error occurred: {e}"
 
+# iface = gr.Interface(
+#     fn=predict,
+#     inputs=gr.Image(label="Upload a dog image", type="numpy"),
+#     outputs=gr.Markdown(label="Prediction Results"),
+#     title="<h1 style='font-family:Roboto; font-weight:bold; color:#2C3E50; text-align:center;'>🐶 Dog Breed Classifier 🔍</h1>",
+#     article= 'For more details on this project and other work, feel free to visit my GitHub [Dog Breed Classifier](https://github.com/Eric-Chung-0511/Learning-Record/tree/main/Data%20Science%20Projects/Dog%20Breed%20Classifier)',
+#     description="<p style='font-family:Open Sans; color:#34495E; text-align:center;'>Upload a picture of a dog, and model will predict its breed, provide detailed information, and include an extra information link!</p>",
+#     examples=['Border_Collie.jpg',
+#               'Golden_Retriever.jpeg',
+#               'Saint_Bernard.jpeg',
+#               'French_Bulldog.jpeg',
+#               'Samoyed.jpg'],
+#      css = """
+#     .container {
+#         max-width: 900px;
+#         margin: 0 auto;
+#         padding: 20px;
+#         background-color: rgba(255, 255, 255, 0.9);
+#         border-radius: 15px;
+#         box-shadow: 0 0 20px rgba(0, 0, 0, 0.1);
+#     }
+    
+#     .gr-form {
+#         display: flex;
+#         flex-direction: column;
+#         align-items: center;
+#     }
+    
+#     .gr-box {
+#         width: 100%;
+#         max-width: 500px;
+#     }
+    
+#     .output-markdown, .output-image {
+#         margin-top: 20px;
+#         padding: 15px;
+#         background-color: #f5f5f5;
+#         border-radius: 10px;
+#     }
+    
+#     .examples {
+#         display: flex;
+#         justify-content: center;
+#         flex-wrap: wrap;
+#         gap: 10px;
+#         margin-top: 20px;
+#     }
+    
+#     .examples img {
+#         width: 100px;
+#         height: 100px;
+#         object-fit: cover;
+#     }
+#     """,
+#     theme='default')
+
+
+
+# # Launch the app
+# if __name__ == "__main__":
+#     iface.launch()
+
 def predict(image):
     try:
         image_tensor = preprocess_image(image)
         with torch.no_grad():
             output = model(image_tensor)
-            logits = output[0] if isinstance(output, tuple) else output
+            if isinstance(output, tuple):
+                logits = output[0]
+            else:
+                logits = output
 
+            # 取得預測的top k結果
             probabilities = F.softmax(logits, dim=1)
             topk_probs, topk_indices = torch.topk(probabilities, k=3)
 
+            # 檢查最高的預測機率
             top1_prob = topk_probs[0][0].item()
-            topk_breeds = [dog_breeds[idx.item()] for idx in topk_indices[0]]
-            topk_probs_percent = [f"{prob.item() * 100:.2f}%" for prob in topk_probs[0]]
 
             if top1_prob >= 0.5:
-                # High confidence prediction
-                breed = topk_breeds[0]
+                # 正確辨識時，返回該品種資訊
+                predicted = topk_indices[0][0]
+                breed = dog_breeds[predicted.item()]
                 description = get_dog_description(breed)
+                akc_link = get_akc_breeds_link()
+
                 if isinstance(description, dict):
-                    formatted_description = "\n\n".join([f"**{key}**: {value}" for key, value in description.items()])
+                    description_str = "\n\n".join([f"**{key}**: {value}" for key, value in description.items()])
                 else:
-                    formatted_description = description
+                    description_str = description
 
-                akc_link = get_akc_breeds_link()
-                formatted_description += f"\n\n**Want to learn more about dog breeds?** [Visit the AKC dog breeds page]({akc_link}) and search for {breed} to find detailed information."
+                # 添加AKC連結
+                description_str += f"\n\n**Want to learn more about dog breeds?** [Visit the AKC dog breeds page]({akc_link}) and search for {breed} to find detailed information."
 
+                # 添加免責聲明
                 disclaimer = ("\n\n*Disclaimer: The external link provided leads to the American Kennel Club (AKC) dog breeds page. "
                               "You may need to search for the specific breed on that page. "
                               "I am not responsible for the content on external sites. "
                               "Please refer to the AKC's terms of use and privacy policy.*")
-                formatted_description += disclaimer
+                description_str += disclaimer
 
-                return formatted_description
+                return description_str, gr.Button.update(visible=False), gr.Button.update(visible=False), gr.Button.update(visible=False)
 
             elif top1_prob < 0.1:
-                # Very low confidence prediction
-                return ("The model couldn't confidently identify the breed. The image might not be clear enough or might not contain a dog. "
-                        "Please try uploading a clearer image of a dog.")
+                # 如果信心度低於 0.1，返回提示請上傳更清晰的圖片
+                return "The image is too unclear or the dog breed is not in the dataset. Please upload a clearer image of the dog.", gr.Button.update(visible=False), gr.Button.update(visible=False), gr.Button.update(visible=False)
+
             else:
-                # Medium confidence prediction
-                topk_results = "\n\n".join([f"**{i+1}. {breed}** (Confidence: {prob})" for i, (breed, prob) in enumerate(zip(topk_breeds, topk_probs_percent))])
+                # 不確定時，返回top 3的預測結果，並且允許點擊查看詳細資訊
+                topk_breeds = [dog_breeds[idx.item()] for idx in topk_indices[0]]
+                topk_probs_percent = [f"{prob.item() * 100:.2f}%" for prob in topk_probs[0]]
+
+                # 提供說明
                 explanation = (
-                    f"The model couldn't confidently identify the breed. Here are the top 3 possible breeds:\n\n{topk_results}\n\n"
-                    "Please select one of the breeds above to see more information:"
+                    f"The model couldn't confidently identify the breed. Here are the top 3 possible breeds:\n"
+                    f"1. {topk_breeds[0]} ({topk_probs_percent[0]} confidence)\n"
+                    f"2. {topk_breeds[1]} ({topk_probs_percent[1]} confidence)\n"
+                    f"3. {topk_breeds[2]} ({topk_probs_percent[2]} confidence)\n\n"
+                    "Click on a button to view more information about the breed."
                 )
-                return explanation, gr.update(choices=topk_breeds, visible=True)
 
+                return explanation, gr.Button.update(visible=True, value=f"More about {topk_breeds[0]}"), gr.Button.update(visible=True, value=f"More about {topk_breeds[1]}"), gr.Button.update(visible=True, value=f"More about {topk_breeds[2]}")
     except Exception as e:
-        return f"An error occurred: {e}"
+        return f"An error occurred: {e}", gr.Button.update(visible=False), gr.Button.update(visible=False), gr.Button.update(visible=False)
 
-def show_breed_info(breed):
+def show_details(breed):
     description = get_dog_description(breed)
+    akc_link = get_akc_breeds_link()
+    
     if isinstance(description, dict):
-        formatted_description = "\n\n".join([f"**{key}**: {value}" for key, value in description.items()])
+        description_str = "\n\n".join([f"**{key}**: {value}" for key, value in description.items()])
     else:
-        formatted_description = description
+        description_str = description
 
-    akc_link = get_akc_breeds_link()
-    formatted_description += f"\n\n**Want to learn more about dog breeds?** [Visit the AKC dog breeds page]({akc_link}) and search for {breed} to find detailed information."
+    # 添加AKC連結
+    description_str += f"\n\n**Want to learn more about dog breeds?** [Visit the AKC dog breeds page]({akc_link}) and search for {breed} to find detailed information."
 
+    # 添加免責聲明
     disclaimer = ("\n\n*Disclaimer: The external link provided leads to the American Kennel Club (AKC) dog breeds page. "
                   "You may need to search for the specific breed on that page. "
                   "I am not responsible for the content on external sites. "
                   "Please refer to the AKC's terms of use and privacy policy.*")
-    formatted_description += disclaimer
+    description_str += disclaimer
 
-    return formatted_description
+    return description_str
 
+# Gradio Interface
 iface = gr.Interface(
     fn=predict,
     inputs=gr.Image(label="Upload a dog image", type="numpy"),
-    outputs=gr.Markdown(label="Prediction Results"),
+    outputs=[gr.Markdown(label="Prediction Results"), gr.Button(value="View More 1", visible=False), gr.Button(value="View More 2", visible=False), gr.Button(value="View More 3", visible=False)],
     title="<h1 style='font-family:Roboto; font-weight:bold; color:#2C3E50; text-align:center;'>🐶 Dog Breed Classifier 🔍</h1>",
     article= 'For more details on this project and other work, feel free to visit my GitHub [Dog Breed Classifier](https://github.com/Eric-Chung-0511/Learning-Record/tree/main/Data%20Science%20Projects/Dog%20Breed%20Classifier)',
     description="<p style='font-family:Open Sans; color:#34495E; text-align:center;'>Upload a picture of a dog, and model will predict its breed, provide detailed information, and include an extra information link!</p>",
@@ -326,10 +405,15 @@ iface = gr.Interface(
         object-fit: cover;
     }
     """,
-    theme='default')
+    theme='default'
+)
 
+# 定義按鈕的點擊事件
+iface.add_event_listener('View More 1', fn=lambda: show_details(topk_breeds[0]))
+iface.add_event_listener('View More 2', fn=lambda: show_details(topk_breeds[1]))
+iface.add_event_listener('View More 3', fn=lambda: show_details(topk_breeds[2]))
 
-
-# Launch the app
+# 啟動 Gradio 應用
 if __name__ == "__main__":
     iface.launch()
+