Update app.py

app.py

@@ -204,6 +204,29 @@ def get_akc_breeds_link():
 #     except Exception as e:
 #         return f"An error occurred: {e}"
 
+# 返回特定狗品種的描述函數
+def get_breed_info(breed):
+    description = get_dog_description(breed)
+    akc_link = get_akc_breeds_link()
+
+    if isinstance(description, dict):
+        description_str = "\n\n".join([f"**{key}**: {value}" for key, value in description.items()])
+    else:
+        description_str = description
+
+    # 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.*")
+    description_str += disclaimer
+
+    return description_str
+
+# 原始的預測函數，增加了按鈕來觸發品種描述的顯示
 def predict(image):
     try:
         image_tensor = preprocess_image(image)
@@ -214,80 +237,37 @@ def predict(image):
             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()
 
-            # 假設低於 20% 機率為非狗或不確定的圖片
             if top1_prob < 0.2:
-                return (
-                    "The model couldn't confidently identify a dog breed. "
-                    "It seems like the image may not contain a dog, or the image quality is too low. "
-                    "Please upload a clearer picture or ensure the subject is a dog."
-                )
+                return "The image does not appear to be a dog. Please upload a clearer or different dog image."
 
-            # 當信心高於 50% 時，直接返回該品種資訊
             if top1_prob >= 0.5:
                 predicted = topk_indices[0][0]
                 breed = dog_breeds[predicted.item()]
                 return get_breed_info(breed)
 
             else:
-                # 信心不足50%，返回top 3的預測結果，並且當點擊時能查看詳細資訊
+                # 如果模型無法確定，列出 top 3 品種按鈕
                 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]]
 
-                # 提供每個品種的回調函數
-                topk_results = "\n\n".join(
-                    [f"**{i+1}. [Click here to view more about {breed}](#) ({prob} confidence)**"
-                     for i, (breed, prob) in enumerate(zip(topk_breeds, topk_probs_percent))]
-                )
+                # 用按鈕來返回品種描述
+                buttons = [gr.Button(f"Click here to view more about {breed} ({prob})", variant="primary")
+                           for breed, prob in zip(topk_breeds, topk_probs_percent)]
 
-                # 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"
-                    "This can happen if the image quality is low or the breed is rare in the dataset. "
-                    "Please try uploading a clearer image or a different angle of the dog. "
-                    "For more accurate results, ensure the dog is the main subject of the photo."
-                )
-
-                return explanation
+                return f"The model couldn't confidently identify the breed. Here are the top 3 possible breeds:", buttons
 
     except Exception as e:
         return f"An error occurred: {e}"
 
-def get_breed_info(breed):
-    """
-    返回指定狗品種的詳細資訊，類似於 >=50% 信心時的結果。
-    """
-    description = get_dog_description(breed)
-    akc_link = get_akc_breeds_link()
-
-    if isinstance(description, dict):
-        description_str = "\n\n".join([f"**{key}**: {value}" for key, value in description.items()])
-    else:
-        description_str = description
-
-    # 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.*")
-    description_str += disclaimer
-
-    return description_str
-
 
 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.Component(type="button")],
     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>",