Fix Gradio app.py: resolve TypeError and localhost accessibility issues

- Fixed TypeError: argument of type 'bool' is not iterable
- Added share=True to resolve localhost accessibility
- Improved error handling and model loading
- Enhanced UI with better parameter specifications
- Added path auto-detection for flexible deployment

app.py

@@ -2,23 +2,43 @@ import os
 import cv2
 import numpy as np
 import gradio as gr
-from realtime_sign_prediction import RealtimeSignPredictor
 
-# 初始化預測器
-print("🚀 正在初始化手語辨識系統...")
-predictor = RealtimeSignPredictor(
-    model_path="tsflow/models/best_model.pt",
-    config_path="tsflow/results/test_results.json",
-    sequence_length=50,
-    use_segmentation=True
-)
-print("✅ 手語辨識系統初始化完成！")
+# 檢查檔案是否存在
+model_path = "tsflow/models/best_model.pt"
+config_path = "tsflow/results/test_results.json"
+
+# 如果是在SignView2.0目錄下運行，調整路徑
+if not os.path.exists(model_path):
+    model_path = "../tsflow/models/best_model.pt"
+    config_path = "../tsflow/results/test_results.json"
+
+try:
+    from realtime_sign_prediction import RealtimeSignPredictor
+    
+    # 初始化預測器
+    print("🚀 正在初始化手語辨識系統...")
+    predictor = RealtimeSignPredictor(
+        model_path=model_path,
+        config_path=config_path,
+        sequence_length=50,
+        use_segmentation=True
+    )
+    print("✅ 手語辨識系統初始化完成！")
+    MODEL_LOADED = True
+    
+except Exception as e:
+    print(f"⚠️ 模型載入失敗: {e}")
+    print("🔄 使用模擬模式運行...")
+    MODEL_LOADED = False
 
 def process_image(image):
     """處理上傳的影像"""
     if image is None:
         return None, "請上傳影像或使用攝像頭拍攝"
     
+    if not MODEL_LOADED:
+        return image, "⚠️ 模型未載入，無法進行預測\n請檢查模型檔案路徑"
+    
     try:
         # 處理畫面
         results, keypoints, flow_features = predictor.process_frame(image)
@@ -47,79 +67,111 @@ def process_image(image):
 
 def clear_sequence():
     """清除預測序列"""
-    predictor.keypoint_sequence.clear()
-    predictor.flow_sequence.clear()
-    return "✅ 已清除預測序列"
+    if MODEL_LOADED:
+        predictor.keypoint_sequence.clear()
+        predictor.flow_sequence.clear()
+        return "✅ 已清除預測序列"
+    else:
+        return "⚠️ 模型未載入"
 
 # 創建簡化的 Gradio 介面
-with gr.Blocks(title="SignView2.0 - 手語辨識系統") as demo:
-    
-    gr.Markdown("""
-    # 🤟 SignView2.0 - 手語辨識系統
-    
-    **支援34種手語詞彙的即時辨識系統，準確率達94.25%**
-    
-    ## 📋 支援詞彙
-    again, all, apple, bad, bathroom, beautiful, bird, black, blue, book, 
-    bored, boy, brother, brown, but, computer, cousin, dance, day, deaf, 
-    doctor, dog, draw, drink, eat, english, family, father, fine, finish, 
-    fish, forget, friend, girl
-    
-    ## 🚀 使用說明
-    1. 上傳影像或使用攝像頭拍攝手語動作
-    2. 點擊「分析手語」按鈕
-    3. 查看辨識結果
-    """)
-    
-    with gr.Row():
-        with gr.Column():
-            # 簡化的影像輸入
-            input_image = gr.Image(
-                label="影像輸入",
-                height=300
-            )
-            
-            with gr.Row():
-                process_btn = gr.Button("🔍 分析手語", variant="primary")
-                clear_btn = gr.Button("🗑️ 清除序列", variant="secondary")
+def create_interface():
+    with gr.Blocks(
+        title="SignView2.0 - 手語辨識系統",
+        theme=gr.themes.Soft(),
+        css="""
+        .gradio-container {
+            max-width: 1200px !important;
+        }
+        """
+    ) as demo:
+        
+        gr.Markdown("""
+        # 🤟 SignView2.0 - 手語辨識系統
         
-        with gr.Column():
-            # 結果輸出
-            output_image = gr.Image(
-                label="辨識結果",
-                height=300
-            )
+        **支援34種手語詞彙的即時辨識系統，準確率達94.25%**
+        
+        ## 📋 支援詞彙
+        again, all, apple, bad, bathroom, beautiful, bird, black, blue, book, 
+        bored, boy, brother, brown, but, computer, cousin, dance, day, deaf, 
+        doctor, dog, draw, drink, eat, english, family, father, fine, finish, 
+        fish, forget, friend, girl
+        
+        ## 🚀 使用說明
+        1. 上傳影像或使用攝像頭拍攝手語動作
+        2. 點擊「分析手語」按鈕
+        3. 查看辨識結果
+        """)
+        
+        with gr.Row():
+            with gr.Column():
+                # 簡化的影像輸入 - 移除可能導致schema錯誤的複雜參數
+                input_image = gr.Image(
+                    label="影像輸入",
+                    type="numpy",
+                    height=300
+                )
+                
+                with gr.Row():
+                    process_btn = gr.Button("🔍 分析手語", variant="primary")
+                    clear_btn = gr.Button("🗑️ 清除序列", variant="secondary")
             
-            prediction_text = gr.Textbox(
-                label="預測結果",
-                lines=8,
-                value="等待影像輸入..."
-            )
-    
-    # 系統資訊
-    gr.Markdown("""
-    ## 📊 系統資訊
-    - **模型準確率**: 94.25%
-    - **F1分數**: 94.24%
-    - **特徵提取**: MediaPipe + 光流
-    - **模型架構**: BiLSTM + 注意力機制
-    - **背景分割**: MediaPipe Segmentation
+            with gr.Column():
+                # 結果輸出
+                output_image = gr.Image(
+                    label="辨識結果",
+                    type="numpy",
+                    height=300
+                )
+                
+                prediction_text = gr.Textbox(
+                    label="預測結果",
+                    lines=8,
+                    value="等待影像輸入...",
+                    interactive=False
+                )
+        
+        # 系統資訊
+        gr.Markdown("""
+        ## 📊 系統資訊
+        - **模型準確率**: 94.25%
+        - **F1分數**: 94.24%
+        - **特徵提取**: MediaPipe + 光流
+        - **模型架構**: BiLSTM + 注意力機制
+        - **背景分割**: MediaPipe Segmentation
+        
+        **開發者**: XiaoBai1221 | **平台**: Hugging Face Spaces
+        """)
+        
+        # 事件處理
+        process_btn.click(
+            fn=process_image,
+            inputs=[input_image],
+            outputs=[output_image, prediction_text],
+            api_name="predict"
+        )
+        
+        clear_btn.click(
+            fn=clear_sequence,
+            inputs=[],
+            outputs=[prediction_text],
+            api_name="clear"
+        )
     
-    **開發者**: XiaoBai1221 | **平台**: Hugging Face Spaces
-    """)
+    return demo
+
+if __name__ == "__main__":
+    # 啟動應用程式
+    print("🎉 SignView2.0 手語辨識系統已啟動！")
     
-    # 事件處理
-    process_btn.click(
-        fn=process_image,
-        inputs=input_image,
-        outputs=[output_image, prediction_text]
-    )
+    demo = create_interface()
     
-    clear_btn.click(
-        fn=clear_sequence,
-        outputs=prediction_text
-    )
-
-# 啟動應用程式 - 不使用 share 參數
-print("🎉 SignView2.0 手語辨識系統已啟動！")
-demo.launch() 
+    # 修復錯誤：設定share=True和其他參數
+    demo.launch(
+        share=True,  # 解決localhost accessibility問題
+        server_name="0.0.0.0",  # 允許外部訪問
+        server_port=7860,  # 指定端口
+        debug=False,  # 避免debug模式的schema問題
+        show_error=True,  # 顯示錯誤訊息
+        quiet=False  # 顯示啟動訊息
+    )