重新創建簡化版 app.py - 修復 Gradio 兼容性問題

app.py

@@ -0,0 +1,125 @@
+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！")
+
+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"
+    
+    try:
+        # 處理畫面
+        results, keypoints, flow_features = predictor.process_frame(image)
+        
+        # 繪製關鍵點
+        annotated_frame = predictor.draw_landmarks(image.copy(), results)
+        
+        # 獲取預測結果
+        top_predictions = predictor.get_top_predictions(top_k=3)
+        
+        # 格式化預測結果
+        if top_predictions:
+            prediction_text = "🎯 手語辨識結果:\n\n"
+            for i, (label, confidence) in enumerate(top_predictions, 1):
+                prediction_text += f"{i}. {label}: {confidence:.2%}\n"
+            
+            # 添加序列資訊
+            prediction_text += f"\n📊 序列進度: {len(predictor.keypoint_sequence)}/{predictor.sequence_length}"
+        else:
+            prediction_text = "📡 正在收集動作序列...\n請確保手語動作清晰可見"
+        
+        return annotated_frame, prediction_text
+        
+    except Exception as e:
+        return image, f"❌ 處理錯誤: {str(e)}"
+
+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"
+
+# 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")
+        
+        with gr.Column():
+            # 結果輸出
+            output_image = gr.Image(
+                label="辨識結果",
+                height=300
+            )
+            
+            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
+    
+    **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]
+    )
+    
+    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()