Update app.py

app.py

@@ -54,31 +54,24 @@ def extract_feature(signal: np.ndarray, sr: int) -> np.ndarray:
 # --- 4. 三種預測函式 ---
 
 def predict_face(img):
-    global _last_time, _last_result
+    print("predict_face called, img is None?", img is None)
     if img is None:
         return {}
-    now = time.time()
-    # 限频: 每 0.5 秒最多分析一次
-    if now - _last_time < 0.5 and _last_result:
-        return _last_result
     try:
         res = DeepFace.analyze(img, actions=["emotion"], detector_backend="opencv")
-        # 处理返回类型
+        # 省略 list/dict 处理...
+        # 直接取第一张人脸
         if isinstance(res, list):
-            first = res[0] if len(res) > 0 else {}
+            first = res[0] if res else {}
             emo = first.get("emotion", {}) if isinstance(first, dict) else {}
-        elif isinstance(res, dict):
-            emo = res.get("emotion", {})
         else:
-            emo = {}
-        _last_result = emo
-        _last_time = now
+            emo = res.get("emotion", {}) if isinstance(res, dict) else {}
         print("predict_face result:", emo)
         return emo
     except Exception as e:
         print("DeepFace.analyze error:", e)
-        # 出错时返回上次有效结果或空
-        return _last_result if _last_result else {}
+        return {}
+
 
 
 
@@ -144,15 +137,12 @@ def predict_text_mixed(text: str):
 
 # --- 5. 建立 Gradio 介面 ---
 with gr.Blocks() as demo:
-    gr.Markdown("## 多模態即時情緒分析")
-    with gr.Tabs():
-        # 臉部情緒 Tab
-        with gr.TabItem("臉部情緒"):
-            gr.Markdown("### 臉部情緒 (即時 Webcam Streaming 分析)")
-            with gr.Row():
-                webcam = gr.Image(sources="webcam", streaming=True, type="numpy", label="攝像頭畫面")
-                emotion_output = gr.Label(label="情緒分布")
-            webcam.stream(fn=predict_face, inputs=webcam, outputs=emotion_output)
+    with gr.TabItem("臉部情緒"):
+        with gr.Row():
+            webcam = gr.Image(source="webcam", streaming=True, type="numpy", label="攝像頭畫面")
+            face_out = gr.Label(label="情緒分布")
+        webcam.stream(fn=predict_face, inputs=webcam, outputs=face_out)
+
 
 
         # 其餘 Tab 可按原先寫法，或用 Blocks 方式