Update app.py

app.py

@@ -6,7 +6,6 @@ import seaborn as sns
 import gradio as gr
 import os
 
-# 從 model.py 匯入架構
 from model import DualStreamTransformer, ArcMarginProduct
 
 css = """
@@ -55,9 +54,7 @@ if os.path.exists(MODEL_PATH):
     model.eval()
     print("模型載入成功！")
 
-# ==========================================
-# 邏輯函式
-# ==========================================
+
 def analyze_and_predict(*all_answers):
     if any(a is None for a in all_answers):
         raise gr.Error("請完整填寫所有問卷題目！")
@@ -65,7 +62,6 @@ def analyze_and_predict(*all_answers):
     ccmq_map = {"總是": 5, "經常": 4, "有時": 3, "很少": 2, "沒有": 1}
     osdi_map = {"總是": 4, "經常": 3, "一半一半": 2, "偶而": 1, "完全不曾": 0}
     
-    # 資料處理
     x1 = torch.tensor([[ccmq_map[a] for a in all_answers[:25]]], dtype=torch.float32).to(DEVICE)
     x2 = torch.tensor([[osdi_map[a] for a in all_answers[25:]]], dtype=torch.float32).to(DEVICE)
 
@@ -76,14 +72,12 @@ def analyze_and_predict(*all_answers):
         pred_idx = torch.argmax(probs, dim=1).item()
         conf = probs[0, pred_idx].item()
 
-    # 繪圖展示 (研討會風格)
     plt.rcParams['font.sans-serif'] = ['Microsoft JhengHei', 'DejaVu Sans']
     fig, ax = plt.subplots(figsize=(6, 4))
     sns.barplot(x=[conf, 1-conf], y=["預測類別", "其他"], palette="viridis", ax=ax)
-    ax.set_title(f"AI 診斷信心度: {conf:.2%}")
+    ax.set_title(f"診斷信心度: {conf:.2%}")
 
-    # 表格數據
-    table_data = [] # 此處可根據需求填充
+    table_data = [] 
     
     res_label = "🔴 乾眼風險 (SJS/DES)" if pred_idx == 1 else "🟢 正常/健康"
     return (
@@ -94,13 +88,13 @@ def analyze_and_predict(*all_answers):
         {"風險機率": conf if pred_idx==1 else 1-conf, "健康程度": 1 - (conf if pred_idx==1 else 1-conf)},
         table_data,
         fig,
-        fig # Demo 用，可替換為關聯圖
+        fig 
     )
 
 def reset_system():
     return [gr.update(visible=True), gr.update(visible=False), gr.update(selected=0)] + [None] * 37
 with gr.Blocks(theme=gr.themes.Soft(), css=".scroll-box { height: 450px; overflow-y: auto; }") as demo:
-    gr.Markdown("# 舌象與眼疾中西醫 AI 診斷系統")
+    gr.Markdown("# 中醫 AI 診斷系統")
 
     with gr.Column(visible=True) as stage_1:
         with gr.Tabs() as survey_tabs:
@@ -150,7 +144,6 @@ with gr.Blocks(theme=gr.themes.Soft(), css=".scroll-box { height: 450px; overflo
                 plot_2 = gr.Plot()
         finish_btn = gr.Button("結束並重新開始", size="lg")
 
-    # 邏輯綁定
     all_inputs = all_ccmq + all_osdi
     btn_next.click(fn=lambda: gr.Tabs(selected=1), outputs=survey_tabs)
     submit_btn.click(fn=analyze_and_predict, inputs=all_inputs, outputs=[stage_1, stage_2, res_title, res_desc, res_prob, res_table, plot_1, plot_2])