Update app.py

app.py

@@ -84,7 +84,7 @@ classifier.eval()
 print("✅ Ready.")
 
 # ==========================
-# 3. Panel B: SVG 细胞图 (6类完整显示)
+# 3. Panel B: SVG 细胞图 (修复 NameError)
 # ==========================
 def generate_bacterial_svg(target_class):
     target = target_class.lower() if target_class else ""
@@ -104,10 +104,11 @@ def generate_bacterial_svg(target_class):
         "bg_text": "#78909C", "bg_line": "#CFD8DC", "bg_dot": "#B0BEC5"
     }
 
-    # 结构样式
+    # 结构样式 (修复了 width_norm 变量名错误)
     def style(active, base_fill, base_stroke, w_act="4", w_norm="2"):
         if active: return c["hl_fill"], c["hl_stroke"], w_act
-        return base_fill, base_stroke, width_norm
+        # ✅ 修复点：这里原来写成了 width_norm，现已修正为 w_norm
+        return base_fill, base_stroke, w_norm
 
     om_f, om_s, om_w = style(is_peri, c["bg_fill_om"], c["hl_stroke"] if is_om else c["bg_stroke"])
     cw_s = c["hl_stroke"] if is_cw else "#B0BEC5"
@@ -206,7 +207,7 @@ def draw_attention_heatmap_strip(weights, sequence):
     im = ax.imshow(data, cmap='Reds', aspect='auto', vmin=0, vmax=1)
     
     # 样式美化
-    ax.set_title("Sequence Attention Heatmap (High Color = Key Motif)", fontsize=10, fontweight='bold', color='#37474F', pad=10)
+    ax.set_title("Sequence Attention Heatmap (High Color = Key Feature)", fontsize=10, fontweight='bold', color='#37474F', pad=10)
     ax.set_xlabel("Residue Position", fontsize=9)
     
     # 隐藏 Y 轴刻度
@@ -332,7 +333,7 @@ with gr.Blocks(theme=theme, css=layout_css, title="LocPred-Prok") as app:
             output_label = gr.Label(num_top_classes=NUM_CLASSES, show_label=False)
 
         with gr.Column(elem_classes="panel-card"):
-            gr.Markdown("<div class='panel-header'><span class='panel-label'>D</span>Attention Heatmap (Motif Discovery)</div>")
+            gr.Markdown("<div class='panel-header'><span class='panel-label'>D</span>Learned Attention Heatmap</div>")
             output_plot = gr.Plot(label="Attention", show_label=False)
 
     submit_btn.click(fn=predict, inputs=sequence_input, outputs=[output_label, output_svg, output_plot])