feat: 添加获取选中模型的功能并优化模型数据处理

app.py

@@ -126,7 +126,7 @@ class Demo:
                     model_checkbox = gr.Checkbox(label=model_name, value=False)
                     seed_infr = gr.Number(label="种子值", value=42753)
                     slider_scale_infr = gr.Slider(-4, 4, label="滑块刻度", value=3, info="较大的滑块刻度会导致更强的编辑效果")
-                    self.model_sections.append((model_checkbox.value, seed_infr, slider_scale_infr.value))
+                    self.model_sections.append(((model_checkbox.label, model_checkbox.value), seed_infr.value, slider_scale_infr.value))
 
             with gr.Row():
                 self.start_noise_infr = gr.Slider(
@@ -293,14 +293,24 @@ class Demo:
         
         return [gr.update(interactive=True, value='Train'), gr.update(value='Done Training! \n Try your custom slider in the "Test" tab'), f'models/{save_name}', gr.update(choices=list(model_map.keys()), value=save_name.replace('.pt',''))]
 
+    def get_selected_models(self):
+        # 过滤出被选中的模型数据
+        selected = [
+            (section[0][0], section[1], section[2])  # (label, seed, scale)
+            for section in self.model_sections 
+            if section[0][1]  # 检查 checkbox value 是否为 True
+        ]
+        
+        if selected:
+            # 解包成三个数组
+            labels, seeds, scales = zip(*selected)
+            return list(labels), list(seeds), list(scales)
+        else:
+            return [], [], []
     
     def inference(self, prompt, start_noise, model, pbar=gr.Progress(track_tqdm=True)):
-        model_sections = self.model_sections
-        print(111, model_sections)
-        model_names = [section[0] for section in model_sections if section[0]]
-        seed_list = [section[1] for section in model_sections if section[0]]
-        scale_list = [section[2] for section in model_sections if section[0]]
-        print(222, model_names, seed_list, scale_list)
+        result = self.get_selected_models()
+        model_names, seed_list, scale_list = result
 
         if self.current_model != model:
             if model=='SDXL Turbo':