Update app.py

app.py

@@ -211,7 +211,7 @@ def start_tryon(dict, garm_img, garment_des, is_checked, is_checked_crop, denois
                     pose_img =  tensor_transfrom(pose_img).unsqueeze(0).to(device,torch.float16)
                     garm_tensor =  tensor_transfrom(garm_img).unsqueeze(0).to(device,torch.float16)
                     generator = torch.Generator(device).manual_seed(seed) if seed is not None else None
-                    images = pipe(
+                    result = pipe(
                         prompt_embeds=prompt_embeds.to(device,torch.float16),
                         negative_prompt_embeds=negative_prompt_embeds.to(device,torch.float16),
                         pooled_prompt_embeds=pooled_prompt_embeds.to(device,torch.float16),
@@ -228,8 +228,18 @@ def start_tryon(dict, garm_img, garment_des, is_checked, is_checked_crop, denois
                         width=768,
                         ip_adapter_image = garm_img.resize((768,1024)),
                         guidance_scale=2.0,
-                    ).images
-
+                    )
+                    
+                    # 결과 형태 확인 및 처리
+                    if isinstance(result, tuple):
+                        images = result[0]
+                    elif hasattr(result, 'images'):
+                        images = result.images
+                    else:
+                        raise ValueError(f"Unexpected result type: {type(result)}")
+
+    print(f"Result type: {type(result)}")
+    print(f"Result content: {result}")
     print(f"Mask shape: {mask.size}")
     print(f"Human image shape: {human_img.size}")
     print(f"Garment image shape: {garm_img.size}")
@@ -242,20 +252,6 @@ def start_tryon(dict, garm_img, garment_des, is_checked, is_checked_crop, denois
     else:
         return images[0], mask_gray, status_message
 
-garm_list = os.listdir(os.path.join(example_path,"cloth"))
-garm_list_path = [os.path.join(example_path,"cloth",garm) for garm in garm_list]
-
-human_list = os.listdir(os.path.join(example_path,"human"))
-human_list_path = [os.path.join(example_path,"human",human) for human in human_list]
-
-human_ex_list = []
-for ex_human in human_list_path:
-    ex_dict= {}
-    ex_dict['background'] = ex_human
-    ex_dict['layers'] = None
-    ex_dict['composite'] = None
-    human_ex_list.append(ex_dict)
-
 image_blocks = gr.Blocks(theme="Nymbo/Nymbo_Theme").queue(max_size=12)
 with image_blocks as demo:
     with gr.Column():