Update app.py

app.py

@@ -122,7 +122,7 @@ pipe = TryonPipeline.from_pretrained(
 pipe.unet_encoder = UNet_Encoder
 
 
-@spaces.GPU(duration=90)  # 実行時間を90秒に設定
+@spaces.GPU(duration=120)  # 実行時間を120秒に設定
 def start_tryon(
     dict, garm_img, garment_des, is_checked, is_checked_crop, denoise_steps, seed, num_images
 ):
@@ -212,8 +212,11 @@ def start_tryon(
     pose_img_tensor = tensor_transfrom(pose_img).unsqueeze(0).to(device, torch.float16)
     garm_tensor = tensor_transfrom(garm_img).unsqueeze(0).to(device, torch.float16)
 
+    # 初期化
+    output_images = gr.State([])
+
     # 最初にマスク画像を一度だけ出力
-    yield None, mask_gray
+    yield output_images.value, mask_gray
 
     for i in range(int(num_images)):
         current_seed = seed + i if seed is not None and seed != -1 else None
@@ -248,9 +251,18 @@ def start_tryon(
             out_img = images[0].resize(crop_size)
             human_img_copy = human_img_orig.copy()
             human_img_copy.paste(out_img, (int(left), int(top)))
-            yield [human_img_copy], None
+            new_image = human_img_copy
         else:
-            yield [images[0]], None
+            new_image = images[0]
+
+        # 画像を追加
+        output_images.value.append(new_image)
+
+        # ギャラリーを更新
+        yield output_images.value, None
+
+    # 最終的な結果を返す
+    return output_images.value, None
 
 
 garm_list = os.listdir(os.path.join(example_path, "cloth"))
@@ -335,4 +347,4 @@ with image_blocks as demo:
         api_name='tryon',
     )
 
-image_blocks.launch()
+image_blocks.launch(show_error=True)