Update app.py

app.py

@@ -195,7 +195,7 @@ def process_image_mask(image_mask_dict):
     background = image_mask_dict.get("background")
     layers     = image_mask_dict.get("layers")
 
-    if background is None or not layers:
+    if background is None:
         return None
 
     # ---- 1) Drop alpha from background ----
@@ -206,32 +206,36 @@ def process_image_mask(image_mask_dict):
     if img_array.ndim == 3 and img_array.shape[2] == 4:
         img_array = img_array[..., :3]
 
-    # ---- 2) Load mask layer and binarize ----
-    layer = layers[0]
-    if isinstance(layer, Image.Image) and layer.mode == "RGBA":
-        layer = layer.convert("RGB")
-    mask_array = np.array(layer)
-    if mask_array.ndim == 3 and mask_array.shape[2] == 4:
-        mask_array = mask_array[..., :3]
-
-    # convert to gray + binary
-    if mask_array.ndim == 3:
-        mask_gray = cv2.cvtColor(mask_array, cv2.COLOR_RGB2GRAY)
-    else:
-        mask_gray = mask_array
-    _, binary_mask = cv2.threshold(mask_gray, 1, 255, cv2.THRESH_BINARY)
+    # ---- 2) マスクがある場合のみマスク処理 ----
+    if layers and len(layers) > 0:
+        layer = layers[0]
+        if isinstance(layer, Image.Image) and layer.mode == "RGBA":
+            layer = layer.convert("RGB")
+        mask_array = np.array(layer)
+        if mask_array.ndim == 3 and mask_array.shape[2] == 4:
+            mask_array = mask_array[..., :3]
+
+        # convert to gray + binary
+        if mask_array.ndim == 3:
+            mask_gray = cv2.cvtColor(mask_array, cv2.COLOR_RGB2GRAY)
+        else:
+            mask_gray = mask_array
+        _, binary_mask = cv2.threshold(mask_gray, 1, 255, cv2.THRESH_BINARY)
 
-    # 市松模様合成ロジック
-    total_pixels = img_array.shape[0] * img_array.shape[1]
-    cell_size = max(int(np.sqrt(total_pixels) / 20), 10)
-    checkerboard = create_checkerboard(img_array.shape[1], img_array.shape[0], cell_size)
+        # 市松模様合成ロジック
+        total_pixels = img_array.shape[0] * img_array.shape[1]
+        cell_size = max(int(np.sqrt(total_pixels) / 20), 10)
+        checkerboard = create_checkerboard(img_array.shape[1], img_array.shape[0], cell_size)
 
-    result = img_array.copy()
-    binary_mask_3ch = np.stack([binary_mask]*3, axis=2) // 255
-    for c in range(3):
-        result[..., c] = result[..., c] * (1 - binary_mask_3ch[..., c]) + checkerboard[..., c] * binary_mask_3ch[..., c]
+        result = img_array.copy()
+        binary_mask_3ch = np.stack([binary_mask]*3, axis=2) // 255
+        for c in range(3):
+            result[..., c] = result[..., c] * (1 - binary_mask_3ch[..., c]) + checkerboard[..., c] * binary_mask_3ch[..., c]
 
-    return result.astype(np.uint8)
+        return result.astype(np.uint8)
+    else:
+        # マスクがない場合は元の画像をそのまま返す
+        return img_array
 
 # 最も近い解像度を見つける関数
 def find_nearest_resolution(width, height):