diff --git a/app/service/design_fast/pipeline/no_seg_print_painting.py b/app/service/design_fast/pipeline/no_seg_print_painting.py
index 0ffaa93..a1db587 100644
--- a/app/service/design_fast/pipeline/no_seg_print_painting.py
+++ b/app/service/design_fast/pipeline/no_seg_print_painting.py
@@ -418,6 +418,9 @@ class NoSegPrintPainting:
 def tile_image(pattern, mask, dim, gap_x, gap_y, canvas_h, canvas_w, location, angle=0):
     """
     按照指定的 X/Y 间距平铺印花，并支持旋转
+    【修改版】以被平铺图案的【中心】作为平铺基准点
+
+    :param location: [[center_y, center_x]]  → 第一个图案中心的坐标
     :param angle: 旋转角度 (度数, 逆时针)
     """
     # 1. 确保输入是 RGBA
@@ -429,44 +432,52 @@ def tile_image(pattern, mask, dim, gap_x, gap_y, canvas_h, canvas_w, location, a
     rotated_p = rotate_image(resized_p, angle)
     p_h, p_w = rotated_p.shape[:2]
 
-    # 3. 创建透明单元格
-    cell_h, cell_w = p_h + gap_y, p_w + gap_x
+    # 3. 创建透明单元格（图案放在单元格中心）
+    cell_h = p_h + gap_y
+    cell_w = p_w + gap_x
+
     unit_cell = np.zeros((cell_h, cell_w, 4), dtype=np.uint8)
-    unit_cell[:p_h, :p_w, :] = rotated_p
+
+    # 计算图案在单元格中的左上角位置（让图案居中）
+    start_y = (cell_h - p_h) // 2
+    start_x = (cell_w - p_w) // 2
+    unit_cell[start_y:start_y + p_h, start_x:start_x + p_w, :] = rotated_p
 
     # 4. 执行平铺
-    tiles_y = (canvas_h // cell_h) + 2
-    tiles_x = (canvas_w // cell_w) + 2
+    tiles_y = (canvas_h // cell_h) + 3  # 多加一点余量更安全
+    tiles_x = (canvas_w // cell_w) + 3
     full_tiled = np.tile(unit_cell, (tiles_y, tiles_x, 1))
 
-    # 5. 裁剪平铺层
-    offset_x = int(location[0][1] % cell_w)
-    offset_y = int(location[0][0] % cell_h)
+    # 5. 计算偏移（关键修改：以中心为基准）
+    center_y, center_x = location[0][0], location[0][1]  # 第一个图案的中心位置
+
+    # 计算从哪个位置开始裁剪，才能让中心落在指定坐标
+    offset_y = int((center_y - (p_h // 2)) % cell_h)
+    offset_x = int((center_x - (p_w // 2)) % cell_w)
+
     tiled_layer = full_tiled[offset_y: offset_y + canvas_h,
     offset_x: offset_x + canvas_w]
 
-    # 6. 创建纯白色背景并合成
-    # 创建一个纯白色的 BGR 画布
+    # 6. 创建纯白色背景并合成（保持你原来的风格）
     white_background = np.full((canvas_h, canvas_w, 3), 255, dtype=np.uint8)
 
-    # 分离平铺层的颜色通道和 Alpha 通道
     tiled_bgr = tiled_layer[:, :, :3]
-    alpha_mask = tiled_layer[:, :, 3] / 255.0  # 归一化到 0-1
-    alpha_mask = cv2.merge([alpha_mask, alpha_mask, alpha_mask])  # 扩展到 3 通道
+    alpha_mask = tiled_layer[:, :, 3] / 255.0
+    alpha_mask = cv2.merge([alpha_mask, alpha_mask, alpha_mask])
 
-    # 执行 Alpha 混合：结果 = 平铺层 * alpha + 背景 * (1 - alpha)
     tiled_print = (tiled_bgr * alpha_mask + white_background * (1 - alpha_mask)).astype(np.uint8)
 
-    resized_mask = cv2.resize(mask, dim, interpolation=cv2.INTER_NEAREST)  # mask用最近邻，不模糊
-    rotated_mask = rotate_image(resized_mask, angle)
+    # ====================== 处理 Mask ======================
+    # Mask 也同样居中处理
+    resized_mask = cv2.resize(mask, dim, interpolation=cv2.INTER_NEAREST)
+    rotated_mask = rotate_image(resized_mask, angle)  # 注意：mask也需要旋转
 
-    # 创建mask单元
     unit_mask = np.zeros((cell_h, cell_w), dtype=np.uint8)
-    unit_mask[:p_h, :p_w] = rotated_mask
+    unit_mask[start_y:start_y + p_h, start_x:start_x + p_w] = rotated_mask
 
-    # 平铺mask
     full_mask_tiled = np.tile(unit_mask, (tiles_y, tiles_x))
-    tiled_mask = full_mask_tiled[offset_y: offset_y + canvas_h, offset_x: offset_x + canvas_w]
+    tiled_mask = full_mask_tiled[offset_y: offset_y + canvas_h,
+    offset_x: offset_x + canvas_w]
 
     return tiled_print, cv2.bitwise_not(tiled_mask)
 
diff --git a/app/service/design_fast/pipeline/print_painting.py b/app/service/design_fast/pipeline/print_painting.py
index c9f4653..ebf5856 100644
--- a/app/service/design_fast/pipeline/print_painting.py
+++ b/app/service/design_fast/pipeline/print_painting.py
@@ -479,6 +479,9 @@ class PrintPainting:
 def tile_image(pattern, mask, dim, gap_x, gap_y, canvas_h, canvas_w, location, angle=0):
     """
     按照指定的 X/Y 间距平铺印花，并支持旋转
+    【修改版】以被平铺图案的【中心】作为平铺基准点
+
+    :param location: [[center_y, center_x]]  → 第一个图案中心的坐标
     :param angle: 旋转角度 (度数, 逆时针)
     """
     # 1. 确保输入是 RGBA
@@ -490,45 +493,52 @@ def tile_image(pattern, mask, dim, gap_x, gap_y, canvas_h, canvas_w, location, a
     rotated_p = rotate_image(resized_p, angle)
     p_h, p_w = rotated_p.shape[:2]
 
-    # 3. 创建透明单元格
-    cell_h, cell_w = p_h + gap_y, p_w + gap_x
+    # 3. 创建透明单元格（图案放在单元格中心）
+    cell_h = p_h + gap_y
+    cell_w = p_w + gap_x
+
     unit_cell = np.zeros((cell_h, cell_w, 4), dtype=np.uint8)
-    unit_cell[:p_h, :p_w, :] = rotated_p
+
+    # 计算图案在单元格中的左上角位置（让图案居中）
+    start_y = (cell_h - p_h) // 2
+    start_x = (cell_w - p_w) // 2
+    unit_cell[start_y:start_y + p_h, start_x:start_x + p_w, :] = rotated_p
 
     # 4. 执行平铺
-    tiles_y = (canvas_h // cell_h) + 2
-    tiles_x = (canvas_w // cell_w) + 2
+    tiles_y = (canvas_h // cell_h) + 3  # 多加一点余量更安全
+    tiles_x = (canvas_w // cell_w) + 3
     full_tiled = np.tile(unit_cell, (tiles_y, tiles_x, 1))
 
-    # 5. 裁剪平铺层
-    offset_x = int(location[0][1] % cell_w)
-    offset_y = int(location[0][0] % cell_h)
+    # 5. 计算偏移（关键修改：以中心为基准）
+    center_y, center_x = location[0][0], location[0][1]  # 第一个图案的中心位置
+
+    # 计算从哪个位置开始裁剪，才能让中心落在指定坐标
+    offset_y = int((center_y - (p_h // 2)) % cell_h)
+    offset_x = int((center_x - (p_w // 2)) % cell_w)
+
     tiled_layer = full_tiled[offset_y: offset_y + canvas_h,
     offset_x: offset_x + canvas_w]
 
-    # 6. 创建纯白色背景并合成
-    # 创建一个纯白色的 BGR 画布
+    # 6. 创建纯白色背景并合成（保持你原来的风格）
     white_background = np.full((canvas_h, canvas_w, 3), 255, dtype=np.uint8)
 
-    # 分离平铺层的颜色通道和 Alpha 通道
     tiled_bgr = tiled_layer[:, :, :3]
-    alpha_mask = tiled_layer[:, :, 3] / 255.0  # 归一化到 0-1
-    alpha_mask = cv2.merge([alpha_mask, alpha_mask, alpha_mask])  # 扩展到 3 通道
+    alpha_mask = tiled_layer[:, :, 3] / 255.0
+    alpha_mask = cv2.merge([alpha_mask, alpha_mask, alpha_mask])
 
-    # 执行 Alpha 混合：结果 = 平铺层 * alpha + 背景 * (1 - alpha)
     tiled_print = (tiled_bgr * alpha_mask + white_background * (1 - alpha_mask)).astype(np.uint8)
 
-    # 处理mask的平铺
-    resized_mask = cv2.resize(mask, dim, interpolation=cv2.INTER_NEAREST)  # mask用最近邻，不模糊
-    rotated_mask = rotate_image(resized_mask, angle)
+    # ====================== 处理 Mask ======================
+    # Mask 也同样居中处理
+    resized_mask = cv2.resize(mask, dim, interpolation=cv2.INTER_NEAREST)
+    rotated_mask = rotate_image(resized_mask, angle)  # 注意：mask也需要旋转
 
-    # 创建mask单元
     unit_mask = np.zeros((cell_h, cell_w), dtype=np.uint8)
-    unit_mask[:p_h, :p_w] = rotated_mask
+    unit_mask[start_y:start_y + p_h, start_x:start_x + p_w] = rotated_mask
 
-    # 平铺mask
     full_mask_tiled = np.tile(unit_mask, (tiles_y, tiles_x))
-    tiled_mask = full_mask_tiled[offset_y: offset_y + canvas_h, offset_x: offset_x + canvas_w]
+    tiled_mask = full_mask_tiled[offset_y: offset_y + canvas_h,
+    offset_x: offset_x + canvas_w]
 
     return tiled_print, cv2.bitwise_not(tiled_mask)