更新 .gitea/workflows/prod_build_manual.yaml

# Conflicts:
#	app/service/design_fast/utils/synthesis_item.py
#	app/service/prompt_generation/chatgpt_for_translation.py

.gitea/workflows/prod_build_manual.yaml

@@ -7,7 +7,7 @@ jobs:
     runs-on: ubuntu-latest
 
     env:
-      REMOTE_DEPLOY_PATH: /workspace/AiDA_Workspace/Python_Server_Workspace/Prod
+      REMOTE_DEPLOY_PATH: /workspace/AiDA_Workspace/Python_Server_Workspace/AiDA_Prod
 
     steps:
       - name: 1.检出代码

app/core/config.py

@@ -36,7 +36,7 @@ class Settings(BaseSettings):
 
     # --- mysql 配置信息 ---
     MYSQL_HOST: str = Field(default='', description="")
-    MYSQL_PORT: int = Field(default='', description="")
+    MYSQL_PORT: int = Field(default=3306, description="")
     MYSQL_USER: str = Field(default='', description="")
     MYSQL_PASSWORD: str = Field(default='', description="")
     MYSQL_DB: str = Field(default='', description="")

app/schemas/design.py

@@ -8,9 +8,9 @@ class SAMRequestModel(BaseModel):
     object_name: str = Field(..., description="minio object name ")
     image_path: str = Field(..., description="图片路径，必填字段")
     type: str = Field(..., description="推理类型，必填字段")
-    points: Optional[List[List[float]]] = None
-    labels: Optional[List[int]] = None
-    box: Optional[List[int]] = None
+    points: Optional[List[List[float]]] | None = None
+    labels: Optional[List[int]] | None = None
+    box: Optional[List[int]] | None = None
 
 
 class DesignModel(BaseModel):

app/schemas/generate_image.py

@@ -35,6 +35,13 @@ class GenerateSingleLogoImageModel(BaseModel):
     seed: str
 
 
+class GenerateSloganImageModel(BaseModel):
+    num_point: int
+    tasks_id: str
+    prompt: str
+    image_url: str
+
+
 class GenerateProductImageModel(BaseModel):
     tasks_id: str
     prompt: str
@@ -43,6 +50,13 @@ class GenerateProductImageModel(BaseModel):
     product_type: str
 
 
+class Flux2ToProductImgModel(BaseModel):
+    tasks_id: str
+    prompt: str
+    image_path: str
+    infer_step: int | None = None
+
+
 class GenerateRelightImageModel(BaseModel):
     tasks_id: str
     prompt: str

app/service/design_fast/pipeline/no_seg_print_painting.py

@@ -27,7 +27,7 @@ class NoSegPrintPainting:
             # 获取平铺 + 旋转 的overall print
             painting_dict = self.painting_collection(painting_dict, overall_print)
             result['no_seg_sketch_overall'] = result['no_seg_sketch_print'] = self.printpaint(result, painting_dict, print_=True)
-            result['pattern_image'] = result['no_seg_sketch_overall']
+            # result['pattern_image'] = result['no_seg_sketch_overall']
 
         if single_print:
             print_background = np.zeros((result['pattern_image'].shape[0], result['pattern_image'].shape[1], 3), dtype=np.uint8)
@@ -166,15 +166,17 @@ class NoSegPrintPainting:
         dim_max = max(painting_dict['dim_image_h'], painting_dict['dim_image_w'])
         dim_pattern = (int(dim_max * print_['scale'] / 5), int(dim_max * print_['scale'] / 5))
         gap = print_dict.get('gap', [[0, 0]])[0]
-        painting_dict['tile_print'] = tile_image(pattern=print_['image'],
-                                                 dim=dim_pattern,
-                                                 gap_x=gap[0],
-                                                 gap_y=gap[1],
-                                                 canvas_h=painting_dict['dim_image_h'],
-                                                 canvas_w=painting_dict['dim_image_w'],
-                                                 location=painting_dict['location'],
-                                                 angle=int(print_.get('print_angle_list', [0])[0]))
-        painting_dict['mask_inv_print'] = np.zeros(painting_dict['tile_print'].shape[:2], dtype=np.uint8)
+        painting_dict['tile_print'], painting_dict['mask_inv_print'] = tile_image(pattern=print_['image'],
+                                                                                  mask=print_['mask'],
+                                                                                  dim=dim_pattern,
+                                                                                  gap_x=gap[0],
+                                                                                  gap_y=gap[1],
+                                                                                  canvas_h=painting_dict['dim_image_h'],
+                                                                                  canvas_w=painting_dict['dim_image_w'],
+                                                                                  location=painting_dict['location'],
+                                                                                  angle=int(print_.get('print_angle_list', [0])[0]))
+        # painting_dict['mask_inv_print'] = np.zeros(painting_dict['tile_print'].shape[:2], dtype=np.uint8)
+        # painting_dict['mask_inv_print'] = self.get_mask_inv(painting_dict['tile_print'])
         return painting_dict
 
     def tile_image(self, pattern, dim, scale, dim_image_h, dim_image_w, location, trigger=False):
@@ -255,10 +257,15 @@ class NoSegPrintPainting:
         image = oss_get_image(oss_client=self.minio_client, bucket=bucket_name, object_name=object_name, data_type="PIL")
         # 判断图片格式，如果是RGBA 则贴在一张纯白图片上 防止透明转黑
         if image.mode == "RGBA":
+            mask_pil = image.split()[3]
             new_background = Image.new('RGB', image.size, (255, 255, 255))
             new_background.paste(image, mask=image.split()[3])
             image = new_background
+        else:
+            mask_pil = Image.new('L', image.size, 255)  # L=灰度图，255=纯白
         print_dict['image'] = cv2.cvtColor(np.asarray(image), cv2.COLOR_RGB2BGR)
+        print_dict['mask'] = cv2.threshold(np.array(mask_pil), 127, 255, cv2.THRESH_BINARY)[1]
+
         return print_dict
 
     def crop_image(self, image, image_size_h, image_size_w, location, print_shape):
@@ -408,9 +415,12 @@ class NoSegPrintPainting:
         return cropped_img
 
 
-def tile_image(pattern, dim, gap_x, gap_y, canvas_h, canvas_w, location, angle=0):
+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
@@ -422,35 +432,54 @@ def tile_image(pattern, dim, gap_x, gap_y, canvas_h, canvas_w, location, angle=0
     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)
-    result = (tiled_bgr * alpha_mask + white_background * (1 - alpha_mask)).astype(np.uint8)
+    tiled_print = (tiled_bgr * alpha_mask + white_background * (1 - alpha_mask)).astype(np.uint8)
 
-    return result
+    # ====================== 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
+
+    unit_mask = np.zeros((cell_h, cell_w), dtype=np.uint8)
+    unit_mask[start_y:start_y + p_h, start_x:start_x + p_w] = rotated_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]
+
+    return tiled_print, cv2.bitwise_not(tiled_mask)
 
 
 def rotate_image(image, angle):

app/service/design_fast/pipeline/print_painting.py

@@ -41,7 +41,7 @@ class PrintPainting:
         if overall_print['print_path_list']:
             overall_print['location'][0] = [x * y for x, y in zip(overall_print['location'][0], result['resize_scale'])]
             painting_dict = {'dim_image_h': result['pattern_image'].shape[0], 'dim_image_w': result['pattern_image'].shape[1]}
-            result['print_image'] = result['pattern_image']
+            result['print_image'] = result['pattern_image'].copy()
             # 获取平铺 + 旋转 的overall print
             painting_dict = self.painting_collection(painting_dict, overall_print)
             result['print_image'] = self.printpaint(result, painting_dict, print_=True)
@@ -229,15 +229,15 @@ class PrintPainting:
         dim_max = max(painting_dict['dim_image_h'], painting_dict['dim_image_w'])
         dim_pattern = (int(dim_max * print_['scale'] / 5), int(dim_max * print_['scale'] / 5))
         gap = print_dict.get('gap', [[0, 0]])[0]
-        painting_dict['tile_print'] = tile_image(pattern=print_['image'],
-                                                 dim=dim_pattern,
-                                                 gap_x=gap[0],
-                                                 gap_y=gap[1],
-                                                 canvas_h=painting_dict['dim_image_h'],
-                                                 canvas_w=painting_dict['dim_image_w'],
-                                                 location=painting_dict['location'],
-                                                 angle=int(print_.get('print_angle_list', [0])[0]))
-        painting_dict['mask_inv_print'] = np.zeros(painting_dict['tile_print'].shape[:2], dtype=np.uint8)
+        painting_dict['tile_print'], painting_dict['mask_inv_print'] = tile_image(pattern=print_['image'],
+                                                                                  mask=print_['mask'],
+                                                                                  dim=dim_pattern,
+                                                                                  gap_x=gap[0],
+                                                                                  gap_y=gap[1],
+                                                                                  canvas_h=painting_dict['dim_image_h'],
+                                                                                  canvas_w=painting_dict['dim_image_w'],
+                                                                                  location=painting_dict['location'],
+                                                                                  angle=int(print_.get('print_angle_list', [0])[0]))
         return painting_dict
 
     def tile_image(self, pattern, dim, scale, dim_image_h, dim_image_w, location, trigger=False):
@@ -318,10 +318,15 @@ class PrintPainting:
         image = oss_get_image(oss_client=self.minio_client, bucket=bucket_name, object_name=object_name, data_type="PIL")
         # 判断图片格式，如果是RGBA 则贴在一张纯白图片上 防止透明转黑
         if image.mode == "RGBA":
+            mask_pil = image.split()[3]
             new_background = Image.new('RGB', image.size, (255, 255, 255))
             new_background.paste(image, mask=image.split()[3])
             image = new_background
+        else:
+            mask_pil = Image.new('L', image.size, 255)  # L=灰度图，255=纯白
         print_dict['image'] = cv2.cvtColor(np.asarray(image), cv2.COLOR_RGB2BGR)
+        print_dict['mask'] = cv2.threshold(np.array(mask_pil), 127, 255, cv2.THRESH_BINARY)[1]
+
         return print_dict
 
     def crop_image(self, image, image_size_h, image_size_w, location, print_shape):
@@ -471,9 +476,12 @@ class PrintPainting:
         return cropped_img
 
 
-def tile_image(pattern, dim, gap_x, gap_y, canvas_h, canvas_w, location, angle=0):
+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
@@ -485,35 +493,54 @@ def tile_image(pattern, dim, gap_x, gap_y, canvas_h, canvas_w, location, angle=0
     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)
-    result = (tiled_bgr * alpha_mask + white_background * (1 - alpha_mask)).astype(np.uint8)
+    tiled_print = (tiled_bgr * alpha_mask + white_background * (1 - alpha_mask)).astype(np.uint8)
 
-    return result
+    # ====================== 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
+
+    unit_mask = np.zeros((cell_h, cell_w), dtype=np.uint8)
+    unit_mask[start_y:start_y + p_h, start_x:start_x + p_w] = rotated_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]
+
+    return tiled_print, cv2.bitwise_not(tiled_mask)
 
 
 def rotate_image(image, angle):

app/service/design_fast/utils/synthesis_item.py

@@ -342,82 +342,33 @@ def update_base_size_priority(layers):
 
 
 def transpose_rotate(layer, image):
-    """
-    融合镜像（transpose）和旋转（rotate）逻辑，计算实际旋转角度后执行图像变换，
-    并调整粘贴位置以保持视觉中心一致
+    # transpose[0]是左右 transpose[1]是上下
+    transpose = layer.get('transpose', [1, 1])  # 默认为1, 1代表不镜像
 
-    参数:
-        layer: 包含transpose、rotate、adaptive_position等属性的字典
-        image: PIL Image对象，待处理的图像
-
-    返回:
-        tuple: (处理后的Image对象, 新的粘贴坐标(x, y))
-    """
-    # 获取镜像状态（transpose[0]=左右，transpose[1]=上下；1=正常，-1=镜像）
-    transpose = layer.get('transpose', [1, 1])
-    is_mirrored_x = transpose[0]  # 左右镜像状态
-    is_mirrored_y = transpose[1]  # 上下镜像状态
-
-    # 获取原始旋转角度和粘贴位置
-    original_rotate = layer.get('rotate', 0)
+    rotate = layer.get('rotate', 0)
     paste_x, paste_y = layer['adaptive_position'][1], layer['adaptive_position'][0]
     original_w = image.width
     original_h = image.height
+    # transpose左右是1 上下是-1
+    if transpose[0] != 1:
+        # 左右
+        image = image.transpose(0)
 
-    # ------------------- 核心修改：计算实际旋转角度 -------------------
-    # 结合镜像状态，计算需要实际执行的旋转角度
-    actual_rotate = calculate_actual_rotate(original_rotate, is_mirrored_x, is_mirrored_y)
-    # ------------------- 执行镜像变换 -------------------
-    # 左右镜像（transpose[0] != 1 即-1，表示镜像）
-    if is_mirrored_x != 1:
-        image = image.transpose(0)  # 假设transpose(0)对应左右翻转（需匹配你的PIL版本）
+    if transpose[1] != 1:
+        # 上下
+        image = image.transpose(1)
 
-    # 上下镜像（transpose[1] != 1 即-1，表示镜像）
-    if is_mirrored_y != 1:
-        image = image.transpose(1)  # 假设transpose(1)对应上下翻转
-
-    # ------------------- 执行旋转并调整粘贴位置 -------------------
-    if actual_rotate != 0:  # 只有实际旋转角度非0时才执行旋转
-        # 注意：原代码中是rotate(-rotate)，这里同步调整符号
-        image = image.rotate(-actual_rotate, expand=True)
-
-        # 计算粘贴位置以保持视觉中心一致
-        # 原位置的中心点
+    if rotate:
+        image = image.rotate(-rotate, expand=True)
+        # 4. 计算粘贴位置以保持视觉中心一致
+        # 原本 (15, 36) 是 288*288 的左上角，我们计算其中心点
         target_center_x = paste_x + original_w // 2
         target_center_y = paste_y + original_h // 2
 
-        # 旋转后图像的新尺寸
+        # 获取旋转后图像的新尺寸
         new_w, new_h = image.size
 
-        # 新的左上角坐标（保证中心不变）
+        # 计算新的左上角坐标，使得旋转后的图像中心依然在原定的中心位置
         paste_x = target_center_x - new_w // 2
         paste_y = target_center_y - new_h // 2
-
-    return image, (paste_x, paste_y)
-
-
-def calculate_actual_rotate(before_rotate, is_mirrored_x, is_mirrored_y):
-    """
-    根据X/Y轴镜像状态计算实际的旋转角度，并标准化到0-360度
-
-    参数:
-        before_rotate: 原始旋转角度（数值类型）
-        is_mirrored_x: X轴镜像状态，-1表示镜像，1表示正常
-        is_mirrored_y: Y轴镜像状态，-1表示镜像，1表示正常
-
-    返回:
-        float/int: 标准化后的实际旋转角度（0-360度）
-    """
-    actual_rotate = before_rotate
-
-    # 根据镜像状态调整旋转角度
-    if is_mirrored_x == -1 and is_mirrored_y == 1:
-        actual_rotate = -before_rotate
-    elif is_mirrored_x == 1 and is_mirrored_y == -1:
-        actual_rotate = -before_rotate
-    # elif is_mirrored_x == -1 and is_mirrored_y == -1:
-    #     actual_rotate = before_rotate + 180
-
-    # 角度标准化到0-360度
-    normalized_rotate = ((actual_rotate % 360) + 360) % 360
-    return normalized_rotate
+    return image, (paste_x, paste_y)

app/service/prompt_generation/chatgpt_for_translation.py

@@ -104,7 +104,7 @@ def get_translation_from_llama3(text):
     # 创建请求的负载 translator是自定义的翻译模型
     payload = {
         "model": "AiDA-translator:latest",
-        "prompt": f"[{text}]",
+        "prompt": text,
         "stream": False
     }
     # 将负载转换为 JSON 格式
@@ -180,7 +180,7 @@ def get_prompt_from_image(image_path, text):
 
 def main():
     """Main function"""
-    text = get_translation_from_llama3("[火焰]")
+    text = get_translation_from_llama3("火焰")
     print(text)
 
 

docker-compose.yml

@@ -11,4 +11,10 @@ services:
       - /etc/localtime:/etc/localtime:ro
       - ./seg_cache:/seg_cache
     ports:
-      - "${SERVE_PORT}:80"
+      - "${SERVE_PORT}:80"
+    networks:
+      - aida_app_net
+networks:
+  aida_app_net:
+    external: true
+    name: aida_app_net