feat:

fix: 移除打印

.gitea/workflows/develop_build_manual.yaml

@@ -35,6 +35,4 @@ jobs:
             cd ${{ env.REMOTE_DEPLOY_PATH }}
             
             docker-compose down 2>&1
-            docker-compose up -d --build --remove-orphans 2>&1
+            docker-compose up -d  2>&1
-            
-            docker image prune -f 2>&1

.gitea/workflows/develop_build_scheduled.yaml

@@ -1,8 +1,8 @@
 name: 定时 AiDA python develop 分支构建部署
 on:
   # 使用 schedule 触发器，遵循标准的 Cron 格式 (分钟 小时-8 日期 月份 星期)
-  schedule:
+  # schedule:
-    - cron: '30 9 * * *'
+  #   - cron: '30 9 * * *'
 
 jobs:
   scheduled_deploy:

.gitea/workflows/ltx_develop_build_manual.yaml

@@ -0,0 +1,40 @@
+name: 手动 AiDA python develop 分支构建部署
+on:
+  workflow_dispatch:
+
+jobs:
+  scheduled_deploy:
+    runs-on: ubuntu-latest
+
+    env:
+      REMOTE_DEPLOY_PATH: /workspace/Trinity/Fastapi_AiDA_Trinity_Dev
+
+    steps:
+      - name: 1.检出代码
+        uses: actions/checkout@v4
+        with:
+          ref: 'dev-ltx'
+
+      - name: 2.复制文件到服务器
+        uses: appleboy/scp-action@v0.1.7
+        with:
+          host: ${{ secrets.SERVER_HOST }}
+          username: ${{ secrets.SERVER_USER }}
+          password: ${{ secrets.SERVER_PASSWORD }}
+          source: "."
+          target: ${{ env.REMOTE_DEPLOY_PATH }}
+      
+      - name: 3.重启docker-compose
+        uses: appleboy/ssh-action@v0.1.10
+        with:
+          host: ${{ secrets.SERVER_HOST }}
+          username: ${{ secrets.SERVER_USER }}
+          password: ${{ secrets.SERVER_PASSWORD }}
+          script: |
+            # 进入项目目录
+            cd ${{ env.REMOTE_DEPLOY_PATH }}
+            
+            docker-compose down 2>&1
+            docker-compose up -d --build --remove-orphans 2>&1
+            
+            docker image prune -f 2>&1

.gitea/workflows/prod_build_manual.yaml

@@ -0,0 +1,40 @@
+name: 定时 AiDA python prod 分支构建部署
+on:
+  workflow_dispatch:
+
+jobs:
+  scheduled_deploy:
+    runs-on: ubuntu-latest
+
+    env:
+      REMOTE_DEPLOY_PATH: /workspace/Trinity/Fastapi_AiDA_Trinity_Prod
+
+    steps:
+      - name: 1.检出代码
+        uses: actions/checkout@v4
+        with:
+          ref: 'master'
+
+      - name: 2.复制文件到服务器
+        uses: appleboy/scp-action@v0.1.7
+        with:
+          host: ${{ secrets.SERVER_HOST }}
+          username: ${{ secrets.SERVER_USER }}
+          password: ${{ secrets.SERVER_PASSWORD }}
+          source: "."
+          target: ${{ env.REMOTE_DEPLOY_PATH }}
+      
+      - name: Restart Docker containers
+        uses: appleboy/ssh-action@v0.1.10
+        with:
+          host: ${{ secrets.SERVER_HOST }}
+          username: ${{ secrets.SERVER_USER }}
+          password: ${{ secrets.SERVER_PASSWORD }}
+          script: |
+            # 进入项目目录
+            cd ${{ env.REMOTE_DEPLOY_PATH }}
+            
+            docker-compose down 2>&1
+            docker-compose up -d 2>&1
+            
+            docker image prune -f 2>&1

.gitea/workflows/prod_build_scheduled.yaml

@@ -0,0 +1,42 @@
+name: 定时 AiDA python prod 分支构建部署
+on:
+  # 使用 schedule 触发器，遵循标准的 Cron 格式 (分钟 小时-8 日期 月份 星期)
+  schedule:
+    - cron: '07 13 23 1 *'
+
+jobs:
+  scheduled_deploy:
+    runs-on: ubuntu-latest
+
+    env:
+      REMOTE_DEPLOY_PATH: /workspace/Trinity/Fastapi_AiDA_Trinity_Prod
+
+    steps:
+      - name: 1.检出代码
+        uses: actions/checkout@v4
+        with:
+          ref: 'master'
+
+      - name: 2.复制文件到服务器
+        uses: appleboy/scp-action@v0.1.7
+        with:
+          host: ${{ secrets.SERVER_HOST }}
+          username: ${{ secrets.SERVER_USER }}
+          password: ${{ secrets.SERVER_PASSWORD }}
+          source: "."
+          target: ${{ env.REMOTE_DEPLOY_PATH }}
+      
+      - name: Restart Docker containers
+        uses: appleboy/ssh-action@v0.1.10
+        with:
+          host: ${{ secrets.SERVER_HOST }}
+          username: ${{ secrets.SERVER_USER }}
+          password: ${{ secrets.SERVER_PASSWORD }}
+          script: |
+            # 进入项目目录
+            cd ${{ env.REMOTE_DEPLOY_PATH }}
+            
+            docker-compose down 2>&1
+            docker-compose up -d 2>&1
+            
+            docker image prune -f 2>&1

app/api/api_design.py

@@ -4,6 +4,7 @@ import logging
 import requests
 from fastapi import APIRouter, HTTPException, BackgroundTasks
 
+from app.core.config import settings
 from app.schemas.design import DesignModel, ModelProgressModel, DesignStreamModel, SAMRequestModel
 from app.schemas.response_template import ResponseModel
 from app.service.design_fast.design_generate import design_generate, design_generate_v2
@@ -425,7 +426,7 @@ async def seg_anything(request_data: SAMRequestModel):
     """
     try:
         logger.info(f"seg_anything request item is : @@@@@@:{json.dumps(request_data.dict(), indent=4)}")
-        data = requests.post("http://10.1.1.240:10075/predict", json=request_data.dict())
+        data = requests.post(f"http://{settings.A6000_SERVICE_HOST}:10075/predict", json=request_data.dict())
         logger.info(f"seg_anything response @@@@@@:{json.dumps(json.loads(data.content), indent=4)}")
         return ResponseModel(data=json.loads(data.content))
     except Exception as e:

app/core/config.py

@@ -64,11 +64,16 @@ class Settings(BaseSettings):
     # --- Design Callback Java 接口 ---
     JAVA_STREAM_API_URL: str = Field(default='', description="")
 
+    # --- 服务器IP ---
+    A6000_SERVICE_HOST: str = Field(default='', description="")
+    B_4_X_4090_SERVICE_HOST: str = Field(default='', description="")
+
     # --- 其他配置信息 以下均为Docker容器内配置---
     LOGS_PATH: str = Field(default="/logs/", description="")
     CATEGORY_PATH: str = Field(default="/app/service/attribute/config/descriptor/category/category_dis.csv", description="")
     SEG_CACHE_PATH: str = Field(default="/seg_cache/", description="")
     RECOMMEND_PATH_PREFIX: str = Field(default="/app/service/recommend/", description="")
+    SERVE_PORT: int = Field(default=2010, description="")
 
 
 settings = Settings()
@@ -117,39 +122,41 @@ KEYPOINT_RESULT_TABLE_FIELD_SET = ('neckline_left', 'neckline_right', 'shoulder_
 MILVUS_TABLE_KEYPOINT = "keypoint_cache_2"
 
 # ollama 地址
-OLLAMA_URL = "http://10.1.1.240:11434/api/embeddings"
+OLLAMA_URL = f"http://{settings.A6000_SERVICE_HOST}:11434/api/embeddings"
 
 """Triton Server Config"""
 # Design
-DESIGN_MODEL_URL = '10.1.1.240:10000'
+DESIGN_MODEL_URL = f'{settings.A6000_SERVICE_HOST}:10000'
 DESIGN_MODEL_NAME = 'seg_knet'
+# Seg Product
+SEG_PRODUCT_MODEL_URL = f'{settings.B_4_X_4090_SERVICE_HOST}:3000'
 # Generate Image
-GI_MODEL_URL = '10.1.1.240:10061'
+GI_MODEL_URL = f'{settings.A6000_SERVICE_HOST}:10061'
 GI_MODEL_NAME = 'flux'
 # Generate Single Logo
-GSL_MODEL_URL = '10.1.1.243:10041'
+GSL_MODEL_URL = f'{settings.B_4_X_4090_SERVICE_HOST}:10041'
 GSL_MODEL_NAME = 'stable_diffusion_xl_transparent'
 # Generate Product （整套和单品）
-GPI_MODEL_URL = '10.1.1.243:10051'
+GPI_MODEL_URL = f'{settings.B_4_X_4090_SERVICE_HOST}:10051'
 GPI_MODEL_NAME_OVERALL = 'diffusion_ensemble_all'
 GPI_MODEL_NAME_SINGLE = 'stable_diffusion_1_5_cnet'
 
 # 以下停用中...*************
 # 多视角生成
-GMV_MODEL_URL = '10.1.1.243:10081'
+GMV_MODEL_URL = f'{settings.B_4_X_4090_SERVICE_HOST}:10081'
 GMV_MODEL_NAME = 'multi_view'
 # 超分
 SR_MODEL_NAME = "super_resolution"
-SR_TRITON_URL = "10.1.1.240:10031"
+SR_TRITON_URL = f"{settings.A6000_SERVICE_HOST}:10031"
 # 打光
-GRI_MODEL_URL = '10.1.1.240:10051'
+GRI_MODEL_URL = f'{settings.A6000_SERVICE_HOST}:10051'
 GRI_MODEL_NAME_OVERALL = 'diffusion_relight_ensemble'
 GRI_MODEL_NAME_SINGLE = 'stable_diffusion_1_5_relight'
 # agent 图片生成
-FAST_GI_MODEL_URL = '10.1.1.243:10011'
+FAST_GI_MODEL_URL = f'{settings.B_4_X_4090_SERVICE_HOST}:10011'
 FAST_GI_MODEL_NAME = 'stable_diffusion_xl'
 # 图转视频 triton版
-PT_MODEL_URL = '10.1.1.243:10061'
+PT_MODEL_URL = f'{settings.B_4_X_4090_SERVICE_HOST}:10061'
 
 # *************
 

app/service/brand_dna/service.py

@@ -9,7 +9,7 @@ import torch.nn.functional as F
 import tritonclient.http as httpclient
 from minio import Minio
 
-from app.core.config import DESIGN_MODEL_URL
+from app.core.config import DESIGN_MODEL_URL, SEG_PRODUCT_MODEL_URL
 from app.core.config import settings
 from app.schemas.brand_dna import BrandDnaModel
 from app.service.attribute.config import const
@@ -29,7 +29,7 @@ class BrandDna:
         self.attr_type = pd.read_csv(settings.CATEGORY_PATH)
         # self.attr_type = pd.read_csv(r"E:\workspace\trinity_client_aida\app\service\attribute\config\descriptor\category\category_dis.csv")
         self.att_client = httpclient.InferenceServerClient(url=DESIGN_MODEL_URL)
-        self.seg_client = httpclient.InferenceServerClient(url='10.1.1.243:30000')
+        self.seg_client = httpclient.InferenceServerClient(url=SEG_PRODUCT_MODEL_URL)
         self.const = const
         # self.const = local_debug_const
 

app/service/clothing_seg/service.py

@@ -23,7 +23,7 @@ class ClothingSeg:
     def __init__(self, request_data):
         self.image_data = request_data.image_data
         self.user_id = request_data.user_id
-        self.triton_client = grpcclient.InferenceServerClient(url="10.1.1.243:10071")
+        self.triton_client = grpcclient.InferenceServerClient(url=f"{settings.B_4_X_4090_SERVICE_HOST}:10071")
 
     @RunTime
     def get_result(self):
@@ -139,7 +139,7 @@ def get_bounding_box(mask):
 
 if __name__ == "__main__":
     test_data = ClothingSegModel(
-        user_id=89,
+        user_id="89",
         image_data=[
             # {
             #     "image_url": "test/clothing_seg/dress.jpg",

app/service/design_fast/design_generate.py

@@ -130,7 +130,7 @@ def design_generate(request_data):
                 items_response['synthesis_url'] = synthesis(layers, new_size, basic)
 
         else:
-            item_result = process_item(object['items'][0], basic)
+            item_result = process_item(object['items'][0], basic, design_type)
             items_response['layers'].append({
                 'image_category': f"{item_result['name']}_front",
                 'image_size': item_result['back_image'].size if item_result['back_image'] else None,
@@ -184,6 +184,7 @@ def design_generate_v2(request_data):
 
     def process_object(object, callback_url):
         basic = object['basic']
+        design_type = basic.get('design_type', "default")
         items_response = {
             'layers': [],
             'objectSign': object['objectSign'] if 'objectSign' in object.keys() else "",
@@ -192,7 +193,7 @@ def design_generate_v2(request_data):
         if basic['single_overall'] == "overall":
             item_results = []
             for item in object['items']:
-                item_results.append(process_item(item, basic))
+                item_results.append(process_item(item, basic, design_type))
             layers = []
             for item in item_results:
                 process_layer(item, layers)
@@ -217,7 +218,7 @@ def design_generate_v2(request_data):
                 })
             items_response['synthesis_url'] = synthesis(layers, new_size, basic)
         else:
-            item_result = process_item(object['items'][0], basic)
+            item_result = process_item(object['items'][0], basic, design_type)
             items_response['layers'].append({
                 'image_category': f"{item_result['name']}_front",
                 'image_size': item_result['back_image'].size if item_result['back_image'] else None,

app/service/design_fast/item.py

@@ -82,8 +82,8 @@ class OthersMergeItem(BaseItem):
             Segmentation(minio_client),
             # BackPerspective(minio_client),
             Color(minio_client),
-            NoSegPrintPainting(minio_client),
+            # NoSegPrintPainting(minio_client),
-            PrintPainting(minio_client),
+            # PrintPainting(minio_client),
             Scaling(),
             Split(minio_client)
         ]

app/service/design_fast/pipeline/no_seg_print_painting.py

@@ -169,7 +169,7 @@ class NoSegPrintPainting:
                                                  canvas_h=painting_dict['dim_image_h'],
                                                  canvas_w=painting_dict['dim_image_w'],
                                                  location=painting_dict['location'],
-                                                 angle=45)
+                                                 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)
         return painting_dict
 

app/service/design_fast/pipeline/print_painting.py

@@ -232,7 +232,7 @@ class PrintPainting:
                                                  canvas_h=painting_dict['dim_image_h'],
                                                  canvas_w=painting_dict['dim_image_w'],
                                                  location=painting_dict['location'],
-                                                 angle=45)
+                                                 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)
         return painting_dict
 

app/service/design_fast/pipeline/segmentation.py

@@ -47,6 +47,7 @@ class Segmentation:
                 # 本地查询seg 缓存是否存在
                 _, seg_result = self.load_seg_result(result["image_id"])
                 # 判断缓存和实际图片size是否相同
+                _ = False
                 if not _ or result["image"].shape[:2] != seg_result.shape:
                     # 推理获得seg 结果
                     seg_result = get_seg_result(result['image'])

app/service/design_fast/pipeline/split.py

@@ -21,7 +21,9 @@ class Split(object):
         try:
             if result['name'] in ('outwear', 'dress', 'blouse', 'skirt', 'trousers', 'tops', 'bottoms', 'others'):
                 if result.get('design_type', None) == 'merge':
-                    # merge 不需要返回mask (红绿图)
+                    ori_front_mask = result['front_mask'].copy()
+                    ori_back_mask = result['back_mask'].copy()
+
                     if result['resize_scale'][0] == 1.0 and result['resize_scale'][1] == 1.0:
                         front_mask = result['front_mask']
                         back_mask = result['back_mask']
@@ -43,6 +45,20 @@ class Split(object):
                     result_front_image_pil = Image.fromarray(cv2.cvtColor(result_front_image, cv2.COLOR_BGR2RGBA))
                     result['front_image'], result["front_image_url"], _ = upload_png_mask(self.minio_client, result_front_image_pil, f'{generate_uuid()}', mask=None)
 
+                    height, width = ori_front_mask.shape
+                    mask_image = np.zeros((height, width, 3))
+                    mask_image[ori_front_mask != 0] = [0, 0, 255]
+                    mask_image[ori_back_mask != 0] = [0, 255, 0]
+                    rbga_mask = rgb_to_rgba(mask_image, ori_front_mask + ori_back_mask)
+                    mask_pil = Image.fromarray(cv2.cvtColor(rbga_mask.astype(np.uint8), cv2.COLOR_BGR2RGBA))
+                    image_data = io.BytesIO()
+                    mask_pil.save(image_data, format='PNG')
+                    image_data.seek(0)
+                    image_bytes = image_data.read()
+                    req = oss_upload_image(oss_client=self.minio_client, bucket="aida-clothing", object_name=f"mask/mask_{generate_uuid()}.png", image_bytes=image_bytes)
+                    result['mask_url'] = req.bucket_name + "/" + req.object_name
+
+
                     result_back_image = np.zeros_like(rgba_image)
                     back_mask = cv2.resize(back_mask, new_size, interpolation=cv2.INTER_AREA)
                     result_back_image[back_mask != 0] = rgba_image[back_mask != 0]

app/service/design_fast/utils/organize.py

@@ -79,7 +79,7 @@ def organize_others(layer):
     front_layer = dict(priority=layer['priority'] if layer.get("layer_order", False) else PRIORITY_DICT.get(f'{layer["name"].lower()}_front', None),
                        name=f'{layer["name"].lower()}_front',
                        image=layer["front_image"],
-                       # mask_image=layer['front_mask_image'],
+                       mask_image=layer['front_mask_image'],
                        image_url=layer['front_image_url'],
                        mask_url=layer.get('mask_url', None),
                        sacle=layer['scale'],
@@ -97,7 +97,7 @@ def organize_others(layer):
     back_layer = dict(priority=-layer.get("priority", 0) if layer.get("layer_order", False) else PRIORITY_DICT.get(f'{layer["name"].lower()}_back', None),
                       name=f'{layer["name"].lower()}_back',
                       image=layer["back_image"],
-                      # mask_image=layer['back_mask_image'],
+                      mask_image=layer['back_mask_image'],
                       image_url=layer['back_image_url'],
                       mask_url=layer.get('mask_url', None),
                       sacle=layer['scale'],

app/service/design_fast/utils/synthesis_item.py

@@ -342,32 +342,82 @@ def update_base_size_priority(layers):
 
 
 def transpose_rotate(layer, image):
-    # 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
+    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
 
-    rotate = layer.get('rotate', 0)
+    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)
     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
+    # ------------------- 核心修改：计算实际旋转角度 -------------------
-    if transpose[0] != 1:
+    # 结合镜像状态，计算需要实际执行的旋转角度
-        # 左右
+    actual_rotate = calculate_actual_rotate(original_rotate, is_mirrored_x, is_mirrored_y)
-        image = image.transpose(0)
+    # ------------------- 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:
+    # 上下镜像（transpose[1] != 1 即-1，表示镜像）
-        # 上下
+    if is_mirrored_y != 1:
-        image = image.transpose(1)
+        image = image.transpose(1)  # 假设transpose(1)对应上下翻转
 
-    if rotate:
+    # ------------------- 执行旋转并调整粘贴位置 -------------------
-        image = image.rotate(-rotate, expand=True)
+    if actual_rotate != 0:  # 只有实际旋转角度非0时才执行旋转
-        # 4. 计算粘贴位置以保持视觉中心一致
+        # 注意：原代码中是rotate(-rotate)，这里同步调整符号
-        # 原本 (15, 36) 是 288*288 的左上角，我们计算其中心点
+        image = image.rotate(-actual_rotate, expand=True)
-        target_center_x = 15 + 288 // 2
-        target_center_y = 36 + 288 // 2
 
-        # 获取旋转后图像的新尺寸
+        # 计算粘贴位置以保持视觉中心一致
+        # 原位置的中心点
+        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
         new_w, new_h = image.size
 
-        # 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
+        # 新的左上角坐标（保证中心不变）
         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

app/service/design_pre_processing/service.py

@@ -7,7 +7,7 @@ import numpy as np
 import torch
 import tritonclient.grpc as grpcclient
 from minio import Minio
-from pymilvus import MilvusClient
+# from pymilvus import MilvusClient
 from urllib3.exceptions import ResponseError
 
 from app.core.config import settings, SR_MODEL_NAME, SR_TRITON_URL, MILVUS_TABLE_KEYPOINT, KEYPOINT_RESULT_TABLE_FIELD_SET
@@ -58,7 +58,21 @@ class DesignPreprocessing:
             if len(image.shape) == 2:
                 image = cv2.cvtColor(image, cv2.COLOR_GRAY2RGB)
             elif image.shape[2] == 4:  # 如果是四通道 mask
-                image = image[:, :, :3]
+                # 分离RGB和Alpha通道
+                bgr = image[:, :, :3]
+                alpha = image[:, :, 3]
+
+                # 创建白色背景（也可改为其他颜色，如(255,255,255)就是白色）
+                background_color = (255, 255, 255)
+                background = np.full_like(bgr, background_color)
+
+                # 将Alpha通道转换为掩码（0=透明，255=不透明）
+                alpha_mask = alpha / 255.0  # 归一化到0-1
+                alpha_mask = np.expand_dims(alpha_mask, axis=-1)  # 扩展维度，方便广播计算
+
+                # 混合背景和原图：透明区域显示背景色，不透明区域显示原图
+                image = (bgr * alpha_mask + background * (1 - alpha_mask)).astype(np.uint8)
+                # 此时image已经是3通道RGB，无需再执行image = image[:, :, :3]
             obj["image_obj"] = image
         return image_list
 
@@ -174,8 +188,9 @@ class DesignPreprocessing:
             scale = 0.4
             if waist_width / scale >= image_width:
                 add_width = int((waist_width / scale - image_width) / 2)
-                ret = cv2.copyMakeBorder(image['obj'], 0, 0, add_width, add_width, cv2.BORDER_CONSTANT, value=(256, 256, 256))
+                ret = cv2.copyMakeBorder(image['obj'], 0, 0, add_width, add_width, cv2.BORDER_CONSTANT, value=(255, 255, 255))
-                image_bytes = cv2.imencode(".jpg", ret)[1].tobytes()
+                img_rgba = cv2.cvtColor(ret, cv2.COLOR_RGB2RGBA)
+                image_bytes = cv2.imencode(".png", img_rgba)[1].tobytes()
                 # image['show_image_url'] = f"{image['image_url'].split('/', 1)[0]}/{self.minio_client.put_object(image['image_url'].split('/', 1)[0], image['image_url'].split('/', 1)[1].replace('.', '-show.'), io.BytesIO(image_bytes), len(image_bytes), content_type='image/jpeg').object_name}"
                 bucket_name = image['image_url'].split('/', 1)[0]
                 object_name = image['image_url'].split('/', 1)[1].replace('.', '-show.')
@@ -261,14 +276,15 @@ class DesignPreprocessing:
 
     def keypoint_cache(self, sketch):
         try:
-            client = MilvusClient(uri=settings.MILVUS_URL, token=settings.MILVUS_TOKEN, db_name=settings.MILVUS_ALIAS)
+            # client = MilvusClient(uri=settings.MILVUS_URL, token=settings.MILVUS_TOKEN, db_name=settings.MILVUS_ALIAS)
             keypoint_id = sketch['image_id']
-            res = client.query(
+            # res = client.query(
-                collection_name=MILVUS_TABLE_KEYPOINT,
+            #     collection_name=MILVUS_TABLE_KEYPOINT,
-                # ids=[keypoint_id],
+            #     # ids=[keypoint_id],
-                filter=f"keypoint_id == {keypoint_id}",
+            #     filter=f"keypoint_id == {keypoint_id}",
-                output_fields=['keypoint_vector', 'keypoint_site']
+            #     output_fields=['keypoint_vector', 'keypoint_site']
-            )
+            # )
+            res = []
             if len(res) == 0:
                 # 没有结果 直接推理拿结果 并保存
                 keypoint_infer_result = self.infer_keypoint_result(sketch)

app/service/prompt_generation/chatgpt_for_translation.py

@@ -90,7 +90,7 @@ def get_response(messages):
 
 def get_translation_from_llama3(text):
     start_time = time.time()
-    url = "http://10.1.1.240:11434/api/generate"
+    url = f"http://{settings.A6000_SERVICE_HOST}:11434/api/generate"
     # url = "http://10.1.1.240:1143/api/generate"
 
     # prompt = f"System: {prefix_for_llama}\nUser:[{text}]"
@@ -148,7 +148,7 @@ def get_translation_from_llama3(text):
 def get_prompt_from_image(image_path, text):
     start_time = time.time()
     # url = "http://localhost:11434/api/generate"
-    url = "http://10.1.1.243:11434/api/generate"
+    url = f"http://{settings.B_4_X_4090_SERVICE_HOST}:11434/api/generate"
 
     image_base64 = minio_util.minio_url_to_base64(image_path.img)
     # image_base64 = minio_url_to_base64(image_path)

docker-compose.yml

@@ -1,25 +1,14 @@
 services:
   aida_server:
+    container_name: "AiDA_${SERVE_ENV}_Server"
     build:
       context: .
       dockerfile: Dockerfile
     working_dir: /app
     volumes:
       - ./app:/app/app
-      - ./.env_prod:/app/.env
+      - ./.env:/app/.env
       - /etc/localtime:/etc/localtime:ro
       - ./seg_cache:/seg_cache
     ports:
-      - "10200:80"
+      - "${SERVE_PORT}:80"
-    depends_on:
-      - redis
-  redis:
-    image: redis
-    container_name: aida_redis
-    restart: always
-    ports:
-      - "6400:6379"
-    volumes:
-      - ./redis/data:/data
-      - ./redis/conf/redis.conf:/etc/redis/redis.conf
-    command: redis-server /etc/redis/redis.conf --appendonly yes