feat: 印花逻辑修改 默认不处理除overall以外所有印花类型

fix:

app/core/config.backup.py

@@ -1,235 +0,0 @@
-import os
-
-import pika
-from dotenv import load_dotenv
-from pydantic import BaseSettings
-
-BASE_DIR = os.path.abspath(os.path.join(os.path.dirname(__file__), '../../'))
-load_dotenv(os.path.join(BASE_DIR, '.env'))
-
-
-class Settings(BaseSettings):
-    PROJECT_NAME: str = 'FASTAPI BASE'
-    SECRET_KEY: str = ''
-    API_PREFIX: str = ''
-    BACKEND_CORS_ORIGINS: list[str] = ['*']
-    DATABASE_URL: str = ''
-    ACCESS_TOKEN_EXPIRE_SECONDS: int = 60 * 60 * 24 * 7  # Token expired after 7 days
-    SECURITY_ALGORITHM: str = 'HS256'
-    LOGGING_CONFIG_FILE: str = os.path.join(BASE_DIR, 'logging_env.py')
-
-
-OSS = "minio"
-DEBUG = False
-if DEBUG:
-    LOGS_PATH = "logs/"
-    CATEGORY_PATH = "service/attribute/config/descriptor/category/category_dis.csv"
-    SEG_CACHE_PATH = "../seg_cache/"
-    POSE_TRANSFORM_VIDEO_PATH = "../pose_transform_video/"
-    RECOMMEND_PATH_PREFIX = "service/recommend/"
-    CHROMADB_PATH = "./chromadb/"
-else:
-    LOGS_PATH = "app/logs/"
-    CATEGORY_PATH = "app/service/attribute/config/descriptor/category/category_dis.csv"
-    SEG_CACHE_PATH = "/seg_cache/"
-    POSE_TRANSFORM_VIDEO_PATH = "/pose_transform_video/"
-    RECOMMEND_PATH_PREFIX = "app/service/recommend/"
-    CHROMADB_PATH = "/chromadb/"
-
-# RABBITMQ_ENV = ""  # 生产环境
-RABBITMQ_ENV = os.getenv("RABBITMQ_ENV", "-dev")
-# RABBITMQ_ENV = "-local"  # 本地测试环境
-
-if RABBITMQ_ENV == "-dev":
-    JAVA_STREAM_API_URL = f"https://develop.api.aida.com.hk/api/third/party/receiveDesignResults"
-elif RABBITMQ_ENV == "-prod":
-    JAVA_STREAM_API_URL = f"https://api.aida.com.hk/api/third/party/receiveDesignResults"
-
-settings = Settings()
-
-# minio 配置
-MINIO_URL = "www.minio-api.aida.com.hk"
-MINIO_ACCESS = 'vXKFLSJkYeEq2DrSZvkB'
-MINIO_SECRET = 'uKTZT3x7C43WvPN9QTc99DiRkwddWZrG9Uh3JVlR'
-MINIO_SECURE = True
-
-# S3 配置
-S3_ACCESS_KEY = "AKIAVD3OJIMF6UJFLSHZ"
-S3_AWS_SECRET_ACCESS_KEY = "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"
-S3_REGION_NAME = "ap-east-1"
-
-# redis 配置
-REDIS_HOST = "10.1.1.240"
-REDIS_PORT = "6379"
-REDIS_DB = "2"
-
-# rabbitmq config
-RABBITMQ_PARAMS = {
-    "host": "18.167.251.121",
-    "port": 5672,
-    "credentials": pika.credentials.PlainCredentials(username='rabbit', password='123456'),
-    "virtual_host": "/"
-}
-
-# milvus 配置
-MILVUS_URL = "http://10.1.1.240:19530"
-MILVUS_TOKEN = "root:Milvus"
-MILVUS_ALIAS = "default"
-MILVUS_TABLE_KEYPOINT = "keypoint_cache_2"
-MILVUS_TABLE_SEG = "seg_cache"
-
-# Mysql 配置
-DB_HOST = '18.167.251.121'  # 数据库主机地址
-# DB_PORT = int( 33006)
-DB_PORT = 33008  # 数据库端口
-DB_USERNAME = 'aida_con_python'  # 数据库用户名
-DB_PASSWORD = '123456'  # 数据库密码
-DB_NAME = 'aida'  # 数据库库名
-
-# openai
-os.environ['SERPAPI_API_KEY'] = "a793513017b0718db7966207c31703d280d12435c982f1e67bbcbffa52e7632c"
-OPENAI_STREAM = True
-BUFFER_THRESHOLD = 6  # must be even number
-SINGLE_TOKEN_THRESHOLD = 200
-TOKEN_THRESHOLD = 600
-OPENAI_TEMPERATURE = 0
-
-# OPENAI_API_KEY =  "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"
-OPENAI_API_KEY = "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"
-OPENAI_MODEL = "gpt-3.5-turbo-0613"
-OPENAI_MODEL_LIST = {"gpt-3.5-turbo-0613",
-                     "gpt-3.5-turbo-16k-0613",
-                     "gpt-4-0314",
-                     "gpt-4-32k-0314",
-                     "gpt-4-0613",
-                     "gpt-4-32k-0613", }
-
-# SR service config
-SR_MODEL_NAME = "super_resolution"
-SR_TRITON_URL = "10.1.1.240:10031"
-SR_MINIO_BUCKET = "aida-users"
-SR_RABBITMQ_QUEUES = f"SuperResolution{RABBITMQ_ENV}"
-
-# GenerateImage service config
-FAST_GI_MODEL_URL = '10.1.1.243:10011'
-FAST_GI_MODEL_NAME = 'stable_diffusion_xl'
-
-GI_MODEL_URL = '10.1.1.240:10061'
-GI_MODEL_NAME = 'flux'
-
-GMV_MODEL_URL = '10.1.1.243:10081'
-GMV_MODEL_NAME = 'multi_view'
-
-GMV_RABBITMQ_QUEUES = f"GenerateMultiView{RABBITMQ_ENV}"
-
-GI_MINIO_BUCKET = "aida-users"
-GI_RABBITMQ_QUEUES = f"GenerateImage{RABBITMQ_ENV}"
-GI_SYS_IMAGE_URL = "aida-sys-image/generate_image/white_image.jpg"
-
-# SLOGAN service config
-SLOGAN_RABBITMQ_QUEUES = f"Slogan{RABBITMQ_ENV}"
-
-# Generate Single Logo service config
-GSL_MODEL_URL = '10.1.1.243:10041'
-GSL_MINIO_BUCKET = "aida-users"
-GSL_MODEL_NAME = 'stable_diffusion_xl_transparent'
-GEN_SINGLE_LOGO_RABBITMQ_QUEUES = f"GenSingleLogo{RABBITMQ_ENV}"
-
-# Generate Product service config
-# GPI_RABBITMQ_QUEUES = os.getenv("GEN_PRODUCT_IMAGE_RABBITMQ_QUEUES", f"ToProductImage{RABBITMQ_ENV}")
-# GPI_MODEL_NAME_OVERALL = 'sdxl_ensemble_all'
-# GPI_MODEL_URL = '10.1.1.243:10051'
-
-# Generate Product service config 旧版product img 模型
-GPI_RABBITMQ_QUEUES = f"ToProductImage{RABBITMQ_ENV}"
-BATCH_GPI_RABBITMQ_QUEUES = f"BatchToProductImage{RABBITMQ_ENV}"
-GPI_MODEL_NAME_OVERALL = 'diffusion_ensemble_all'
-GPI_MODEL_NAME_SINGLE = 'stable_diffusion_1_5_cnet'
-GPI_MODEL_URL = '10.1.1.243:10051'
-
-# Generate Single Logo service config
-GRI_RABBITMQ_QUEUES = f"Relight{RABBITMQ_ENV}"
-BATCH_GRI_RABBITMQ_QUEUES = f"BatchRelight{RABBITMQ_ENV}"
-GRI_MODEL_NAME_OVERALL = 'diffusion_relight_ensemble'
-GRI_MODEL_NAME_SINGLE = 'stable_diffusion_1_5_relight'
-GRI_MODEL_URL = '10.1.1.240:10051'
-
-# Pose Transform service config
-
-PS_RABBITMQ_QUEUES = f"PoseTransform{RABBITMQ_ENV}"
-BATCH_PS_RABBITMQ_QUEUES = f"BatchPoseTransform{RABBITMQ_ENV}"
-PT_MODEL_URL = '10.1.1.243:10061'
-
-# SEG service config
-SEGMENTATION = {
-    "new_model_name": "seg_knet",
-    "name": "seg_ocrnet_hr18",
-    "input": "seg_input__0",
-    "output": "seg_output__0",
-}
-# ollama config
-OLLAMA_URL = "http://10.1.1.240:11434/api/embeddings"
-
-# design batch
-BATCH_DESIGN_RABBITMQ_QUEUES = f"DesignBatch{RABBITMQ_ENV}"
-
-# DESIGN config
-DESIGN_MODEL_URL = '10.1.1.240:10000'
-AIDA_CLOTHING = "aida-clothing"
-KEYPOINT_RESULT_TABLE_FIELD_SET = ('neckline_left', 'neckline_right', 'shoulder_left', 'shoulder_right', 'armpit_left', 'armpit_right',
-                                   'cuff_left_in', 'cuff_left_out', 'cuff_right_in', 'cuff_right_out', 'waistband_left', 'waistband_right')
-
-# DESIGN 预处理
-IF_DEBUG_SHOW = False
-
-# 优先级
-PRIORITY_DICT = {
-    'earring_front': 99,
-    'bag_front': 98,
-    'hairstyle_front': 97,
-    'outwear_front': 20,
-    'tops_front': 19,
-    'dress_front': 18,
-    'blouse_front': 17,
-    'skirt_front': 16,
-    'trousers_front': 15,
-    'bottoms_front': 14,
-    'shoes_right': 1,
-    'shoes_left': 1,
-    'body': 0,
-    'bottoms_back': -14,
-    'trousers_back': -15,
-    'skirt_back': -16,
-    'blouse_back': -17,
-    'dress_back': -18,
-    'tops_back': -19,
-    'outwear_back': -20,
-    'hairstyle_back': -97,
-    'bag_back': -98,
-    'earring_back': -99,
-}
-
-QWEN_API_KEY = "sk-f31c29e61ac2498ba5e307aaa6dc10e0"
-
-DB_CONFIG = {
-    "host": "18.167.251.121",
-    "port": 3306,
-    "user": "root",
-    "password": "QWa998345",
-    "database": "aida",
-    "charset": "utf8mb4"
-}
-
-TABLE_CATEGORIES = {
-    "female_dress": "female/dress",
-    "female_outwear": "female/outwear",
-    "female_trousers": "female/trousers",
-    "female_skirt": "female/skirt",
-    "female_blouse": "female/blouse",
-    "male_tops": "male/tops",
-    "male_bottoms": "male/bottoms",
-    "male_outwear": "male/outwear"
-}
-
-# --- ComfyUI 配置信息 ---
-COMFYUI_SERVER_ADDRESS = "10.1.2.227:8080"  # 替换为您的 ComfyUI 服务器地址

app/service/design_fast/pipeline/no_seg_print_painting.py

@@ -12,9 +12,13 @@ class NoSegPrintPainting:
         self.minio_client = minio_client
 
     def __call__(self, result):
-        single_print = result['print']['single']
+        # single_print = [result['print']['single']]
         overall_print = result['print']['overall']
-        element_print = result['print']['element']
+        # element_print = result['print']['element'
+
+        single_print = None
+        element_print = None
+
         result['single_image'] = None
         result['print_image'] = None
 
@@ -25,7 +29,7 @@ class NoSegPrintPainting:
             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']
 
-        if single_print['print_path_list']:
+        if single_print:
             print_background = np.zeros((result['pattern_image'].shape[0], result['pattern_image'].shape[1], 3), dtype=np.uint8)
             mask_background = np.zeros((result['pattern_image'].shape[0], result['pattern_image'].shape[1], 3), dtype=np.uint8)
             for i in range(len(single_print['print_path_list'])):
@@ -65,7 +69,7 @@ class NoSegPrintPainting:
                 single_image = cv2.add(tmp1, tmp2)
                 result['no_seg_sketch_print'] = single_image
 
-        if element_print['element_path_list']:
+        if element_print:
             print_background = np.zeros((result['final_image'].shape[0], result['final_image'].shape[1], 3), dtype=np.uint8)
             mask_background = np.zeros((result['final_image'].shape[0], result['final_image'].shape[1], 3), dtype=np.uint8)
             for i in range(len(element_print['element_path_list'])):

app/service/design_fast/pipeline/print_painting.py

@@ -12,10 +12,14 @@ class PrintPainting:
         self.minio_client = minio_client
 
     def __call__(self, result):
-        single_print = result['print']['single']
+        # single_print = result['print']['single']
         overall_print = result['print']['overall']
-        element_print = result['print']['element']
+        # element_print = result['print']['element']
-        partial_path = result['print']['partial'] if 'partial' in result['print'] else None
+        # partial_path = result['print']['partial'] if 'partial' in result['print'] else None
+
+        single_print = None
+        element_print = None
+        partial_path = None
         result['single_image'] = None
         result['print_image'] = None
         # TODO 给result['pattern_image'] resize 到resize_scale的大小
@@ -43,7 +47,7 @@ class PrintPainting:
             result['print_image'] = self.printpaint(result, painting_dict, print_=True)
             result['single_image'] = result['final_image'] = result['pattern_image'] = result['print_image']
 
-        if single_print['print_path_list']:
+        if single_print:
             # 2025-9-19 印花调整 印花坐标按照sketch的缩放比调整
             sketch_resize_scale = result['resize_scale']
             print_background = np.zeros((result['pattern_image'].shape[0], result['pattern_image'].shape[1], 3), dtype=np.uint8)
@@ -84,7 +88,7 @@ class PrintPainting:
                 tmp2 = (result['final_image'] * (temp_fg / 255)).astype(np.uint8)
                 result['single_image'] = cv2.add(tmp1, tmp2)
 
-        if element_print['element_path_list']:
+        if element_print:
             # 2025-9-19 印花调整 印花坐标按照sketch的缩放比调整
             sketch_resize_scale = result['resize_scale']
             print_background = np.zeros((result['final_image'].shape[0], result['final_image'].shape[1], 3), dtype=np.uint8)