aidlab/AiDA_Python
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feat（新功能）:

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fix（修复bug）:
docs（文档变更）:
refactor（重构）:
test(增加测试): 旧版product 测试
This commit is contained in:
zhouchengrong
2025-02-04 09:54:38 +08:00
parent 48ae1cfb75
commit 092de8c43d
2 changed files with 10 additions and 4 deletions
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8
app/core/config.py
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@@ -129,8 +129,14 @@ GSL_MODEL_NAME = 'stable_diffusion_xl_transparent'
GEN_SINGLE_LOGO_RABBITMQ_QUEUES = os.getenv("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 = os.getenv("GEN_PRODUCT_IMAGE_RABBITMQ_QUEUES", f"ToProductImage{RABBITMQ_ENV}")
GPI_MODEL_NAME_OVERALL = 'sdxl_ensemble_all'
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

6
app/service/generate_image/service_generate_product_image.py
View File

@@ -226,7 +226,7 @@ class GenerateProductImage:
# self.connection = pika.BlockingConnection(pika.ConnectionParameters(**RABBITMQ_PARAMS))
# self.channel = self.connection.channel()
# self.minio_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE)
self.grpc_client = grpcclient.InferenceServerClient(url="10.1.1.243:18001")
self.grpc_client = grpcclient.InferenceServerClient(url=GPI_MODEL_URL)
self.redis_client = redis.StrictRedis(host=REDIS_HOST, port=REDIS_PORT, db=REDIS_DB, decode_responses=True)
self.category = "product_image"
self.image_strength = request_data.image_strength
@@ -293,9 +293,9 @@ class GenerateProductImage:
inputs = [input_text, input_image, input_image_strength]
if self.product_type == "single":
ctx = self.grpc_client.async_infer(model_name="stable_diffusion_1_5_cnet", inputs=inputs, callback=self.callback)
ctx = self.grpc_client.async_infer(model_name=GPI_MODEL_NAME_SINGLE, inputs=inputs, callback=self.callback)
else:
ctx = self.grpc_client.async_infer(model_name="diffusion_ensemble_all", inputs=inputs, callback=self.callback)
ctx = self.grpc_client.async_infer(model_name=GPI_MODEL_NAME_OVERALL, inputs=inputs, callback=self.callback)
time_out = 600
while time_out > 0: