aidlab/AiDA_Python
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Merge branch 'refs/heads/develop'

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zhouchengrong
2025-02-04 10:09:42 +08:00
parent 331a815a31 3a0c730e9c
commit 67bcefdc2b
2 changed files with 35 additions and 14 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

41
app/service/generate_image/service_generate_product_image.py
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@@ -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:
@@ -331,18 +331,33 @@ def infer_cancel(tasks_id):
def pre_processing_image(image_url):
image = oss_get_image(bucket=image_url.split('/')[0], object_name=image_url[image_url.find('/') + 1:], data_type="PIL")
# 调整图片高度为768像素，保持宽高比
width, height = image.size
new_height = 768
new_width = int(width * (new_height / height))
# 目标图片的尺寸
target_width = 512
target_height = 768
# 原始图片的尺寸
original_width, original_height = image.size
# 计算宽度和高度的缩放比例
width_ratio = target_width / original_width
height_ratio = target_height / original_height
# 选择较小的缩放比例，确保图片能完整放入目标图片中
scale_ratio = min(width_ratio, height_ratio)
# 计算调整后的尺寸
new_width = int(original_width * scale_ratio)
new_height = int(original_height * scale_ratio)
# 调整图片大小
resized_image = image.resize((new_width, new_height))
# 创建一个512x768的透明图片
result_image = Image.new("RGBA", (512, 768), (255, 255, 255, 255))
# 创建一个 512x768 的透明图片
result_image = Image.new("RGBA", (target_width, target_height), (255, 255, 255, 0))
# 计算需要粘贴的位置，使图片居中
x_offset = (512 - new_width) // 2
y_offset = 0
x_offset = (target_width - new_width) // 2
y_offset = (target_height - new_height) // 2
# 将调整大小后的图片粘贴到透明图片上
result_image.paste(resized_image, (x_offset, y_offset), mask=resized_image.split()[3])
@@ -371,8 +386,8 @@ if __name__ == '__main__':
tasks_id="123-89",
# prompt="",
image_strength=0.7,
prompt="The best quality, masterpiece, real image.,high quality clothing details,8K realistic,HDR",
image_url="aida-results/result_40c7924e-e220-11ef-8ea2-0242ac150003.png",
prompt=" The best quality, masterpiece, real image.Outwear,high quality clothing details,8K realistic,HDR",
image_url="aida-results/result_40b1a2fe-e220-11ef-9bfa-0242ac150003.png",
product_type="single"
)
server = GenerateProductImage(rd)