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feat 4090 triton server 测试

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fix
This commit is contained in:
zhouchengrong
2024-11-19 17:35:10 +08:00
parent 26be5279df
commit 754c6eff87
3 changed files with 36 additions and 31 deletions
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6
app/core/config.py
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@@ -117,10 +117,10 @@ GEN_SINGLE_LOGO_RABBITMQ_QUEUES = os.getenv("GEN_SINGLE_LOGO_RABBITMQ_QUEUES", f
# Generate Product service config
GPI_RABBITMQ_QUEUES = os.getenv("GEN_PRODUCT_IMAGE_RABBITMQ_QUEUES", f"ToProductImage{RABBITMQ_ENV}")
GPI_MODEL_NAME_OVERALL = 'diffusion_ensemble_all'
GPI_MODEL_NAME_SINGLE = 'stable_diffusion_1_5_cnet'
GPI_MODEL_NAME_OVERALL = 'stable_diffusion_xl_cnet'
GPI_MODEL_NAME_SINGLE = 'stable_diffusion_xl_cnet'
GPI_MODEL_URL = '10.1.1.240:10041'
GPI_MODEL_URL = '10.1.1.243:10051'
# Generate Single Logo service config
GRI_RABBITMQ_QUEUES = os.getenv("GEN_RELIGHT_IMAGE_RABBITMQ_QUEUES", f"Relight{RABBITMQ_ENV}")

59
app/service/generate_image/service_generate_product_image.py
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@@ -15,7 +15,7 @@ import cv2
import numpy as np
import redis
import tritonclient.grpc as grpcclient
from PIL import Image, ImageOps
from PIL import Image
from tritonclient.utils import np_to_triton_dtype
from app.core.config import *
@@ -41,7 +41,7 @@ class GenerateProductImage:
self.batch_size = 1
self.product_type = request_data.product_type
self.prompt = request_data.prompt
self.image, self.image_size = pre_processing_image(request_data.image_url)
self.image, self.image_size, self.left, self.top = pre_processing_image(request_data.image_url)
self.tasks_id = request_data.tasks_id
self.user_id = self.tasks_id[self.tasks_id.rfind('-') + 1:]
self.gen_product_data = {'tasks_id': self.tasks_id, 'status': 'PENDING', 'message': "pending", 'image_url': ''}
@@ -58,9 +58,10 @@ class GenerateProductImage:
if self.product_type == "single":
image = result.as_numpy("generated_cnet_image")
else:
image = result.as_numpy("generated_inpaint_image")
image = result.as_numpy("generated_cnet_image")
image_result = Image.fromarray(np.squeeze(image.astype(np.uint8))).resize(self.image_size)
image_url = upload_SDXL_image(image_result, user_id=self.user_id, category=f"{self.category}", file_name=f"{self.tasks_id}.png")
cropped_image = post_processing_image(image_result, self.left, self.top)
image_url = upload_SDXL_image(cropped_image, user_id=self.user_id, category=f"{self.category}", file_name=f"{self.tasks_id}.png")
self.gen_product_data['status'] = "SUCCESS"
self.gen_product_data['message'] = "success"
self.gen_product_data['image_url'] = str(image_url)
@@ -74,7 +75,7 @@ class GenerateProductImage:
try:
prompts = [self.prompt] * self.batch_size
self.image = cv2.cvtColor(self.image, cv2.COLOR_BGR2RGB)
self.image = cv2.resize(self.image, (512, 768))
self.image = cv2.resize(self.image, (1024, 1024))
images = [self.image.astype(np.uint8)] * self.batch_size
if self.product_type == "single":
@@ -82,9 +83,9 @@ class GenerateProductImage:
image_obj = np.array(images, dtype=np.uint8).reshape((-1, 768, 512, 3))
image_strength_obj = np.array(self.image_strength, dtype=np.float32).reshape(-1, 1)
else:
text_obj = np.array(prompts, dtype="object").reshape(1)
image_obj = np.array(images, dtype=np.uint8).reshape((768, 512, 3))
image_strength_obj = np.array(self.image_strength, dtype=np.float32).reshape((1))
text_obj = np.array(prompts, dtype="object").reshape((-1, 1))
image_obj = np.array(images, dtype=np.uint8).reshape((-1, 1024, 1024, 3))
image_strength_obj = np.array(self.image_strength, dtype=np.float32).reshape((-1, 1))
# 假设 prompts、images 和 self.image_strength 已经定义
@@ -136,22 +137,13 @@ 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")
# resize 原图至1024*1024
image = image.resize((int(1024 / image.height * image.width), 1024))
# 原始图片的尺寸
width, height = image.size
# 计算长宽比为 3:2 的新尺寸
desired_ratio = 2 / 3
current_ratio = width / height
if current_ratio > desired_ratio:
# 原始图片更宽，需要在上下添加 padding
new_width = width
new_height = int(width / desired_ratio)
else:
# 原始图片更高或者长宽比已经为 3:2
new_height = height
new_width = int(height * desired_ratio)
new_height, new_width = 1024, 1024
# 创建一个新的画布，大小为添加 padding 后的尺寸，并设置为白色背景
pad_image = Image.new('RGBA', (new_width, new_height), (0, 0, 0, 0))
@@ -160,9 +152,9 @@ def pre_processing_image(image_url):
top = (new_height - height) // 2
pad_image.paste(image, (left, top))
# 将画布 resize 成宽度 500，长度 750
resized_image = pad_image.resize((500, 750))
image_size = (512, 768)
# 将画布 resize 成宽度 1024，长度 1024
resized_image = pad_image.resize((1024, 1024))
image_size = (1024, 1024)
if resized_image.mode in ('RGBA', 'LA') or (resized_image.mode == 'P' and 'transparency' in resized_image.info):
# 创建白色背景
@@ -171,15 +163,28 @@ def pre_processing_image(image_url):
background.paste(resized_image, mask=resized_image.split()[3])
image = np.array(background)
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
return image, image_size
return image, image_size, left, top
def post_processing_image(image, left, top):
width, height = image.size
# 计算裁剪后的宽度和坐标
new_width = width - 2 * left
right = left + new_width
# 进行裁剪操作
cropped_image = image.crop((left, 0, right, height))
# 保存裁剪后的图像，将此处的 'cropped_image.jpg' 替换为你想要保存的文件名
return cropped_image
if __name__ == '__main__':
rd = GenerateProductImageModel(
tasks_id="123-89",
# prompt="",
image_strength=0.9,
prompt=" the best quality, masterpiece. detailed, high-res, simple background, studio photography, extremely detailed, updo, detailed face, face, close-up, HDR, UHD, 8K realistic, Highly detailed, simple background, Studio lighting",
image_strength=0.65,
prompt="The best quality, masterpiece, real image. A handsome man wearing blouse, outwear, trousers, 8K realistic, HUD",
image_url="aida-results/result_00097282-ebb2-11ee-a822-b48351119060.png",
product_type="overall"
)

2
app/service/utils/new_oss_client.py
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@@ -82,7 +82,7 @@ if __name__ == '__main__':
# url = "aida-users/89/sketchboard/female/Dress/e6724ab7-8d3f-4677-abe0-c3e42ab7af85.jpeg"
# url = "aida-users/87/print/956614a2-7e75-4fbe-9ed0-c1831e37a2c9-4-87.png"
# url = "aida-users/89/single_logo/123-89.png"
url ="aida-results/result_91559b60-a61c-11ef-af8e-0242ac150002.png"
url ="aida-results/result_27915298-a656-11ef-b4f3-0242ac150002.png"
# url = "aida-collection-element/12148/Sketchboard/95ea577b-305b-4a62-b30a-39c0dd3ddb3f.png"
read_type = "2"