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Merge branch 'local'

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# Conflicts:
#	Dockerfile
#	app/core/config.py
This commit is contained in:
zhouchengrong
2024-04-22 14:32:18 +08:00
parent bf9c27c24e 25fdcdb6b0
commit cf8e5e0518
9 changed files with 78 additions and 97 deletions
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4
.gitignore vendored
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@@ -125,7 +125,9 @@ seg_result/
seg_result
*.png
uwsgi
#*.yaml
*.yaml
*.yml
Dockerfile
.conf
app/logs

22
Dockerfile
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@@ -1,22 +0,0 @@
FROM python:3.9
ENV TZ=Asia/Shanghai
RUN apt update
RUN apt install -y vim
RUN apt install -y libgl1-mesa-glx
COPY ./requirements.txt /requirements.txt
RUN pip install --upgrade pip
RUN pip install -r requirements.txt
RUN pip install gunicorn
RUN pip3 install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118
RUN #pip install mmcv==1.4.2 -f https://download.openmmlab.com/mmcv/dist/cu117/torch1.13/index.html
WORKDIR /app
COPY . .
ENV FLASK_APP=manage.py
LABEL maintainer="zchengrong@yeah.net" \
description="My Python 3.9 - trinity aida " \
version="1.0" \
name="trinity_aida"
CMD ["gunicorn", "-c", "gunicorn_config.py", "app.main:app" , "-e", "SR_RABBITMQ_QUEUES=SuperResolution" ,"-e", "GI_RABBITMQ_QUEUES=GenerateImage"]

4
app/core/config.py
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@@ -27,9 +27,9 @@ else:
LOGS_PATH = "app/logs/"
CATEGORY_PATH = "app/service/attribute/config/descriptor/category/category_dis.csv"
RABBITMQ_ENV = "" # 生产环境
# RABBITMQ_ENV = "" # 生产环境
# RABBITMQ_ENV = "-dev" # 开发环境
# RABBITMQ_ENV = "-local" # 本地测试环境
RABBITMQ_ENV = "-local" # 本地测试环境
settings = Settings()

3
app/service/attribute/service_att_recognition.py
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@@ -30,9 +30,6 @@ class AttributeRecognition:
self.const = const
self.triton_client = httpclient.InferenceServerClient(url=f"{ATT_TRITON_URL}")
def __del__(self):
self.triton_client.close()
def get_result(self):
for sketch in self.request_data:
if sketch['category'] == "Tops" or sketch['category'] == "Blouse":

122
app/service/generate_image/service.py
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@@ -10,7 +10,10 @@
import json
import logging
import time
from io import BytesIO
import cv2
import minio
import redis
import tritonclient.grpc as grpcclient
import numpy as np
@@ -20,7 +23,6 @@ from tritonclient.utils import np_to_triton_dtype
from app.core.config import *
from app.schemas.generate_image import GenerateImageModel
from app.service.generate_image.utils.upload_sd_image import upload_png_sd
from app.service.utils.generate_uuid import generate_uuid
logger = logging.getLogger()
@@ -32,40 +34,52 @@ class GenerateImage:
self.redis_client = redis.StrictRedis(host=REDIS_HOST, port=REDIS_PORT, db=REDIS_DB, decode_responses=True)
self.connection = pika.BlockingConnection(pika.ConnectionParameters(**RABBITMQ_PARAMS))
self.channel = self.connection.channel()
if request_data.mode == "txt2img":
self.image = np.random.randint(0, 256, (1024, 1024, 3), dtype=np.uint8)
if request_data.mode == "img2img":
self.image = self.get_image(request_data.image_url)
self.prompt = request_data.prompt
else:
self.image = request_data.image
self.image = np.random.randint(0, 256, (1024, 1024, 3), dtype=np.uint8)
self.prompt = request_data.prompt
self.tasks_id = request_data.tasks_id
self.user_id = self.tasks_id[self.tasks_id.rfind('-') + 1:]
self.prompt = request_data.prompt
self.mode = request_data.mode
self.batch_size = 1
self.category = request_data.category
self.index = 0
self.generate_data = {'tasks_id': self.tasks_id, 'status': 'PENDING', 'message': "pending", 'data': ''}
self.redis_client.set(self.tasks_id, json.dumps(self.generate_data))
self.redis_client.expire(self.tasks_id, 600)
def __del__(self):
self.redis_client.close()
self.grpc_client.close()
self.connection.close()
def __call__(self, *args, **kwargs):
self.generate_data = json.dumps({'status': 'PENDING', 'message': "pending", 'data': ''})
self.redis_client.set(self.tasks_id, self.generate_data)
def get_image(self, image_url):
# Get data of an object.
# Read data from response.
try:
response = self.minio_client.get_object(image_url.split('/')[0], image_url[image_url.find('/') + 1:])
image_file = BytesIO(response.data)
image_array = np.asarray(bytearray(image_file.read()), dtype=np.uint8)
image_cv2 = cv2.imdecode(image_array, cv2.IMREAD_COLOR)
except minio.error.S3Error:
image_cv2 = np.random.randint(0, 256, (1024, 1024, 3), dtype=np.uint8)
return image_cv2
def callback(self, result, error):
if error:
generate_data = json.dumps({'status': 'FAILURE', 'message': f"{error}", 'data': f"{error}"})
self.redis_client.set(self.tasks_id, generate_data)
self.generate_data['status'] = "FAILURE"
self.generate_data['message'] = str(error)
self.generate_data['data'] = str(error)
self.redis_client.set(self.tasks_id, json.dumps(self.generate_data))
else:
image_result = result.as_numpy("generated_image")[0]
image_url = upload_png_sd(image_result, user_id=self.user_id, category=f"{self.category}", object_name=f"{self.tasks_id}.png")
generate_data = json.dumps({'status': 'SUCCESS', 'message': 'success', 'data': f'{image_url}'})
self.redis_client.set(self.tasks_id, generate_data)
self.generate_data['status'] = "SUCCESS"
self.generate_data['message'] = "success"
self.generate_data['data'] = str(image_url)
self.redis_client.set(self.tasks_id, json.dumps(self.generate_data))
def read_tasks_status(self):
status_data = json.loads(self.redis_client.get(self.tasks_id))
return status_data
status_data = self.redis_client.get(self.tasks_id)
return json.loads(status_data), status_data
def infer(self, inputs):
return self.grpc_client.async_infer(
@@ -75,45 +89,53 @@ class GenerateImage:
)
def get_result(self):
prompts = [self.prompt] * self.batch_size
modes = [self.mode] * self.batch_size
images = [self.image.astype(np.float16)] * self.batch_size
try:
prompts = [self.prompt] * self.batch_size
modes = [self.mode] * self.batch_size
images = [self.image.astype(np.float16)] * self.batch_size
text_obj = np.array(prompts, dtype="object").reshape((-1, 1))
mode_obj = np.array(modes, dtype="object").reshape((-1, 1))
image_obj = np.array(images, dtype=np.float16).reshape((-1, 1024, 1024, 3))
text_obj = np.array(prompts, dtype="object").reshape((-1, 1))
mode_obj = np.array(modes, dtype="object").reshape((-1, 1))
image_obj = np.array(images, dtype=np.float16).reshape((-1, 1024, 1024, 3))
input_text = grpcclient.InferInput("prompt", text_obj.shape, np_to_triton_dtype(text_obj.dtype))
input_image = grpcclient.InferInput("input_image", image_obj.shape, "FP16")
input_mode = grpcclient.InferInput("mode", mode_obj.shape, np_to_triton_dtype(text_obj.dtype))
input_text = grpcclient.InferInput("prompt", text_obj.shape, np_to_triton_dtype(text_obj.dtype))
input_image = grpcclient.InferInput("input_image", image_obj.shape, "FP16")
input_mode = grpcclient.InferInput("mode", mode_obj.shape, np_to_triton_dtype(text_obj.dtype))
input_text.set_data_from_numpy(text_obj)
input_image.set_data_from_numpy(image_obj)
input_mode.set_data_from_numpy(mode_obj)
input_text.set_data_from_numpy(text_obj)
input_image.set_data_from_numpy(image_obj)
input_mode.set_data_from_numpy(mode_obj)
inputs = [input_text, input_image, input_mode]
ctx = self.infer(inputs)
time_out = 60
while time_out > 0:
generate_data = self.read_tasks_status()
if generate_data['status'] in ["REVOKED", "FAILURE"]:
ctx.cancel()
self.channel.basic_publish(exchange='', routing_key=GI_RABBITMQ_QUEUES, body=json.dumps(generate_data))
logger.info(f" [x] Sent {json.dumps(generate_data, indent=4)}")
break
elif generate_data['status'] == "SUCCESS":
self.channel.basic_publish(exchange='', routing_key=GI_RABBITMQ_QUEUES, body=json.dumps(generate_data))
logger.info(f" [x] Sent {json.dumps(generate_data, indent=4)}")
break
time_out -= 1
time.sleep(0.1)
return self.read_tasks_status()
inputs = [input_text, input_image, input_mode]
ctx = self.infer(inputs)
time_out = 60
generate_data = None
while time_out > 0:
generate_data, _ = self.read_tasks_status()
if generate_data['status'] in ["REVOKED", "FAILURE"]:
ctx.cancel()
break
elif generate_data['status'] == "SUCCESS":
break
time_out -= 1
time.sleep(0.1)
return generate_data
except Exception as e:
self.generate_data['status'] = "FAILURE"
self.generate_data['message'] = "failure"
self.generate_data['data'] = str(e)
self.redis_client.set(self.tasks_id, json.dumps(self.generate_data))
raise Exception(str(e))
finally:
dict_generate_data, str_generate_data = self.read_tasks_status()
self.channel.basic_publish(exchange='', routing_key=GI_RABBITMQ_QUEUES, body=str_generate_data)
logger.info(f" [x] Sent {json.dumps(dict_generate_data, indent=4)}")
def infer_cancel(tasks_id):
redis_client = redis.StrictRedis(host=REDIS_HOST, port=REDIS_PORT, db=REDIS_DB, decode_responses=True)
data = {'status': 'REVOKED', 'message': "revoked", 'data': 'revoked'}
generate_data = json.dumps({'status': 'REVOKED', 'message': "revoked", 'data': 'revoked'})
data = {'tasks_id': tasks_id, 'status': 'REVOKED', 'message': "revoked", 'data': 'revoked'}
generate_data = json.dumps(data)
redis_client.set(tasks_id, generate_data)
return data

5
app/service/generate_image/test.py
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@@ -64,11 +64,6 @@ class GenerateImage:
pass
def __del__(self):
self.redis_client.close()
self.triton_client.close()
self.connection.close()
@staticmethod
def image_grid(imgs, rows, cols):
assert len(imgs) == rows * cols

6
app/service/super_resolution/service.py
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@@ -26,14 +26,10 @@ class SuperResolution:
self.sr_xn = data.sr_xn
self.minio_client = Minio(MINIO_URL, access_key=MINIO_ACCESS, secret_key=MINIO_SECRET, secure=MINIO_SECURE)
self.redis_client.set(self.tasks_id, json.dumps({'status': 'PENDING', 'message': "pending", 'data': ''}))
self.redis_client.expire(self.tasks_id, 600)
self.connection = pika.BlockingConnection(pika.ConnectionParameters(**RABBITMQ_PARAMS))
self.channel = self.connection.channel()
def __del__(self):
self.redis_client.close()
self.triton_client.close()
self.connection.close()
# @RunTime
def read_image(self):
try:

9
docker-compose.yml
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@@ -1,9 +0,0 @@
version: "3"
services:
trinity_aida_local:
build: .
container_name: trinity_aida_local
volumes:
- ./trinity_client_aida:/trinity
ports:
- "10201:4562"

BIN
requirements.txt
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