Files
AiDA_Python/app/service/generate_image/service_pose_transform.py
zhouchengrong b4671a3793 feat(新功能): pose transform 接口
fix(修复bug):
docs(文档变更):
refactor(重构):
test(增加测试):
2025-03-17 11:14:54 +08:00

118 lines
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Python
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#!/usr/bin/env python
# -*- coding: UTF-8 -*-
"""
@Project trinity_client
@File service_pose_transform.py
@Author :周成融
@Date 2023/7/26 12:01:05
@detail
"""
import json
import logging
import cv2
import numpy as np
import redis
import tritonclient.grpc as grpcclient
from PIL import Image
from app.core.config import *
from app.schemas.pose_transform import PoseTransformModel
from app.service.generate_image.utils.upload_sd_image import upload_SDXL_image
from app.service.utils.oss_client import oss_get_image
logger = logging.getLogger()
class PoseTransformService:
def __init__(self, request_data):
if DEBUG is False:
self.connection = pika.BlockingConnection(pika.ConnectionParameters(**RABBITMQ_PARAMS))
self.channel = self.connection.channel()
self.grpc_client = grpcclient.InferenceServerClient(url=GRI_MODEL_URL)
self.redis_client = redis.StrictRedis(host=REDIS_HOST, port=REDIS_PORT, db=REDIS_DB, decode_responses=True)
self.category = "pose_transform"
self.batch_size = 1
self.seed = "1"
self.image_url = request_data.image_url
self.image = oss_get_image(bucket=self.image_url.split('/')[0], object_name=self.image_url[self.image_url.find('/') + 1:], data_type="cv2")
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': 'SUCCESS', 'message': "success", 'image_url': ''}
self.redis_client.set(self.tasks_id, json.dumps(self.gen_product_data))
self.redis_client.expire(self.tasks_id, 600)
def callback(self, result, error):
if error:
self.gen_product_data['status'] = "FAILURE"
self.gen_product_data['message'] = str(error)
self.redis_client.set(self.tasks_id, json.dumps(self.gen_product_data))
else:
image = result.as_numpy("generated_inpaint_image")
image_result = Image.fromarray(np.squeeze(image.astype(np.uint8)))
image_url = upload_SDXL_image(image_result, 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)
self.redis_client.set(self.tasks_id, json.dumps(self.gen_product_data))
def read_tasks_status(self):
status_data = self.redis_client.get(self.tasks_id)
return json.loads(status_data), status_data
def get_result(self):
try:
image = cv2.cvtColor(self.image, cv2.COLOR_BGR2RGB)
image = cv2.resize(image, (512, 768))
images = [image.astype(np.uint8)] * self.batch_size
image_obj = np.array(images, dtype=np.uint8).reshape((768, 512, 3))
input_image = grpcclient.InferInput("input_image", image_obj.shape, "UINT8")
input_image.set_data_from_numpy(image_obj)
inputs = [input_image]
# ctx = self.grpc_client.async_infer(model_name=GRI_MODEL_NAME_OVERALL, inputs=inputs, callback=self.callback)
# time_out = 600
# while time_out > 0:
# gen_product_data, _ = self.read_tasks_status()
# if gen_product_data['status'] in ["REVOKED", "FAILURE", "NO_FACE"]:
# ctx.cancel()
# break
# elif gen_product_data['status'] == "SUCCESS":
# break
# time_out -= 1
# time.sleep(0.1)
gen_product_data, _ = self.read_tasks_status()
return gen_product_data
except Exception as e:
self.gen_product_data['status'] = "FAILURE"
self.gen_product_data['message'] = str(e)
self.redis_client.set(self.tasks_id, json.dumps(self.gen_product_data))
raise Exception(str(e))
finally:
dict_gen_product_data, str_gen_product_data = self.read_tasks_status()
if DEBUG is False:
self.channel.basic_publish(exchange='', routing_key=GRI_RABBITMQ_QUEUES, body=str_gen_product_data)
logger.info(f" [x] Sent to {GRI_RABBITMQ_QUEUES} data@@@@ {json.dumps(dict_gen_product_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 = {'tasks_id': tasks_id, 'status': 'REVOKED', 'message': "revoked", 'data': 'revoked'}
gen_product_data = json.dumps(data)
redis_client.set(tasks_id, gen_product_data)
return data
if __name__ == '__main__':
rd = PoseTransformModel(
tasks_id="123-89",
image_url='aida-results/result_0000b606-1902-11ef-9424-0242ac180002.png',
pose_id="1"
)
server = PoseTransformService(rd)
print(server.get_result())