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):

app/api/api_pose_transform.py

@@ -0,0 +1,49 @@
+import json
+import logging
+
+from fastapi import APIRouter, BackgroundTasks, HTTPException
+
+from app.schemas.pose_transform import PoseTransformModel
+from app.schemas.response_template import ResponseModel
+from app.service.generate_image.service_pose_transform import PoseTransformService, infer_cancel as pose_transform_infer_cancel
+
+router = APIRouter()
+logger = logging.getLogger()
+
+
+@router.post("/pose_transform")
+def pose_transform(request_item: PoseTransformModel, background_tasks: BackgroundTasks):
+    """
+        创建一个具有以下参数的请求体:
+        - **tasks_id**: 任务id 用于取消生成任务和获取生成结果
+        - **image_url**: 被生成图片的S3或minio url地址
+        - **pose_id**: 1
+
+
+        示例参数：
+        {
+          "tasks_id": "123-89",
+          "image_url": "aida-results/result_0000b606-1902-11ef-9424-0242ac180002.png",
+          "pose_id": "1"
+        }
+    """
+    try:
+        logger.info(f"pose_transform request item is : @@@@@@:{json.dumps(request_item.dict())}")
+        service = PoseTransformService(request_item)
+        background_tasks.add_task(service.get_result)
+    except Exception as e:
+        logger.warning(f"pose_transform Run Exception @@@@@@:{e}")
+        raise HTTPException(status_code=404, detail=str(e))
+    return ResponseModel()
+
+
+@router.get("/pose_transform_cancel/{tasks_id}")
+def pose_transform_cancel(tasks_id: str):
+    try:
+        logger.info(f"pose_transform_cancel request item is : @@@@@@:{tasks_id}")
+        data = pose_transform_infer_cancel(tasks_id)
+        logger.info(f"pose_transform_cancel response @@@@@@:{data}")
+    except Exception as e:
+        logger.warning(f"pose_transform_cancel Run Exception @@@@@@:{e}")
+        raise HTTPException(status_code=404, detail=str(e))
+    return ResponseModel(data=data['data'])

app/api/api_route.py

@@ -1,5 +1,6 @@
 from fastapi import APIRouter
 
+from app.api import api_agent_generate_image
 from app.api import api_attribute_retrieve, api_query_image
 from app.api import api_brand_dna
 from app.api import api_brighten
@@ -9,11 +10,9 @@ from app.api import api_design_pre_processing
 from app.api import api_generate_image
 from app.api import api_image2sketch
 from app.api import api_mannequins_edit
+from app.api import api_pose_transform
 from app.api import api_prompt_generation
-from app.api import api_recommendation
 from app.api import api_super_resolution
-from app.api import api_agent_generate_image
-
 from app.api import api_test
 
 router = APIRouter()
@@ -33,3 +32,4 @@ router.include_router(api_brand_dna.router, tags=['api_brand_dna'], prefix="/api
 # router.include_router(api_recommendation.router, tags=['api_recommendation'], prefix="/api")
 router.include_router(api_mannequins_edit.router, tags=['api_mannequins_edit'], prefix="/api")
 router.include_router(api_agent_generate_image.router, tags=['api_agent_generate_image'], prefix="/api")
+router.include_router(api_pose_transform.router, tags=['api_pose_transform'], prefix="/api")

app/schemas/pose_transform.py

@@ -0,0 +1,7 @@
+from pydantic import BaseModel
+
+
+class PoseTransformModel(BaseModel):
+    image_url: str
+    tasks_id: str
+    pose_id: str

app/service/generate_image/service_pose_transform.py

@@ -0,0 +1,117 @@
+#!/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())