[Serving] Simple serving YOLOv5 and PP-OCRv3 example, add uvicorn to fastdeploy tools (#986)

* ppocrv3 simple serving

* add uvicorn to fd tools

* update ppdet simple serving readme

* yolov5 simple serving

* not import simple serving by default

* remove config from envs

* update comment

examples/vision/detection/paddledetection/python/serving/README_CN.md

@@ -17,16 +17,9 @@ cd FastDeploy/examples/vision/detection/paddledetection/python/serving
 wget https://bj.bcebos.com/paddlehub/fastdeploy/ppyoloe_crn_l_300e_coco.tgz
 tar xvf ppyoloe_crn_l_300e_coco.tgz
 
-# 安装uvicorn
-pip install uvicorn
-
-# 启动服务，可选择是否使用GPU和TensorRT，可根据uvicorn --help配置IP、端口号等
-# CPU
-MODEL_DIR=ppyoloe_crn_l_300e_coco DEVICE=cpu uvicorn server:app
-# GPU
-MODEL_DIR=ppyoloe_crn_l_300e_coco DEVICE=gpu uvicorn server:app
-# GPU上使用TensorRT （注意：TensorRT推理第一次运行，有序列化模型的操作，有一定耗时，需要耐心等待）
-MODEL_DIR=ppyoloe_crn_l_300e_coco DEVICE=gpu USE_TRT=true uvicorn server:app
+# 启动服务，可修改server.py中的配置项来指定硬件、后端等
+# 可通过--host、--port指定IP和端口号
+fastdeploy simple_serving --app server:app
 ```
 
 客户端：

examples/vision/detection/paddledetection/python/serving/README_EN.md

@@ -17,17 +17,9 @@ cd FastDeploy/examples/vision/detection/paddledetection/python/serving
 wget https://bj.bcebos.com/paddlehub/fastdeploy/ppyoloe_crn_l_300e_coco.tgz
 tar xvf ppyoloe_crn_l_300e_coco.tgz
 
-# Install uvicorn
-pip install uvicorn
-
-# Launch server, it's configurable to use GPU and TensorRT,
-# and run 'uvicorn --help' to check how to specify IP and port, etc.
-# CPU
-MODEL_DIR=ppyoloe_crn_l_300e_coco DEVICE=cpu uvicorn server:app
-# GPU
-MODEL_DIR=ppyoloe_crn_l_300e_coco DEVICE=gpu uvicorn server:app
-# GPU and TensorRT
-MODEL_DIR=ppyoloe_crn_l_300e_coco DEVICE=gpu USE_TRT=true uvicorn server:app
+# Launch server, change the configurations in server.py to select hardware, backend, etc.
+# and use --host, --port to specify IP and port
+fastdeploy simple_serving --app server:app
 ```
 
 Client:

examples/vision/detection/paddledetection/python/serving/client.py

@@ -1,20 +1,15 @@
 import requests
 import json
 import cv2
-import base64
 import fastdeploy as fd
+from fastdeploy.serving.utils import cv2_to_base64
 
 if __name__ == '__main__':
     url = "http://127.0.0.1:8000/fd/ppyoloe"
     headers = {"Content-Type": "application/json"}
 
     im = cv2.imread("000000014439.jpg")
-    data = {
-        "data": {
-            "image": fd.serving.utils.cv2_to_base64(im)
-        },
-        "parameters": {}
-    }
+    data = {"data": {"image": cv2_to_base64(im)}, "parameters": {}}
 
     resp = requests.post(url=url, headers=headers, data=json.dumps(data))
     if resp.status_code == 200:

examples/vision/detection/paddledetection/python/serving/server.py

@@ -1,18 +1,16 @@
 import fastdeploy as fd
+from fastdeploy.serving.server import SimpleServer
 import os
 import logging
 
 logging.getLogger().setLevel(logging.INFO)
 
-# Get arguments from envrionment variables
-model_dir = os.environ.get('MODEL_DIR')
-device = os.environ.get('DEVICE', 'cpu')
-use_trt = os.environ.get('USE_TRT', False)
-
-# Prepare model, download from hub or use local dir
-if model_dir is None:
-    model_dir = fd.download_model(name='ppyoloe_crn_l_300e_coco')
+# Configurations
+model_dir = 'ppyoloe_crn_l_300e_coco'
+device = 'cpu'
+use_trt = False
 
+# Prepare model
 model_file = os.path.join(model_dir, "model.pdmodel")
 params_file = os.path.join(model_dir, "model.pdiparams")
 config_file = os.path.join(model_dir, "infer_cfg.yml")
@@ -33,7 +31,7 @@ model_instance = fd.vision.detection.PPYOLOE(
     runtime_option=option)
 
 # Create server, setup REST API
-app = fd.serving.SimpleServer()
+app = SimpleServer()
 app.register(
     task_name="fd/ppyoloe",
     model_handler=fd.serving.handler.VisionModelHandler,