Python wrapper class for OpenVINO Model Server. User can submit inference request to OVMS with just a few lines of code

Related tags

Deep Learning python deep-learning grpc intel inference tensorflow-serving grpc-client model-serving openvino triton-inference-server openvino-docker openvino-model-server
Overview

OpenVINO Model Server wrapper API for Python

Description

This project provides a Python wrapper class for OpenVINO Model Server.
User can submit DL inference request to OVMS with just a few lines of code.

Sample code

from ovms_wrapper.ovms_wrapper import OpenVINO_Model_Server

import cv2
import numpy as np

ovms = OpenVINO_Model_Server()
ovms.connect('127.0.0.1', 9000)
#print(ovms.get_model_status('resnet_50'))
model = ovms.open_model('resnet_50')
print(model.inputs, model.outputs)

image_file  = 'ovms/lib/python3.8/site-packages/skimage/data/rocket.jpg'
img = cv2.imread(image_file)                # Read an image
res = model.single_image_infer(img)         # Infer
result = res[model.outputs[0]['name']]

# display result
nu = np.array(result)
ma = np.argmax(nu)
print("Result:", ma)

How to setup OpenVINO Model Server (Ubuntu)

Note: OVMS can run on Windows too. Please refer to the official OVMS document for details.

sudo apt update && sudo apt install -y python3-venv
python -m pip install tensorflow tensorflow-serving-api
  • Create Python virtual env, install OpenVINO, and prepare an IR model
    Installing OpenVINO just for downloading a DL model and converting it into OpenVINO IR model. This is not required if you already have the IR models.
python3 -m venv ovms
. ovms/bin/activate
python -m pip install openvino-dev
omz_downloader --name resnet-50-tf
omz_converter --name resnet-50-tf --precisions FP16
deactivate
  • Start OpenVINO Model Server as Docker container
docker run -d --rm \
  -v $PWD/public/resnet-50-tf/FP16:/models/resnet50/1 \
  -p 9000:9000 \
  openvino/model_server:latest \
  --model_path /models/resnet50 \
  --model_name resnet_50 \
  --port 9000

OVMS will start serving the Resnet-50 model as model-name='resnet_50', model-version=1, and gRPC-port=9000.

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Comments
  • not issue, BKM request for utilization

    not issue, BKM request for utilization

    Hi yas-sim, thanks a lot for sharing wonderful code. I'm not good in model server, would you kindly let me know what is the next step for this? "OVMS will start serving the Resnet-50 model as model-name='resnet_50', model-version=1, and gRPC-port=9000." Server w/ resnet is running, how it can be utilized? thanks, p.s.: tensorflow installation was required for model converter. another curious thing is you use "python and python3", I just used python3 only.

    BR/Kobu

    opened by kobuworks 3
Owner
Yasunori Shimura
Yasunori Shimura
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