Demos#

OpenVINO Model Server demos have been created to showcase the usage of the model server as well as demonstrate it’s capabilities.

Check Out New Generative AI Demos#

Check out the list below to see complete step-by-step examples of using OpenVINO Model Server with real world use cases:

With Python Client#

Demo

Description

Text Generation

Generate text using one of popular LLMs sending prompts via gRPC API unary or interactive streaming endpoint.

Stable Diffusion

Generate image using Stable Diffusion model sending prompts via gRPC API unary or interactive streaming endpoint.

CLIP image classification

Classify image according to provided labels using CLIP model embedded in a multi-node MediaPipe graph.

Seq2seq translation

Translate text using seq2seq model via gRPC API.

Age gender recognition

Run prediction on a JPEG image using age gender recognition model via gRPC API.

Horizontal Text Detection in Real-Time

Run prediction on camera stream using a horizontal text detection model via gRPC API. This demo uses pipeline with horizontal_ocr custom node and demultiplexer.

Optical Character Recognition Pipeline

Run prediction on a JPEG image using a pipeline of text recognition and text detection models with a custom node for intermediate results processing via gRPC API. This demo uses pipeline with east_ocr custom node and demultiplexer.

Face Detection

Run prediction on a JPEG image using face detection model via gRPC API.

Single Face Analysis Pipeline

Run prediction on a JPEG image using a simple pipeline of age-gender recognition and emotion recognition models via gRPC API to analyze image with a single face. This demo uses pipeline

Multi Faces Analysis Pipeline

Run prediction on a JPEG image using a pipeline of age-gender recognition and emotion recognition models via gRPC API to extract multiple faces from the image and analyze all of them. This demo uses pipeline with model_zoo_intel_object_detection custom node and demultiplexer

Model Ensemble Pipeline

Combine multiple image classification models into one pipeline and aggregate results to improve classification accuracy.

Image Classification

Run prediction on a JPEG image using image classification model via gRPC API.

Using ONNX Model

Run prediction on a JPEG image using image classification ONNX model via gRPC API in two preprocessing variants. This demo uses pipeline with image_transformation custom node.

Using TensorFlow Model

Run image classification using directly imported TensorFlow model.

Person, Vehicle, Bike Detection

Run prediction on a video file or camera stream using person, vehicle, bike detection model via gRPC API.

Vehicle Analysis Pipeline

Detect vehicles and recognize their attributes using a pipeline of vehicle detection and vehicle attributes recognition models with a custom node for intermediate results processing via gRPC API. This demo uses pipeline with model_zoo_intel_object_detection custom node.

Real Time Stream Analysis

Analyze RTSP video stream in real time with generic application template for custom pre and post processing routines as well as simple results visualizer for displaying predictions in the browser.

Segmentation with PaddlePaddle

Perform segmentation on an image with a PaddlePaddle model.

Natural Language Processing with BERT

Provide a knowledge source and a query and use BERT model for question answering use case via gRPC API. This demo uses dynamic shape feature.

Using inputs data in string format with universal-sentence-encoder model

Handling AI model with text as the model input.

Benchmark App

Generate traffic and measure performance of the model served in OpenVINO Model Server.

Face Blur Pipeline

Detect faces and blur image using a pipeline of object detection models with a custom node for intermediate results processing via gRPC API. This demo uses pipeline with face_blur custom node.

With C++ Client#

Demo

Description

C API applications

How to use C API from the OpenVINO Model Server to create C and C++ application.

Image Classification

Run prediction on a JPEG image using image classification model via gRPC API.

Benchmark App

Generate traffic and measure performance of the model served in OpenVINO Model Server.

With Go Client#

Demo

Description

Image Classification

Run prediction on a JPEG image using image classification model via gRPC API.