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 |
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Generate image using Stable Diffusion model sending prompts via gRPC API unary or interactive streaming endpoint. |
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Classify image according to provided labels using CLIP model embedded in a multi-node MediaPipe graph. |
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Translate text using seq2seq model via gRPC API. |
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Run prediction on a JPEG image using age gender recognition model via gRPC API. |
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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. |
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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. |
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Run prediction on a JPEG image using face detection model via gRPC API. |
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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 |
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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 |
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Combine multiple image classification models into one pipeline and aggregate results to improve classification accuracy. |
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Run prediction on a JPEG image using image classification model via gRPC API. |
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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. |
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Run image classification using directly imported TensorFlow model. |
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Run prediction on a video file or camera stream using person, vehicle, bike detection model via gRPC API. |
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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. |
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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. |
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Perform classification on an image with a PaddlePaddle model. |
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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. |
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Using inputs data in string format with universal-sentence-encoder model |
Handling AI model with text as the model input. |
Generate traffic and measure performance of the model served in OpenVINO Model Server. |
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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 |
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How to use C API from the OpenVINO Model Server to create C and C++ application. |
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Run prediction on a JPEG image using image classification model via gRPC API. |
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Generate traffic and measure performance of the model served in OpenVINO Model Server. |
With Go Client#
Demo |
Description |
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Run prediction on a JPEG image using image classification model via gRPC API. |