List of Notebooks

Each notebook is located in a directory. Any notebook with a button can be run without installing anything. Binder is a free online service with limited resources. For the best performance, please follow the Installation Guide before launching Jupyter Lab or Jupyter Notebook.

Getting Started

Brief tutorials that demonstrate how to use OpenVINO's Python API for inference.

Notebook	Description	Preview
001-hello-world	Classify an image with OpenVINO
002-openvino-api	Learn the OpenVINO Python API
003-hello-segmentation	Semantic segmentation with OpenVINO

Convert & Optimize

Tutorials that explain how to optimize and quantize models with OpenVINO tools.

Notebook	Description	Preview
101-tensorflow-to-openvino	Convert TensorFlow models to OpenVINO IR
102-pytorch-onnx-to-openvino	Convert PyTorch models to OpenVINO IR
103-paddle-onnx-to-openvino	Convert PaddlePaddle models to OpenVINO IR
104-model-tools	Download, convert and benchmark models from Open Model Zoo
105-language-quantize-bert	Optimize and quantize a pre-trained BERT model

Model Demos

Demos that demonstrate inference on a particular model.

Notebook	Description	Preview
201-vision-monodepth	Monocular depth estimation with images and video
202-vision-superresolution-image	Upscale raw images with a super resolution model	→
202-vision-superresolution-video	Turn 360p into 1080p video using a super resolution model	→
205-vision-background-removal	Remove and replace the background in an image using salient object detection
206-vision-paddlegan-anime	Turn an image into anime using a GAN	→

Model Training

Tutorials that include code to train neural networks.

Notebook	Description	Preview
301-tensorflow-training-openvino	Train a flower classification model from TensorFlow, then convert to OpenVINO IR
301-tensorflow-training-openvino-pot	Use Post-training Optimization Tool (POT) to quantize the flowers model