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

Here you will fine a collection of notebooks categorized into four classes, select the one is more related with your need or test all if you want. Good Luck!

💻 First steps

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

001-hello-world	002-openvino-api	003-hello-segmentation	004-hello-detection
Classify an image with OpenVINO	Learn the OpenVINO Python API	Semantic segmentation with OpenVINO	Text detection with OpenVINO

⌚ Convert & Optimize

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

101-tensorflow-to-openvino	102-pytorch-onnx-to-openvino	103-paddle-onnx-to-openvino	104-model-tools
Convert TensorFlow models to OpenVINO IR	Convert PyTorch models to OpenVINO IR	Convert PaddlePaddle models to OpenVINO IR	Download, convert and benchmark models from Open Model Zoo

More amazing notebooks here! Please take a look of the complete list.

Notebook	Description
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
110-ct-segmentation-quantize	Quantize a kidney segmentation model and show live inference
111-detection-quantization	Quantize an object detection model
112-pytorch-post-training-quantization-nncf	Use Neural Network Compression Framework (NNCF) to quantize PyTorch model in post-training mode (without model fine-tuning)
113-image-classification-quantization	Quantize mobilenet image classification

🎯 Model Demos

Demos that demonstrate inference on a particular model.

210-ct-scan-live-inference	211-speech-to-text	213-question-answering	208-optical-character-recognition	209-handwritten-ocr
Show live inference on segmentation of CT-scan data	Run inference on speech-to-text recognition model	Answer your questions basing on a context	Annotate text on images using text recognition resnet	OCR for handwritten simplified Chinese and Japanese
				的人不一了是他有为在责新中任自之我们

More amazing notebooks here! Please take a look of the complete list.

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	→
207-vision-paddlegan-superresolution	Upscale small images with superresolution using a PaddleGAN model
208-optical-character-recognition	Annotate text on images using text recognition resnet
209-handwritten-ocr	OCR for handwritten simplified Chinese and Japanese	的人不一了是他有为在责新中任自之我们
210-ct-scan-live-inference	Show live inference on segmentation of CT-scan data
211-speech-to-text	Run inference on speech-to-text recognition model
212-onnx-style-transfer	Transform images to five different styles with neural style transfer	→
213-question-answering	Answer your questions basing on a context
214-vision-paddle-classification	PaddlePaddle Image Classification with OpenVINO

🏃 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
302-pytorch-quantization-aware-training	Use Neural Network Compression Framework (NNCF) to quantize PyTorch model
305-tensorflow-quantization-aware-training	Use Neural Network Compression Framework (NNCF) to quantize TensorFlow model

📺 Live Demos

Live inference demos that run on a webcam or video files.

401-object-detection-webcam	402-pose-estimation-webcam	403-action-recognition-webcam
Object detection with a webcam or video file	Human pose estimation with a webcam or video file	Human action recognition with a webcam or video file

If you have some problems please check the troubleshooting section or the FAQ section

Notebooks 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 and run the notebooks locally.

You will have a lot of fun with this section:

Vision-monodepth	CT-scan-live-inference	Object-detection-webcam	Pose-estimation-webcam	Action-recognition-webcam