## 📝 Installation Guide OpenVINO Notebooks require Python and Git. To get started, select the guide for your operating system or environment: | [Windows](https://github.com/openvinotoolkit/openvino_notebooks/wiki/Windows) | [Ubuntu](https://github.com/openvinotoolkit/openvino_notebooks/wiki/Ubuntu) | [macOS](https://github.com/openvinotoolkit/openvino_notebooks/wiki/macOS) | [Red Hat](https://github.com/openvinotoolkit/openvino_notebooks/wiki/Red-Hat-and-CentOS) | [CentOS](https://github.com/openvinotoolkit/openvino_notebooks/wiki/Red-Hat-and-CentOS) | [Azure ML](https://github.com/openvinotoolkit/openvino_notebooks/wiki/AzureML) | [Docker](https://github.com/openvinotoolkit/openvino_notebooks/wiki/Docker) | [Amazon SageMaker](https://github.com/openvinotoolkit/openvino_notebooks/wiki/SageMaker) | | ----------------------------------------------------------------------------- | --------------------------------------------------------------------------- | ------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------ | --------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------- | [![-----------------------------------------------------](https://user-images.githubusercontent.com/10940214/155750931-fc094349-b6ec-4e1f-9f9a-113e67941119.jpg)]()

## 🚀 Getting Started The Jupyter notebooks are categorized into four classes, select one related to your needs or give them all a try. Good Luck! **NOTE: The main branch of this repository was updated to support the new OpenVINO 2023.3 release.** To upgrade to the new release version, please run `pip install --upgrade -r requirements.txt` in your `openvino_env` virtual environment. If you need to install for the first time, see the [Installation Guide](#-installation-guide) section below. If you wish to use the previous release version of OpenVINO, please checkout the [2023.2 branch](https://github.com/openvinotoolkit/openvino_notebooks/tree/2023.2). If you wish to use the previous Long Term Support (LTS) version of OpenVINO check out the [2022.3 branch](https://github.com/openvinotoolkit/openvino_notebooks/tree/2022.3). If you need help, please start a GitHub [Discussion](https://github.com/openvinotoolkit/openvino_notebooks/discussions).

### 💻 First steps Brief tutorials that demonstrate how to use OpenVINO's Python API for inference. | [001-hello-world](notebooks/001-hello-world/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F001-hello-world%2F001-hello-world.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/001-hello-world/001-hello-world.ipynb) | [002-openvino-api](notebooks/002-openvino-api/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F002-openvino-api%2F002-openvino-api.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/002-openvino-api/002-openvino-api.ipynb) | [003-hello-segmentation](notebooks/003-hello-segmentation/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F003-hello-segmentation%2F003-hello-segmentation.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/003-hello-segmentation/003-hello-segmentation.ipynb) | [004-hello-detection](notebooks/004-hello-detection/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F004-hello-detection%2F004-hello-detection.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/004-hello-detection/004-hello-detection.ipynb) | | -------------------------------------------------------------------------------- | --------------------------------------------------------------------------- | ------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------- | | 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. | Notebook | Description | | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: |:----------------------------------------------------------------------------------------------------------------------------| | [101-tensorflow-classification-to-openvino](notebooks/101-tensorflow-classification-to-openvino/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F101-tensorflow-classification-to-openvino%2F101-tensorflow-classification-to-openvino.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/101-tensorflow-classification-to-openvino/101-tensorflow-classification-to-openvino.ipynb) | Convert TensorFlow models to OpenVINO IR | | [102-pytorch-to-openvino](notebooks/102-pytorch-to-openvino/)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/102-pytorch-to-openvino/102-pytorch-to-openvino.ipynb) | Convert PyTorch models to OpenVINO IR | | [103-paddle-to-openvino](notebooks/103-paddle-to-openvino/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F103-paddle-to-openvino%2F103-paddle-to-openvino-classification.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/103-paddle-to-openvino/103-paddle-to-openvino-classification.ipynb) | Convert PaddlePaddle models to OpenVINO IR | | [104-model-tools](notebooks/104-model-tools/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F104-model-tools%2F104-model-tools.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/104-model-tools/104-model-tools.ipynb) | Download, convert and benchmark models from Open Model Zoo | | [105-language-quantize-bert](notebooks/105-language-quantize-bert/)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/105-language-quantize-bert/105-language-quantize-bert.ipynb) | Optimize and quantize a pre-trained BERT model | | [106-auto-device](notebooks/106-auto-device/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?labpath=notebooks%2F106-auto-device%2F106-auto-device.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/106-auto-device/106-auto-device.ipynb) | Demonstrate how to use AUTO Device | | [107-speech-recognition-quantization](notebooks/107-speech-recognition-quantization/)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/107-speech-recognition-quantization/107-speech-recognition-quantization-data2vec.ipynb) | Quantize speech recognition models using NNCF PTQ API | | [108-gpu-device](notebooks/108-gpu-device/) | Working with GPUs in OpenVINO™ | | [109-performance-tricks](notebooks/109-performance-tricks/)| Performance tricks in OpenVINO™ | | [110-ct-segmentation-quantize](notebooks/110-ct-segmentation-quantize/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F110-ct-segmentation-quantize%2F110-ct-scan-live-inference.ipynb) | Quantize a kidney segmentation model and show live inference | | [112-pytorch-post-training-quantization-nncf](notebooks/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](notebooks/113-image-classification-quantization/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?labpath=notebooks%2F113-image-classification-quantization%2F113-image-classification-quantization.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/113-image-classification-quantization/113-image-classification-quantization.ipynb) | Quantize Image Classification model | | [115-async-api](notebooks/115-async-api/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?labpath=notebooks%2F115-async-api%2F115-async-api.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/115-async-api/115-async-api.ipynb) | Use Asynchronous Execution to Improve Data Pipelining | | | [116-sparsity-optimization](notebooks/116-sparsity-optimization/)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/116-sparsity-optimization/116-sparsity-optimization.ipynb) | Improve performance of sparse Transformer models | | [117-model-server](notebooks/117-model-server/)| Introduction to model serving with OpenVINO™ Model Server (OVMS) | | [118-optimize-preprocessing](notebooks/118-optimize-preprocessing/)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/118-optimize-preprocessing/118-optimize-preprocessing.ipynb) | Improve performance of image preprocessing step | | [119-tflite-to-openvino](notebooks/119-tflite-to-openvino/)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/119-tflite-to-openvino/119-tflite-to-openvino.ipynb) | Convert TensorFlow Lite models to OpenVINO IR | | | [120-tensorflow-object-detection-to-openvino](notebooks/120-tensorflow-object-detection-to-openvino/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F120-tensorflow-object-detection-to-openvino%2F120-tensorflow-object-detection-to-openvino.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/120-tensorflow-object-detection-to-openvino/120-tensorflow-object-detection-to-openvino.ipynb) | Convert TensorFlow Object Detection models to OpenVINO IR | | [121-convert-to-openvino](notebooks/121-convert-to-openvino/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F121-convert-to-openvino%2F121-convert-to-openvino.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/121-convert-to-openvino/121-convert-to-openvino.ipynb) | Learn OpenVINO model conversion API | | [122-quantizing-model-with-accuracy-control](notebooks/122-quantizing-model-with-accuracy-control/)| Quantizing with Accuracy Control using NNCF | | [123-detectron2-to-openvino](notebooks/123-detectron2-to-openvino/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F123-detectron2-to-openvino%2F123-detectron2-to-openvino.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/123-detectron2-to-openvino/123-detectron2-to-openvino.ipynb) | Convert Detectron2 models to OpenVINO IR | | [124-hugging-face-hub](notebooks/124-hugging-face-hub/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F124-hugging-face-hub%2F124-hugging-face-hub.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/124-hugging-face-hub/124-hugging-face-hub.ipynb) | Load models from Hugging Face Model Hub with OpenVINO™ | | [125-torchvision-zoo-to-openvino](notebooks/125-torchvision-zoo-to-openvino/)
Classification
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F125-torchvision-zoo-to-openvino%2F125-convnext-classification.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/125-torchvision-zoo-to-openvino/125-convnext-classification.ipynb)
Semantic Segmentation
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F125-torchvision-zoo-to-openvino%2F125-lraspp-segmentation.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/125-torchvision-zoo-to-openvino/125-lraspp-segmentation.ipynb)| Convert torchvision classification and semantic segmentation models to OpenVINO IR | | [126-tensorflow-hub](notebooks/126-tensorflow-hub/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F126-tensorflow-hub%2F126-tensorflow-hub.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/126-tensorflow-hub/126-tensorflow-hub.ipynb) | Convert TensorFlow Hub models to OpenVINO IR | | [127-big-transfer-quantization](notebooks/127-big-transfer-quantization/)| BiT Image Classification OpenVINO IR model Quantization with NNCF | | [128-openvino-tokenizers](notebooks/128-openvino-tokenizers/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F128-opnevino-tokenizers%2F128-opnevino-tokenizers.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/128-openvino-tokenizers/128-opnevino-tokenizers.ipynb)| Incorporate Text Processing Into OpenVINO Pipelines with OpenVINO Tokenizers |

### 🎯 Model Demos Demos that demonstrate inference on a particular model. | Notebook | Description | Preview | | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :------------------------------------------------------------------------------- | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | | [201-vision-monodepth](notebooks/201-vision-monodepth/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F201-vision-monodepth%2F201-vision-monodepth.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/201-vision-monodepth/201-vision-monodepth.ipynb) | Monocular depth estimation with images and video |

| | [202-vision-superresolution-image](notebooks/202-vision-superresolution/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F202-vision-superresolution%2F202-vision-superresolution-image.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/202-vision-superresolution/202-vision-superresolution-image.ipynb) | Upscale raw images with a super resolution model |

→

| | [202-vision-superresolution-video](notebooks/202-vision-superresolution/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F202-vision-superresolution%2F202-vision-superresolution-video.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/202-vision-superresolution/202-vision-superresolution-video.ipynb) | Turn 360p into 1080p video using a super resolution model |

→

| | [203-meter-reader](notebooks/203-meter-reader/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?labpath=notebooks%2F203-meter-reader%2F203-meter-reader.ipynb) | PaddlePaddle pre-trained models to read industrial meter's value |

| | [204-segmenter-semantic-segmentation](notebooks/204-segmenter-semantic-segmentation/)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/204-segmenter-semantic-segmentation/204-segmenter-semantic-segmentation.ipynb) | Semantic Segmentation with OpenVINO™ using Segmenter |

| | [205-vision-background-removal](notebooks/205-vision-background-removal/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F205-vision-background-removal%2F205-vision-background-removal.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/205-vision-background-removal/205-vision-background-removal.ipynb) | Remove and replace the background in an image using salient object detection |

| | [206-vision-paddlegan-anime](notebooks/206-vision-paddlegan-anime/)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/206-vision-paddlegan-anime/206-vision-paddlegan-anime.ipynb) | Turn an image into anime using a GAN |

→

| | [207-vision-paddlegan-superresolution](notebooks/207-vision-paddlegan-superresolution/)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/207-vision-paddlegan-superresolution/207-vision-paddlegan-superresolution.ipynb) | Upscale small images with superresolution using a PaddleGAN model| | | [208-optical-character-recognition](notebooks/208-optical-character-recognition/)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/208-optical-character-recognition/208-optical-character-recognition.ipynb) | Annotate text on images using text recognition resnet |

| | [209-handwritten-ocr](notebooks/209-handwritten-ocr/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F209-handwritten-ocr%2F209-handwritten-ocr.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/209-handwritten-ocr/209-handwritten-ocr.ipynb) | OCR for handwritten simplified Chinese and Japanese | handwritten_simplified_chinese_test

的人不一了是他有为在责新中任自之我们 | | [210-slowfast-video-recognition](notebooks/210-slowfast-video-recognition/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F210-slowfast-video-recognition%2F210-slowfast-video-recognition.ipynb) | Video Recognition using SlowFast and OpenVINO™ |

| | [211-speech-to-text](notebooks/211-speech-to-text/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F211-speech-to-text%2F211-speech-to-text.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/211-speech-to-text/211-speech-to-text.ipynb) | Run inference on speech-to-text recognition model |

| | [212-pyannote-speaker-diarization](notebooks/212-pyannote-speaker-diarization/)
| Run inference on speaker diarization pipeline |

| | [213-question-answering](notebooks/213-question-answering/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F213-question-answering%2F213-question-answering.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/213-question-answering/213-question-answering.ipynb) | Answer your questions basing on a context |

| | [214-grammar-correction](notebooks/214-grammar-correction/) | Grammatical Error Correction with OpenVINO | **Input text**: `I'm working in campany for last 2 yeas.`
**Generated text**: `I'm working in a company for the last 2 years.` | | [215-image-inpainting](notebooks/215-image-inpainting/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?labpath=notebooks%2F215-image-inpainting%2F215-image-inpainting.ipynb)| Fill missing pixels with image in-painting |

| | [216-attention-center](notebooks/216-attention-center/)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/216-attention-center/216-attention-center.ipynb) | The attention center model with OpenVINO™ | | | [218-vehicle-detection-and-recognition](notebooks/218-vehicle-detection-and-recognition/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?labpath=notebooks%2F218-vehicle-detection-and-recognition%2F218-vehicle-detection-and-recognition.ipynb) | Use pre-trained models to detect and recognize vehicles and their attributes with OpenVINO |

| | [219-knowledge-graphs-conve](notebooks/219-knowledge-graphs-conve/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?labpath=notebooks%2F219-knowledge-graphs-conve%2F219-knowledge-graphs-conve.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/219-knowledge-graphs-conve/219-knowledge-graphs-conve.ipynb) | Optimize the knowledge graph embeddings model (ConvE) with OpenVINO || | [220-books-alignment-labse](notebooks/220-cross-lingual-books-alignment/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?labpath=notebooks%2F220-cross-lingual-books-alignment%2F220-cross-lingual-books-alignment.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/220-cross-lingual-books-alignment/220-cross-lingual-books-alignment.ipynb)| Cross-lingual Books Alignment With Transformers and OpenVINO™ | | | [221-machine-translation](notebooks/221-machine-translation)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?labpath=notebooks%2F221-machine-translation%2F221-machine-translation.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/221-machine-translation/221-machine-translation.ipynb) | Real-time translation from English to German | | | [222-vision-image-colorization](notebooks/222-vision-image-colorization/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?labpath=notebooks%2F222-vision-image-colorization%2F222-vision-image-colorization.ipynb) | Use pre-trained models to colorize black \& white images using OpenVINO |

| | [223-text-prediction](notebooks/223-text-prediction/)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/223-text-prediction/223-text-prediction.ipynb) | Use pretrained models to perform text prediction on an input sequence |

| | [224-3D-segmentation-point-clouds](notebooks/224-3D-segmentation-point-clouds/)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/224-3D-segmentation-point-clouds/224-3D-segmentation-point-clouds.ipynb) | Process point cloud data and run 3D Part Segmentation with OpenVINO |

| | [225-stable-diffusion-text-to-image](notebooks/225-stable-diffusion-text-to-image)
| Text-to-image generation with Stable Diffusion method |

| | [226-yolov7-optimization](notebooks/226-yolov7-optimization/)
| Optimize YOLOv7 using NNCF PTQ API |

| | [227-whisper-subtitles-generation](notebooks/227-whisper-subtitles-generation/)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/227-whisper-subtitles-generation/227-whisper-convert.ipynb) | Generate subtitles for video with OpenAI Whisper and OpenVINO |

| | [228-clip-zero-shot-image-classification](notebooks/228-clip-zero-shot-image-classification)
| Perform Zero-shot Image Classification with CLIP and OpenVINO |

| | [229-distilbert-sequence-classification](notebooks/229-distilbert-sequence-classification/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?labpath=notebooks%2F229-distilbert-sequence-classification%2F229-distilbert-sequence-classification.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/229-distilbert-sequence-classification/229-distilbert-sequence-classification.ipynb) | Sequence Classification with OpenVINO |

| | [230-yolov8-object-detection](notebooks/230-yolov8-optimization/)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/230-yolov8-optimization/230-yolov8-object-detection.ipynb) | Optimize YOLOv8 object detection using NNCF PTQ API |

| | [230-yolov8-instance-segmentation](notebooks/230-yolov8-optimization/)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/230-yolov8-optimization/230-yolov8-instance-segmentation.ipynb) | Optimize YOLOv8 instance segmentation using NNCF PTQ API |

| | [230-yolov8-keypoint-detection](notebooks/230-yolov8-optimization/)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/230-yolov8-optimization/230-yolov8-keypoint-detection.ipynb) | Optimize YOLOv8 keypoint detection using NNCF PTQ API |

| | [231-instruct-pix2pix-image-editing](notebooks/231-instruct-pix2pix-image-editing/)
| Image editing with InstructPix2Pix |

| | [232-clip-language-saliency-map](notebooks/232-clip-language-saliency-map/)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/232-clip-language-saliency-map/232-clip-language-saliency-map.ipynb) | Language-Visual Saliency with CLIP and OpenVINO™ |

| | [233-blip-visual-language-processing](notebooks/233-blip-visual-language-processing/)
| Visual Question Answering and Image Captioning using BLIP and OpenVINO™ |

| | [234-encodec-audio-compression](notebooks/234-encodec-audio-compression/)
| Audio compression with EnCodec and OpenVINO™ |

| | [235-controlnet-stable-diffusion](notebooks/235-controlnet-stable-diffusion/)
| A Text-to-Image Generation with ControlNet Conditioning and OpenVINO™ |

| | [236-stable-diffusion-v2](notebooks/236-stable-diffusion-v2/)
| Text-to-Image Generation and Infinite Zoom with Stable Diffusion v2 and OpenVINO™ |

| | [237-segment-anything](notebooks/237-segment-anything/)
| Prompt based segmentation using Segment Anything and OpenVINO™.|

| | [238-deep-floyd-if](notebooks/238-deepfloyd-if/)
| Text-to-Image Generation with DeepFloyd IF and OpenVINO™ |

| | [239-image-bind](notebooks/239-image-bind/)
| Binding multimodal data using ImageBind and OpenVINO™ |

| | [240-dolly-2-instruction-following](notebooks/240-dolly-2-instruction-following/)
| Instruction following using Databricks Dolly 2.0 and OpenVINO™ |

| | [241-riffusion-text-to-music](notebooks/241-riffusion-text-to-music/)
| Text-to-Music generation using Riffusion and OpenVINO™ |

| | [242-freevc-voice-conversion](notebooks/242-freevc-voice-conversion/)
| High-Quality Text-Free One-Shot Voice Conversion with FreeVC and OpenVINO™ || | [243-tflite-selfie-segmentation](notebooks/243-tflite-selfie-segmentation/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F243-tflite-selfie-segmentation%2F243-tflite-selfie-segmentation.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/243-tflite-selfie-segmentation/243-tflite-selfie-segmentation.ipynb)| Selfie Segmentation using TFLite and OpenVINO™ |

| | [244-named-entity-recognition](notebooks/244-named-entity-recognition/)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/244-named-entity-recognition/244-named-entity-recognition.ipynb) | Named entity recognition with OpenVINO™ | | | [245-typo-detector](notebooks/245-typo-detector/)
| English Typo Detection in sentences with OpenVINO™ |

| | [246-depth-estimation-videpth](notebooks/246-depth-estimation-videpth/)
| Monocular Visual-Inertial Depth Estimation with OpenVINO™ |

| | [247-code-language-id](notebooks/247-code-language-id/247-code-language-id.ipynb)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F247-code-language-id%2F247-code-language-id.ipynb) | Identify the programming language used in an arbitrary code snippet | || | [248-stable-diffusion-xl](notebooks/248-stable-diffusion-xl/)
| Image generation with Stable Diffusion XL and OpenVINO™ |

| | [249-oneformer-segmentation](notebooks/249-oneformer-segmentation/)
| Universal segmentation with OneFormer and OpenVINO™ |

| | [250-music-generation](notebooks/250-music-generation/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F250-music-generation%2F250-music-generation.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/250-music-generation/250-music-generation.ipynb) | Controllable Music Generation with MusicGen and OpenVINO™ |

| | [251-tiny-sd-image-generation](notebooks/251-tiny-sd-image-generation/)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/251-tiny-sd-image-generation/251-tiny-sd-image-generation.ipynb) | Image Generation with Tiny-SD and OpenVINO™ |

| | [252-fastcomposer-image-generation](notebooks/252-fastcomposer-image-generation/)
| Image generation with FastComposer and OpenVINO™ | | | [253-zeroscope-text2video](notebooks/253-zeroscope-text2video)
| Text-to-video synthesis with ZeroScope and OpenVINO™ | A panda eating bamboo on a rock

| | [254-llm-chatbot](notebooks/254-llm-chatbot)
| Create LLM-powered Chatbot using OpenVINO™ |

| | [255-mms-massively-multilingual-speech](notebooks/255-mms-massively-multilingual-speech/)
| MMS: Scaling Speech Technology to 1000+ languages with OpenVINO™ | | | [256-bark-text-to-audio](notebooks/256-bark-text-to-audio)
| Text-to-Speech generation using Bark and OpenVINO™ |

| | [257-llava-multimodal-chatbot](notebooks/257-llava-multimodal-chatbot)
| Visual-language assistant with LLaVA and OpenVINO™ |

| | [258-blip-diffusion-subject-generation](notebooks/258-blip-diffusion-subject-generation)
| Subject-driven image generation and editing using BLIP Diffusion and OpenVINO™ |

| | [259-decidiffusion-image-generation](notebooks/259-decidiffusion-image-generation)
| Image generation with DeciDiffusion and OpenVINO™ |

| | [260-pix2struct-docvqa](notebooks/260-pix2struct-docvqa)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/260-pix2struct-docvqa/260-pix2struct-docvqa.ipynb)
| Document Visual Question Answering using Pix2Struct and OpenVINO™ |

| [261-fast-segment-anything](notebooks/261-fast-segment-anything/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F261-fast-segment-anything%2F261-fast-segment-anything.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/261-fast-segment-anything/261-fast-segment-anything.ipynb) | Object segmentations with FastSAM and OpenVINO™ |

| | [262-softvc-voice-conversion](notebooks/262-softvc-voice-conversion)
| SoftVC VITS Singing Voice Conversion and OpenVINO™ | | | [263-latent-consistency-models-image-generation](notebooks/263-latent-consistency-models-image-generation)
| Image generation with Latent Consistency Models (LCM) and OpenVINO™ |

| | [264-qrcode-monster](notebooks/264-qrcode-monster/)
| Generate creative QR codes with ControlNet QR Code Monster and OpenVINO™ |

| | [265-wuerstchen-image-generation](notebooks/265-wuerstchen-image-generation)
| Text-to-image generation with Würstchen and OpenVINO™ |

| | [266-speculative-sampling](notebooks/266-speculative-sampling)
| Text Generation via Speculative Sampling, KV Caching, and OpenVINO™ |

| | [267-distil-whisper-asr](notebooks/267-distil-whisper-asr)
| Automatic speech recognition using Distil-Whisper and OpenVINO™ | | | [268-table-question-answering](notebooks/268-table-question-answering)

[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/268-table-question-answering/268-table-question-answering.ipynb)
| Table Question Answering using TAPAS and OpenVINO™ || | [269-film-slowmo](notebooks/269-film-slowmo)
| Frame interpolation with FILM and OpenVINO™ |

| | [270-sound-generation-audioldm2](notebooks/270-sound-generation-audioldm2/)
| Sound Generation with AudioLDM2 and OpenVINO™ |

| | [271-sdxl-turbo](notebooks/271-sdxl-turbo/)
| Single-step image generation using SDXL-turbo and OpenVINO |

| | [272-paint-by-example](notebooks/272-paint-by-example/)
| Exemplar based image editing using diffusion models, [Paint-by-Example](https://github.com/Fantasy-Studio/Paint-by-Example), and OpenVINO™ | ui_example

| | [273-stable-zephyr-3b-chatbot](notebooks/273-stable-zephyr-3b-chatbot)
| Use Stable-Zephyr as chatbot assistant with OpenVINO |

| | [274-efficient-sam](notebooks/274-efficient-sam/)
| Object segmentation with EfficientSAM and OpenVINO™ |

| | [275-llm-question-answering](notebooks/275-llm-question-answering)
| LLM Instruction following pipeline |

| | [276-stable-diffusion-torchdynamo-backend](notebooks/276-stable-diffusion-torchdynamo-backend/)
| Image generation with Stable Diffusion and OpenVINO™ `torch.compile` feature |

| | [277-amused-lightweight-text-to-image](notebooks/277-amused-lightweight-text-to-image)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/277-amused-lightweight-text-to-image/277-amused-lightweight-text-to-image.ipynb)
| Lightweight image generation with aMUSEd and OpenVINO™ |

| | [278-stable-diffusion-ip-adapter](notebooks/278-stable-diffusion-ip-adapter)
| Image conditioning in Stable Diffusion pipeline using IP-Adapter |

| | [279-mobilevlm-language-assistant](notebooks/279-mobilevlm-language-assistant)
| Mobile language assistant with MobileVLM and OpenVINO | | | [280-depth-anything](notebooks/280-depth-anything)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F280-depth-anythingh%2F280-depth-anything.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/280-depth-anything/280-depth-anything.ipynb) | Monocular Depth Estimation with DepthAnything and OpenVINO |

| | [281-kosmos2-multimodal-large-language-model](notebooks/281-kosmos2-multimodal-large-language-model)
| Kosmos-2: Multimodal Large Language Model and OpenVINO™ |

| | [282-siglip-zero-shot-image-classification](notebooks/282-siglip-zero-shot-image-classification)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/282-siglip-zero-shot-image-classification/282-siglip-zero-shot-image-classification.ipynb) | Zero-shot Image Classification with SigLIP |

| | [283-photo-maker](notebooks/283-photo-maker)
| Text-to-image generation using PhotoMaker and OpenVINO |

| | [284-openvoice](notebooks/284-openvoice)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F284-openvoice%2F284-openvoice.ipynb)[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/284-openvoice/284-openvoice.ipynb) | OpenVoice a versatile instant voice tone transferring and generating speech in various languages. |

| | [285-surya-line-level-text-detection](notebooks/285-surya-line-level-text-detection)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/285-surya-line-level-text-detection/285-surya-line-level-text-detection.ipynb) | Line-level text detection with Surya |

| | [286-instant-id](notebooks/286-instant-id)
| InstantID: Zero-shot Identity-Preserving Image Generation using OpenVINO|

| | [287-yolov9-optimization](notebooks/287-yolov9-optimization)
| Optimize YOLOv9 using NNCF |

### 🏃 Model Training Tutorials that include code to train neural networks. | Notebook | Description | Preview | | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :------------------------------------------------------------------------------- | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | | [301-tensorflow-training-openvino](notebooks/301-tensorflow-training-openvino/) | Train a flower classification model from TensorFlow, then convert to OpenVINO IR |

| | [301-tensorflow-training-openvino-nncf](notebooks/301-tensorflow-training-openvino/) | Use Neural Network Compression Framework (NNCF) to quantize model from TensorFlow | | | [302-pytorch-quantization-aware-training](notebooks/302-pytorch-quantization-aware-training/) | Use Neural Network Compression Framework (NNCF) to quantize PyTorch model | | | [305-tensorflow-quantization-aware-training](notebooks/305-tensorflow-quantization-aware-training/)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/305-tensorflow-quantization-aware-training/305-tensorflow-quantization-aware-training.ipynb) | Use Neural Network Compression Framework (NNCF) to quantize TensorFlow model | |

### 📺 Live Demos Live inference demos that run on a webcam or video files. | Notebook | Description | Preview | | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | :------------------------------------------------------------------------------- | :------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------: | | [401-object-detection-webcam](notebooks/401-object-detection-webcam/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F401-object-detection-webcam%2F401-object-detection.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/401-object-detection-webcam/401-object-detection.ipynb) | Object detection with a webcam or video file |

| | [402-pose-estimation-webcam](notebooks/402-pose-estimation-webcam/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F402-pose-estimation-webcam%2F402-pose-estimation.ipynb) | Human pose estimation with a webcam or video file |

| | [403-action-recognition-webcam](notebooks/403-action-recognition-webcam/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F403-action-recognition-webcam%2F403-action-recognition-webcam.ipynb) | Human action recognition with a webcam or video file |

| | [404-style-transfer-webcam](notebooks/404-style-transfer-webcam/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F404-style-transfer-webcam%2F404-style-transfer.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/404-style-transfer-webcam/404-style-transfer.ipynb) | Style Transfer with a webcam or video file |

| | [405-paddle-ocr-webcam](notebooks/405-paddle-ocr-webcam/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?labpath=notebooks%2F405-paddle-ocr-webcam%2F405-paddle-ocr-webcam.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/405-paddle-ocr-webcam/405-paddle-ocr-webcam.ipynb) | OCR with a webcam or video file |

| | [406-3D-pose-estimation-webcam](notebooks/406-3D-pose-estimation-webcam/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?labpath=notebooks%2F406-3D-pose-estimation-webcam%2F406-3D-pose-estimation.ipynb) | 3D display of human pose estimation with a webcam or video file |

| | [407-person-tracking-webcam](notebooks/407-person-tracking-webcam/)
[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/openvinotoolkit/openvino_notebooks/HEAD?filepath=notebooks%2F407-person-tracking-webcam%2F407-person-tracking.ipynb)
[![Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/openvinotoolkit/openvino_notebooks/blob/main/notebooks/407-person-tracking-webcam/407-person-tracking.ipynb) | Person tracking with a webcam or video file |

| If you run into issues, please check the [troubleshooting section](#-troubleshooting), [FAQs](#-faq) or start a GitHub [discussion](https://github.com/openvinotoolkit/openvino_notebooks/discussions). Notebooks with ![binder logo](https://mybinder.org/badge_logo.svg) and ![colab logo](https://colab.research.google.com/assets/colab-badge.svg) buttons can be run without installing anything. [Binder](https://mybinder.org/) and [Google Colab](https://colab.research.google.com/) are free online services with limited resources. For the best performance, please follow the [Installation Guide](#-installation-guide) and run the notebooks locally. [![-----------------------------------------------------](https://user-images.githubusercontent.com/10940214/155750931-fc094349-b6ec-4e1f-9f9a-113e67941119.jpg)]()

## ⚙️ System Requirements The notebooks run almost anywhere — your laptop, a cloud VM, or even a Docker container. The table below lists the supported operating systems and Python versions. | Supported Operating System | [Python Version (64-bit)](https://www.python.org/) | | :--------------------------------------------------------- |:---------------------------------------------------| | Ubuntu 20.04 LTS, 64-bit | 3.8 - 3.10 | | Ubuntu 22.04 LTS, 64-bit | 3.8 - 3.10 | | Red Hat Enterprise Linux 8, 64-bit | 3.8 - 3.10 | | CentOS 7, 64-bit | 3.8 - 3.10 | | macOS 10.15.x versions or higher | 3.8 - 3.10 | | Windows 10, 64-bit Pro, Enterprise or Education editions | 3.8 - 3.10 | | Windows Server 2016 or higher | 3.8 - 3.10 | [![-----------------------------------------------------](https://user-images.githubusercontent.com/10940214/155750931-fc094349-b6ec-4e1f-9f9a-113e67941119.jpg)](#)

## 💻 Run the Notebooks ### To Launch a Single Notebook If you wish to launch only one notebook, like the Monodepth notebook, run the command below. ```bash jupyter 201-vision-monodepth.ipynb ``` ### To Launch all Notebooks ```bash jupyter lab notebooks ``` In your browser, select a notebook from the file browser in Jupyter Lab using the left sidebar. Each tutorial is located in a subdirectory within the `notebooks` directory.

[![-----------------------------------------------------](https://user-images.githubusercontent.com/10940214/155750931-fc094349-b6ec-4e1f-9f9a-113e67941119.jpg)]()

## 🧹 Cleaning Up

1. Shut Down Jupyter Kernel To end your Jupyter session, press `Ctrl-c`. This will prompt you to `Shutdown this Jupyter server (y/[n])?` enter `y` and hit `Enter`.

2. Deactivate Virtual Environment To deactivate your virtualenv, simply run `deactivate` from the terminal window where you activated `openvino_env`. This will deactivate your environment. To reactivate your environment, run `source openvino_env/bin/activate` on Linux or `openvino_env\Scripts\activate` on Windows, then type `jupyter lab` or `jupyter notebook` to launch the notebooks again.

3. Delete Virtual Environment _(Optional)_ To remove your virtual environment, simply delete the `openvino_env` directory:

- On Linux and macOS: ```bash rm -rf openvino_env ```

- On Windows: ```bash rmdir /s openvino_env ```

- Remove `openvino_env` Kernel from Jupyter ```bash jupyter kernelspec remove openvino_env ```

[![-----------------------------------------------------](https://user-images.githubusercontent.com/10940214/155750931-fc094349-b6ec-4e1f-9f9a-113e67941119.jpg)]()

## ⚠️ Troubleshooting If these tips do not solve your problem, please open a [discussion topic](https://github.com/openvinotoolkit/openvino_notebooks/discussions) or create an [issue](https://github.com/openvinotoolkit/openvino_notebooks/issues)! - To check some common installation problems, run `python check_install.py`. This script is located in the openvino_notebooks directory. Please run it after activating the `openvino_env` virtual environment. - If you get an `ImportError`, double-check that you installed the Jupyter kernel. If necessary, choose the `openvino_env` kernel from the _Kernel->Change Kernel_ menu in Jupyter Lab or Jupyter Notebook. - If OpenVINO is installed globally, do not run installation commands in a terminal where `setupvars.bat` or `setupvars.sh` are sourced. - For Windows installation, it is recommended to use _Command Prompt (`cmd.exe`)_, not _PowerShell_. [![-----------------------------------------------------](https://user-images.githubusercontent.com/10940214/155750931-fc094349-b6ec-4e1f-9f9a-113e67941119.jpg)](#-contributors)

## 🧑‍💻 Contributors

Made with [`contrib.rocks`](https://contrib.rocks). [![-----------------------------------------------------](https://user-images.githubusercontent.com/10940214/155750931-fc094349-b6ec-4e1f-9f9a-113e67941119.jpg)]()

## ❓ FAQ * [Which devices does OpenVINO support?](https://docs.openvino.ai/2023.3/openvino_docs_OV_UG_supported_plugins_Supported_Devices.html#doxid-openvino-docs-o-v-u-g-supported-plugins-supported-devices) * [What is the first CPU generation you support with OpenVINO?](https://www.intel.com/content/www/us/en/developer/tools/openvino-toolkit/system-requirements.html) * [Are there any success stories about deploying real-world solutions with OpenVINO?](https://www.intel.com/content/www/us/en/internet-of-things/ai-in-production/success-stories.html) --- \* Other names and brands may be claimed as the property of others.

📚 OpenVINO™ Notebooks