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[DOCS] Updating Tutorials (#17769)

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docs/nbdoc/consts.py
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@ -8,7 +8,7 @@ repo_owner = "openvinotoolkit"
repo_name = "openvino_notebooks"
artifacts_link = "http://repository.toolbox.iotg.sclab.intel.com/projects/ov-notebook/0.1.0-latest/20230517220809/dist/rst_files/"
artifacts_link = "http://repository.toolbox.iotg.sclab.intel.com/projects/ov-notebook/0.1.0-latest/20230529220816/dist/rst_files/"
blacklisted_extensions = ['.xml', '.bin']

167
docs/notebooks-installation.md
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@ -107,7 +107,7 @@ operating system or environment.
Linux Systems may require installation of additional libraries.
The following installation steps should work on Ubuntu Desktop 18.04, 20.04, 20.10, and on Ubuntu Server.
The following installation steps should work on a clean install of Ubuntu Desktop 20.04, and should also work on Ubuntu 22.04 and 20.10, and on Ubuntu Server.
.. code-block::
@ -115,6 +115,17 @@ operating system or environment.
sudo apt-get upgrade
sudo apt-get install python3-venv build-essential python3-dev git-all
For an Intel Integrated Graphics Card, you can install the `Intel Graphics Compute Runtime <https://github.com/intel/compute-runtime>`__ to enable inference on this device. The command for Ubuntu 20.04 is:
.. note::
Only execute this command if you do not yet have OpenCL drivers installed.
.. code-block::
sudo apt-get install intel-opencl-icd
The following installation steps should work on a clean install of Red Hat, CentOS, Amazon Linux 2 or Fedora. If any issues occur, see the `Troubleshooting <#-troubleshooting>`__ section.
.. code-block::
@ -125,17 +136,35 @@ operating system or environment.
.. tab:: macOS
1. **Install Python**
Alternatively, you may skip steps 1-3 if you prefer to manually install `Python 3 <https://www.python.org/>`__ and `Git <https://git-scm.com/>`__.
Download Python software (3.7, 3.8, 3.9, 3.10, 3.11) from `python.org`. For example, this `installer`_.
1. **Install Xcode Command Line Tools**
.. _installer: https://www.python.org/ftp/python/3.7.9/python-3.7.9-macosx10.9.pkg
.. code-block::
Run the installer by double clicking it. Follow the installation steps to set up the software.
xcode-select --install
2. **Install Homebrew**
.. code-block::
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"
After you install it, follow the instructions from the Homebrew installation to set it up.
3. **Install Python and dependencies**
.. code-block::
brew install python@3.9
brew install protobuf
Run each step below in a terminal.
.. note::
Refer to the "Important Information" displayed during installation for information about SSL/TLS certificate validation and running the "Install Certificates.command". These certificates are required to run some of the notebooks.
If OpenVINO is installed globally, do not run any of these commands in a terminal where ``setupvars.sh`` is sourced.
.. tab:: Azure ML
@ -165,38 +194,53 @@ operating system or environment.
FROM quay.io/thoth-station/s2i-thoth-ubi8-py38:v0.29.0
LABEL name="OpenVINO(TM) Notebooks" \
maintainer="helena.kloosterman@intel.com" \
vendor="Intel Corporation" \
version="0.2.0" \
release="2021.4" \
summary="OpenVINO(TM) Developer Tools and Jupyter Notebooks" \
description="OpenVINO(TM) Notebooks Container"
maintainer="helena.kloosterman@intel.com" \
vendor="Intel Corporation" \
version="0.2.0" \
release="2021.4" \
summary="OpenVINO(TM) Developer Tools and Jupyter Notebooks" \
description="OpenVINO(TM) Notebooks Container"
ENV JUPYTER_ENABLE_LAB="true" \
ENABLE_MICROPIPENV="1" \
UPGRADE_PIP_TO_LATEST="1" \
WEB_CONCURRENCY="1" \
THOTH_ADVISE="0" \
THOTH_ERROR_FALLBACK="1" \
THOTH_DRY_RUN="1" \
THAMOS_DEBUG="0" \
THAMOS_VERBOSE="1" \
THOTH_PROVENANCE_CHECK="0"
ENABLE_MICROPIPENV="1" \
UPGRADE_PIP_TO_LATEST="1" \
WEB_CONCURRENCY="1" \
THOTH_ADVISE="0" \
THOTH_ERROR_FALLBACK="1" \
THOTH_DRY_RUN="1" \
THAMOS_DEBUG="0" \
THAMOS_VERBOSE="1" \
THOTH_PROVENANCE_CHECK="0"
USER root
# Upgrade NodeJS > 12.0
# Install dos2unix for line end conversion on Windows
RUN curl -sL https://rpm.nodesource.com/setup_14.x | bash - && \
yum remove -y nodejs && \
yum install -y nodejs mesa-libGL dos2unix libsndfile && \
yum -y update-minimal --security --sec-severity=Important --sec-severity=Critical --sec-severity=Moderate
yum remove -y nodejs && \
yum install -y nodejs-14.18.1 mesa-libGL dos2unix libsndfile && \
yum -y update-minimal --security --sec-severity=Important --sec-severity=Critical --sec-severity=Moderate
# GPU drivers
RUN dnf install -y 'dnf-command(config-manager)' && \
dnf config-manager --add-repo https://repositories.intel.com/graphics/rhel/8.5/intel-graphics.repo
RUN rpm -ivh https://vault.centos.org/centos/8/AppStream/x86_64/os/Packages/mesa-filesystem-21.1.5-1.el8.x86_64.rpm && \
dnf install --refresh -y \
intel-opencl-22.28.23726.1-i419.el8.x86_64 intel-media intel-mediasdk libmfxgen1 libvpl2 \
level-zero intel-level-zero-gpu \
intel-metrics-library intel-igc-core intel-igc-cm \
libva libva-utils intel-gmmlib && \
rpm -ivh http://mirror.centos.org/centos/8-stream/AppStream/x86_64/os/Packages/ocl-icd-2.2.12-1.el8.x86_64.rpm && \
rpm -ivh https://download-ib01.fedoraproject.org/pub/epel/8/Everything/x86_64/Packages/c/clinfo-3.0.21.02.21-4.el8.x86_64.rpm
# Copying in override assemble/run scripts
COPY .docker/.s2i/bin /tmp/scripts
# Copying in source code
COPY .docker /tmp/src
COPY .ci/patch_notebooks.py /tmp/scripts
COPY .ci/validate_notebooks.py /tmp/scripts
COPY .ci/ignore_treon_docker.txt /tmp/scripts
# Git on Windows may convert line endings. Run dos2unix to enable
# building the image when the scripts have CRLF line endings.
@ -253,7 +297,7 @@ operating system or environment.
.. code-block::
python -m pip install --upgrade pip
python -m pip install --upgrade pip wheel setuptools
5. **Install required packages**
@ -263,13 +307,6 @@ operating system or environment.
pip install -r requirements.txt
6. **Install the virtualenv Kernel in Jupyter**
.. code-block::
python -m ipykernel install --user --name openvino_env
.. tab:: Linux Systems
1. **Create a Virtual Environment**
@ -300,6 +337,7 @@ operating system or environment.
.. code-block::
python -m pip install --upgrade pip
pip install wheel setuptools
5. **Install required packages**
@ -308,11 +346,6 @@ operating system or environment.
pip install -r requirements.txt
6. **Install the virtualenv Kernel in Jupyter**
.. code-block::
python -m ipykernel install --user --name openvino_env
.. tab:: macOS
@ -343,8 +376,7 @@ operating system or environment.
.. code-block::
python -m pip install --upgrade pip
python -m pip install --upgrade pip wheel setuptools
5. **Install required packages**
@ -352,55 +384,62 @@ operating system or environment.
pip install -r requirements.txt
6. **Install the virtualenv Kernel in Jupyter**
.. code-block::
python -m ipykernel install --user --name openvino_env
.. tab:: Azure ML
1. **Create a Virtual Environment**
If you already have installed *openvino-dev*, you may skip this step and proceed with the next one.
1. Create a Conda environment
.. code-block::
python3 -m venv openvino_env
conda create --name openvino_env python=3.8 -y
2. **Activate the Environment**
2. Activate the environment
.. code-block::
source openvino_env/bin/activate
conda activate openvino_env
3. **Clone the Repository**
Using the --depth=1 option for git clone reduces download size.
3. Clone OpenVINO notebooks
.. code-block::
git clone https://github.com/openvinotoolkit/openvino_notebooks.git
4. Change directory to ``openvino_notebooks``
.. code-block::
git clone --depth=1 https://github.com/openvinotoolkit/openvino_notebooks.git
cd openvino_notebooks
4. **Upgrade PIP**
5. Upgrade ``pip`` and install required dependencies.
.. code-block::
python -m pip install --upgrade pip
5. **Install required packages**
.. code-block::
pip install -r requirements.txt
6. **Install the virtualenv Kernel in Jupyter**
6. Add ``openvino_env`` to PATH
.. code-block::
python -m ipykernel install --user --name openvino_env
set PATH="/anaconda/envs/openvino_env/bin;%PATH%"
7. Run the notebooks.
To run the notebooks, click on Notebooks and refresh your Files:
.. image:: https://user-images.githubusercontent.com/15709723/117580814-a725c300-b0ae-11eb-93bf-007779c26075.png
.. image:: https://user-images.githubusercontent.com/15709723/117559447-2af19800-b03a-11eb-8bd6-8813b7a8814f.png
.. image:: https://user-images.githubusercontent.com/15709723/117580973-37640800-b0af-11eb-91ae-7194b9b4e505.png
.. note::
Make sure you are using the ``openvino_env`` environment (not Python 3).
.. image:: https://user-images.githubusercontent.com/1720147/162269003-7937b47c-484f-416c-97c7-bb869376ff68.png
.. tab:: Docker
@ -464,7 +503,7 @@ If you want to launch only one notebook, such as the *Monodepth* notebook, run t
.. code:: bash
jupyter 201-vision-monodepth.ipynb
jupyter lab notebooks/201-vision-monodepth/201-vision-monodepth.ipynb
Launch All Notebooks
--------------------------

104
docs/tutorials.md
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@ -115,35 +115,37 @@ Tutorials that explain how to optimize and quantize models with OpenVINO tools.
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| Notebook | Description |
+==============================================================================================================================+==================================================================================================================================+
| `105-language-quantize-bert <notebooks/105-language-quantize-bert-with-output.html>`__ | Optimize and quantize a pre-trained BERT model |
| `105-language-quantize-bert <notebooks/105-language-quantize-bert-with-output.html>`__ | Optimize and quantize a pre-trained BERT model. |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| `106-auto-device <notebooks/106-auto-device-with-output.html>`__ |br| |n106| | Demonstrates how to use AUTO Device |
| `106-auto-device <notebooks/106-auto-device-with-output.html>`__ |br| |n106| | Demonstrates how to use AUTO Device. |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| `107-speech-recognition-quantization <notebooks/107-speech-recognition-quantization-data2vec-with-output.html>`__ | Optimize and quantize a pre-trained Data2Vec speech model |
| `107-speech-recognition-quantization <notebooks/107-speech-recognition-quantization-data2vec-with-output.html>`__ | Optimize and quantize a pre-trained Data2Vec speech model. |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| `107-speech-recognition-quantization <notebooks/107-speech-recognition-quantization-wav2vec2-with-output.html>`__ | Optimize and quantize a pre-trained Wav2Vec2 speech model |
| `107-speech-recognition-quantization <notebooks/107-speech-recognition-quantization-wav2vec2-with-output.html>`__ | Optimize and quantize a pre-trained Wav2Vec2 speech model. |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| `108-gpu-device <notebooks/108-gpu-device-with-output.html>`__ | Working with GPUs in OpenVINO™ |
| `108-gpu-device <notebooks/108-gpu-device-with-output.html>`__ | Working with GPUs in OpenVINO™. |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| `109-performance-tricks <notebooks/109-latency-tricks-with-output.html>`__ | Performance tricks in OpenVINO™ |
| `109-performance-tricks <notebooks/109-latency-tricks-with-output.html>`__ | Performance tricks in OpenVINO™. |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| `110-ct-segmentation-quantize <notebooks/110-ct-segmentation-quantize-with-output.html>`__ |br| |n110| | Quantize a kidney segmentation model and show live inference |
| `110-ct-segmentation-quantize <notebooks/110-ct-scan-live-inference-with-output.html>`__ |br| |n110| | Live inference of a kidney segmentation model and benchmark CT-scan data with OpenVINO. |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| `111-yolov5-quantization-migration <notebooks/111-yolov5-quantization-migration-with-output.html>`__ | Migrate YOLOv5 POT API based quantization pipeline on Neural Network Compression Framework (NNCF) |
| `110-ct-segmentation-quantize <notebooks/110-ct-segmentation-quantize-nncf-with-output.html>`__ | Quantize a kidney segmentation model and show live inference. |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| `112-pytorch-post-training-quantization-nncf <notebooks/112-pytorch-post-training-quantization-nncf-with-output.html>`__ | Use Neural Network Compression Framework (NNCF) to quantize PyTorch model in post-training mode (without model fine-tuning) |
| `111-yolov5-quantization-migration <notebooks/111-yolov5-quantization-migration-with-output.html>`__ | Migrate YOLOv5 POT API based quantization pipeline on Neural Network Compression Framework (NNCF). |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| `113-image-classification-quantization <notebooks/113-image-classification-quantization-with-output.html>`__ |br| |n113| | Quantize mobilenet image classification |
| `112-pytorch-post-training-quantization-nncf <notebooks/112-pytorch-post-training-quantization-nncf-with-output.html>`__ | Use Neural Network Compression Framework (NNCF) to quantize PyTorch model in post-training mode (without model fine-tuning). |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| `114-quantization-simplified-mode <notebooks/114-quantization-simplified-mode-with-output.html>`__ |br| |n114| | Quantize Image Classification Models with POT in Simplified Mode |
| `113-image-classification-quantization <notebooks/113-image-classification-quantization-with-output.html>`__ |br| |n113| | Quantize MobileNet image classification. |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| `115-async-api <notebooks/115-async-api-with-output.html>`__ |br| |n115| | Use Asynchronous Execution to Improve Data Pipelining |
| `114-quantization-simplified-mode <notebooks/114-quantization-simplified-mode-with-output.html>`__ |br| |n114| | Quantize image classification models with POT in simplified mode. |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| `116-sparsity-optimization <notebooks/116-sparsity-optimization-with-output.html>`__ | Improve performance of sparse Transformer models |
| `115-async-api <notebooks/115-async-api-with-output.html>`__ |br| |n115| | Use asynchronous execution to improve data pipelining. |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| `117-model-server <notebooks/117-model-server-with-output.html>`__ | Improve performance of sparse Transformer models |
| `116-sparsity-optimization <notebooks/116-sparsity-optimization-with-output.html>`__ | Improve performance of sparse Transformer models. |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| `118-optimize-preprocessing <notebooks/118-optimize-preprocessing-with-output.html>`__ | Improve performance of image preprocessing step |
| `117-model-server <notebooks/117-model-server-with-output.html>`__ | Improve performance of sparse Transformer models. |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| `118-optimize-preprocessing <notebooks/118-optimize-preprocessing-with-output.html>`__ | Improve performance of image preprocessing step. |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
@ -181,7 +183,9 @@ Demos that demonstrate inference on a particular model.
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `202-vision-superresolution-video <notebooks/202-vision-superresolution-video-with-output.html>`__ |br| |n202v| | Turn 360p into 1080p video using a super resolution model. | |n202v-img1| → |n202v-img2| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `203-meter-reader <notebooks/203-meter-reader-with-output.html>`__ |br| |n203| | PaddlePaddle pre-trained models to read industrial meter's value | |n203-img1| |
| `203-meter-reader <notebooks/203-meter-reader-with-output.html>`__ |br| |n203| | PaddlePaddle pre-trained models to read industrial meter's value. | |n203-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `204-segmenter-semantic-segmentation <notebooks/204-segmenter-semantic-segmentation-with-output.html>`__ | Semantic segmentation with OpenVINO™ using Segmenter. | |n204-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `206-vision-paddlegan-anime <notebooks/206-vision-paddlegan-anime-with-output.html>`__ | Turn an image into anime using a GAN. | |n206-img1| → |n206-img2| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
@ -189,51 +193,55 @@ Demos that demonstrate inference on a particular model.
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `208-optical-character-recognition <notebooks/208-optical-character-recognition-with-output.html>`__ | Annotate text on images using text recognition resnet. | |n208-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `212-pyannote-speaker-diarization <notebooks/212-pyannote-speaker-diarization-with-output.html>`__ | Run inference on speaker diarization pipeline | |n212-img1| |
| `212-pyannote-speaker-diarization <notebooks/212-pyannote-speaker-diarization-with-output.html>`__ | Run inference on speaker diarization pipeline. | |n212-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `213-question-answering <notebooks/213-question-answering-with-output.html>`__ |br| |n213| | Answer your questions basing on a context. | |n213-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `214-grammar-correction <notebooks/214-grammar-correction-with-output.html>`__ | Grammatical Error Correction with OpenVINO | |
| `214-grammar-correction <notebooks/214-grammar-correction-with-output.html>`__ | Grammatical error correction with OpenVINO. | |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `217-vision-deblur <notebooks/217-vision-deblur-with-output.html>`__ |br| |n217| | Deblur Images with DeblurGAN-v2. | |n217-img1| |
| `217-vision-deblur <notebooks/217-vision-deblur-with-output.html>`__ |br| |n217| | Deblur images with DeblurGAN-v2. | |n217-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `219-knowledge-graphs-conve <notebooks/219-knowledge-graphs-conve-with-output.html>`__ |br| |n219| | Optimize the knowledge graph embeddings model (ConvE) with OpenVINO | |
| `219-knowledge-graphs-conve <notebooks/219-knowledge-graphs-conve-with-output.html>`__ |br| |n219| | Optimize the knowledge graph embeddings model (ConvE) with OpenVINO. | |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `220-yolov5-accuracy-check-and-quantization <notebooks/220-yolov5-accuracy-check-and-quantization-with-output.html>`__ | Quantize the Ultralytics YOLOv5 model and check accuracy using the OpenVINO POT API | |n220-img1| |
| `221-machine-translation <notebooks/221-machine-translation-with-output.html>`__ |br| |n221| | Real-time translation from English to German. | |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `221-machine-translation <notebooks/221-machine-translation-with-output.html>`__ |br| |n221| | Real-time translation from English to German | |
| `222-vision-image-colorization <notebooks/222-vision-image-colorization-with-output.html>`__ |br| |n222| | Use pre-trained models to colorize black & white images using OpenVINO. | |n222-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `222-vision-image-colorization <notebooks/222-vision-image-colorization-with-output.html>`__ |br| |n222| | Use pre-trained models to colorize black & white images using OpenVINO | |n222-img1| |
| `223-text-prediction <notebooks/223-text-prediction-with-output.html>`__ | Use pre-trained models to perform text prediction on an input sequence. | |n223-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `223-text-prediction <notebooks/223-text-prediction-with-output.html>`__ | Use pretrained models to perform text prediction on an input sequence | |n223-img1| |
| `224-3D-segmentation-point-clouds <notebooks/224-3D-segmentation-point-clouds-with-output.html>`__ | Process point cloud data and run 3D Part Segmentation with OpenVINO. | |n224-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `224-3D-segmentation-point-clouds <notebooks/224-3D-segmentation-point-clouds-with-output.html>`__ | Process point cloud data and run 3D Part Segmentation with OpenVINO | |n224-img1| |
| `225-stable-diffusion-text-to-image <notebooks/225-stable-diffusion-text-to-image-with-output.html>`__ | Text-to-image generation with Stable Diffusion method. | |n225-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `225-stable-diffusion-text-to-image <notebooks/225-stable-diffusion-text-to-image-with-output.html>`__ | Text-to-image generation with Stable Diffusion method | |n225-img1| |
| `226-yolov7-optimization <notebooks/226-yolov7-optimization-with-output.html>`__ | Optimize YOLOv7, using NNCF PTQ API. | |n226-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `226-yolov7-optimization <notebooks/226-yolov7-optimization-with-output.html>`__ | Optimize YOLOv7 using NNCF PTQ API | |n226-img1| |
| `227-whisper-subtitles-generation <notebooks/227-whisper-subtitles-generation-with-output.html>`__ | Generate subtitles for video with OpenAI Whisper and OpenVINO. | |n227-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `227-whisper-subtitles-generation <notebooks/227-whisper-subtitles-generation-with-output.html>`__ | Generate subtitles for video with OpenAI Whisper and OpenVINO | |n227-img1| |
| `228-clip-zero-shot-image-classification <notebooks/228-clip-zero-shot-image-classification-with-output.html>`__ | Perform Zero-shot image classification with CLIP and OpenVINO. | |n228-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `228-clip-zero-shot-image-classification <notebooks/228-clip-zero-shot-image-classification-with-output.html>`__ | Perform Zero-shot Image Classification with CLIP and OpenVINO | |n228-img1| |
| `229-distilbert-sequence-classification <notebooks/229-distilbert-sequence-classification-with-output.html>`__ |br| |n229| | Sequence classification with OpenVINO. | |n229-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `229-distilbert-sequence-classification <notebooks/229-distilbert-sequence-classification-with-output.html>`__ |br| |n229| | Sequence Classification with OpenVINO | |n229-img1| |
| `230-yolov8-optimization <notebooks/230-yolov8-optimization-with-output.html>`__ | Optimize YOLOv8, using NNCF PTQ API. | |n230-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `230-yolov8-optimization <notebooks/230-yolov8-optimization-with-output.html>`__ | Optimize YOLOv8 using NNCF PTQ API | |n230-img1| |
| `231-instruct-pix2pix-image-editing <notebooks/231-instruct-pix2pix-image-editing-with-output.html>`__ | Image editing with InstructPix2Pix. | |n231-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `231-instruct-pix2pix-image-editing <notebooks/231-instruct-pix2pix-image-editing-with-output.html>`__ | Image editing with InstructPix2Pix | |n231-img1| |
| `232-clip-language-saliency-map <notebooks/232-clip-language-saliency-map-with-output.html>`__ | Language-visual saliency with CLIP and OpenVINO™. | |n232-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `232-clip-language-saliency-map <notebooks/232-clip-language-saliency-map-with-output.html>`__ | Language-Visual Saliency with CLIP and OpenVINO™ | |n232-img1| |
| `233-blip-visual-language-processing <notebooks/233-blip-visual-language-processing-with-output.html>`__ | Visual question answering and image captioning using BLIP and OpenVINO™. | |n233-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `233-blip-visual-language-processing <notebooks/233-blip-visual-language-processing-with-output.html>`__ | Visual Question Answering and Image Captioning using BLIP and OpenVINO™ | |n233-img1| |
| `234-encodec-audio-compression <notebooks/234-encodec-audio-compression-with-output.html>`__ | Audio compression with EnCodec and OpenVINO™. | |n234-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `234-encodec-audio-compression <notebooks/234-encodec-audio-compression-with-output.html>`__ | Audio compression with EnCodec and OpenVINO™ | |n234-img1| |
| `235-controlnet-stable-diffusion <notebooks/235-controlnet-stable-diffusion-with-output.html>`__ | A text-to-image generation with ControlNet Conditioning and OpenVINO™. | |n235-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `235-controlnet-stable-diffusion <notebooks/235-controlnet-stable-diffusion-with-output.html>`__ | A Text-to-Image Generation with ControlNet Conditioning and OpenVINO™ | |n235-img1| |
| `236-stable-diffusion-v2 <notebooks/236-stable-diffusion-v2-infinite-zoom-with-output.html>`__ | Text-to-image generation and Infinite Zoom with Stable Diffusion v2 and OpenVINO™. | |n236-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `236-stable-diffusion-v2 <notebooks/236-stable-diffusion-v2-text-to-image-with-output.html>`__ | Text-to-Image Generation and Infinite Zoom with Stable Diffusion v2 and OpenVINO™ | |n236-img1| |
| `236-stable-diffusion-v2 <notebooks/236-stable-diffusion-v2-text-to-image-with-output.html>`__ | Text-to-image generation with Stable Diffusion v2 and OpenVINO™. | |n236-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `237-segment-anything <notebooks/237-segment-anything-with-output.html>`__ | Prompt based object segmentation mask generation using Segment Anything and OpenVINO™ | |n237-img1| |
| `237-segment-anything <notebooks/237-segment-anything-with-output.html>`__ | Prompt based object segmentation mask generation, using Segment Anything and OpenVINO™. | |n237-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `238-deep-floyd-if <notebooks/238-deep-floyd-if-with-output.html>`__ | Text-to-image generation with DeepFloyd IF and OpenVINO™. | |n238-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `239-image-bind <notebooks/239-image-bind-with-output.html>`__ | Binding multimodal data, using ImageBind and OpenVINO™. | |n239-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
@ -250,10 +258,6 @@ Tutorials that include code to train neural networks.
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| Notebook | Description | Preview |
+===============================================================================================================================+============================================================================================================================================+===========================================+
| `301-tensorflow-training-openvino <notebooks/301-tensorflow-training-openvino-with-output.html>`__ | Train a flower classification model from TensorFlow, then convert to OpenVINO IR. | |n301-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `301-tensorflow-training-openvino-pot <notebooks/301-tensorflow-training-openvino-pot-with-output.html>`__ | Use Post-training Optimization Tool (POT) to quantize the flowers model. | |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `302-pytorch-quantization-aware-training <notebooks/302-pytorch-quantization-aware-training-with-output.html>`__ | Use Neural Network Compression Framework (NNCF) to quantize PyTorch model. | |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `305-tensorflow-quantization-aware-training <notebooks/305-tensorflow-quantization-aware-training-with-output.html>`__ | Use Neural Network Compression Framework (NNCF) to quantize TensorFlow model. | |
@ -278,13 +282,13 @@ Live inference demos that run on a webcam or video files.
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `403-action-recognition-webcam <notebooks/403-action-recognition-webcam-with-output.html>`__ |br| |n403| | Human action recognition with a webcam or video file. | |n403-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `404-style-transfer-webcam <notebooks/404-style-transfer-with-output.html>`__ |br| |n404| | Style Transfer with a webcam or video file | |n404-img1| |
| `404-style-transfer-webcam <notebooks/404-style-transfer-with-output.html>`__ |br| |n404| | Style transfer with a webcam or video file. | |n404-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `405-paddle-ocr-webcam <notebooks/405-paddle-ocr-webcam-with-output.html>`__ |br| |n405| | OCR with a webcam or video file | |n405-img1| |
| `405-paddle-ocr-webcam <notebooks/405-paddle-ocr-webcam-with-output.html>`__ |br| |n405| | OCR with a webcam or video file. | |n405-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `406-3D-pose-estimation-webcam <notebooks/406-3D-pose-estimation-with-output.html>`__ |br| |n406| | 3D display of human pose estimation with a webcam or video file | |n406-img1| |
| `406-3D-pose-estimation-webcam <notebooks/406-3D-pose-estimation-with-output.html>`__ |br| |n406| | 3D display of human pose estimation with a webcam or video file. | |n406-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| `407-person-tracking-webcam <notebooks/407-person-tracking-with-output.html>`__ |br| |n407| | Person tracking with a webcam or video file | |n407-img1| |
| `407-person-tracking-webcam <notebooks/407-person-tracking-with-output.html>`__ |br| |n407| | Person tracking with a webcam or video file. | |n407-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
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