2f95de3239
port https://github.com/openvinotoolkit/openvino/pull/14637 Shift to separating the Workflow section, including moving Run and Optimize inference inside Deploy locally change several article and menu titles minor additional restructuring minor content tweaks remove optimization introduction (may be brought back in parts later) * several link fixes * additional link fixes
60 KiB
Interactive Tutorials (Python)
@sphinxdirective
.. _notebook tutorials:
.. meta:: :description: A collection of Python tutorials run on Jupyter notebooks. The tutorials explain how to use OpenVINO™ toolkit for optimized deep learning inference. :keywords: OpenVINO™ toolkit, Jupyter, Jupyter notebooks, tutorials, Python API, Python, deep learning, inference, model inference, infer a model, Binder, object detection, quantization, image classification, speech recognition, OCR, OpenVINO IR, deep learning model, AI, neural networks
.. toctree:: :maxdepth: 2 :caption: Notebooks :hidden:
notebooks-installation notebooks/notebooks
This collection of Python tutorials are written for running on Jupyter notebooks. The tutorials provide an introduction to the OpenVINO™ toolkit and explain how to use the Python API and tools for optimized deep learning inference. You can run the code one section at a time to see how to integrate your application with OpenVINO libraries.
Notebooks with a |binder logo| button can be run without installing anything.
Once you have found the tutorial of your interest, just click the button next to
the name of it and Binder <https://mybinder.org/>__ will start it in a new tab of a browser.
Binder is a free online service with limited resources (for more information about it,
see the Additional Resources <#-additional-resources>__ section).
.. note::
For the best performance, more control and resources, you should run the notebooks locally.
Follow the Installation Guide <notebooks-installation.html>__ in order to get information
on how to run and manage the notebooks on your machine.
Contents:
-
Getting Started <#-getting-started>__First steps with OpenVINO <#-first-steps>__Convert & Optimize <#-convert--optimize>__Model Demos <#-model-demos>__Model Training <#-model-training>__Live Demos <#-live-demos>__Recommended Tutorials <#-recommended-tutorials>__Additional Resources <#-additional-resources>__Contributors <#-contributors>__
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Getting Started_
The Jupyter notebooks are categorized into four classes, select one related to your needs or give them all a try. Good Luck!
.. raw:: html
First steps with OpenVINO_
Brief tutorials that demonstrate how to use Python API for inference in OpenVINO.
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| Notebook | Description | Preview |
+===============================================================================================================================+============================================================================================================================================+===========================================+
| 001-hello-world <notebooks/001-hello-world-with-output.html>__ |br| |n001| | Classify an image with OpenVINO. | |n001-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| 002-openvino-api <notebooks/002-openvino-api-with-output.html>__ |br| |n002| | Learn the OpenVINO Python API. | |n002-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| 003-hello-segmentation <notebooks/003-hello-segmentation-with-output.html>__ |br| |n003| | Semantic segmentation with OpenVINO. | |n003-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| 004-hello-detection <notebooks/004-hello-detection-with-output.html>__ |br| |n004| | Text detection with OpenVINO. | |n004-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
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Convert & Optimize_
Tutorials that explain how to optimize and quantize models with OpenVINO tools.
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| Notebook | Description | Preview |
+===============================================================================================================================+============================================================================================================================================+===========================================+
| 101-tensorflow-to-openvino <notebooks/101-tensorflow-to-openvino-with-output.html>__ |br| |n101| | Convert TensorFlow models to OpenVINO IR. | |n101-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| 102-pytorch-onnx-to-openvino <notebooks/102-pytorch-onnx-to-openvino-with-output.html>__ | Convert PyTorch models to OpenVINO IR. | |n102-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| 103-paddle-onnx-to-openvino <notebooks/103-paddle-onnx-to-openvino-classification-with-output.html>__ |br| |n103| | Convert PaddlePaddle models to OpenVINO IR. | |n103-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| 104-model-tools <notebooks/104-model-tools-with-output.html>__ |br| |n104| | Download, convert and benchmark models from Open Model Zoo. | |n104-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
.. dropdown:: Explore more notebooks here.
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| Notebook | Description |
+==============================================================================================================================+==================================================================================================================================+
| 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>__ | Demonstrates how to use AUTO Device |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| 107-speech-recognition-quantization <notebooks/107-speech-recognition-quantization-with-output.html>__ | Optimize and quantize a pre-trained Wav2Vec2 speech model |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| 110-ct-segmentation-quantize <notebooks/110-ct-segmentation-quantize-with-output.html>__ | Quantize a kidney segmentation model and show live inference |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| 111-detection-quantization <notebooks/111-detection-quantization-with-output.html>__ |br| |n111| | Quantize an object detection model |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| 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) |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| 113-image-classification-quantization <notebooks/113-image-classification-quantization-with-output.html>__ | Quantize mobilenet image classification |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| 114-quantization-simplified-mode <notebooks/114-quantization-simplified-mode-with-output.html>__ | Quantize Image Classification Models with POT in Simplified Mode |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
| 115-async-api <notebooks/115-async-api-with-output.html>__ | Use Asynchronous Execution to Improve Data Pipelining |
+------------------------------------------------------------------------------------------------------------------------------+----------------------------------------------------------------------------------------------------------------------------------+
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Model Demos_
Demos that demonstrate inference on a particular model.
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| Notebook | Description | Preview |
+===============================================================================================================================+============================================================================================================================================+===========================================+
| 210-ct-scan-live-inference <notebooks/210-ct-scan-live-inference-with-output.html>__ |br| |n210| | Show live inference on segmentation of CT-scan data. | |n210-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| 211-speech-to-text <notebooks/211-speech-to-text-with-output.html>__ |br| |n211| | Run inference on speech-to-text recognition model. | |n211-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| 208-optical-character-recognition <notebooks/208-optical-character-recognition-with-output.html>__ | Annotate text on images using text recognition resnet. | |n208-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| 209-handwritten-ocr <notebooks/209-handwritten-ocr-with-output.html>__ |br| |n209| | OCR for handwritten simplified Chinese and Japanese. | |n209-img1| |br| |chinese-text| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| 218-vehicle-detection-and-recognition <notebooks/218-vehicle-detection-and-recognition-with-output.html>__ | Use pre-trained models to detect and recognize vehicles and their attributes with OpenVINO. | |n218-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
.. dropdown:: Explore more notebooks below.
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| Notebook | Description | Preview |
+===============================================================================================================================+============================================================================================================================================+===========================================+
| 201-vision-monodepth <notebooks/201-vision-monodepth-with-output.html>__ |br| |n201| | Monocular depth estimation with images and video. | |n201-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| 202-vision-superresolution-image <notebooks/202-vision-superresolution-image-with-output.html>__ |br| |n202i| | Upscale raw images with a super resolution model. | |n202i-img1| → |n202i-img2| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| 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| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| 204-named-entity-recognition <notebooks/204-named-entity-recognition-with-output.html>__ |br| |n204| | Perform named entity recognition on simple text. | |n204-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| 205-vision-background-removal <notebooks/205-vision-background-removal-with-output.html>__ |br| |n205| | Remove and replace the background in an image using salient object detection. | |n205-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| 206-vision-paddlegan-anime <notebooks/206-vision-paddlegan-anime-with-output.html>__ |br| |n206| | Turn an image into anime using a GAN. | |n206-img1| → |n206-img2| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| 207-vision-paddlegan-superresolution <notebooks/207-vision-paddlegan-superresolution-with-output.html>__ |br| |n207| | Upscale small images with superresolution using a PaddleGAN model. | |n207-img1| → |n207-img2| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| 212-onnx-style-transfer <notebooks/212-onnx-style-transfer-with-output.html>__ |br| |n212| | Transform images to five different styles with neural style transfer. | |n212-img1| → |n212-img2| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| 214-vision-paddle-classification <notebooks/214-vision-paddle-classification-with-output.html>__ |br| |n214| | PaddlePaddle Image Classification with OpenVINO. | |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| 215-image-inpainting <notebooks/215-image-inpainting-with-output.html>__ | Fill missing pixels with image in-painting. | |n215-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| 216-license-plate-recognition <notebooks/216-license-plate-recognition-with-output.html>__ | Recognize Chinese license plates in traffic. | |n216-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>__ | 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>__ | Real-time translation from English to German | |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| 222-vision-image-colorization <notebooks/222-vision-image-colorization-with-output.html>__ | Use pre-trained models to colorize black & white images using OpenVINO | |n222-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| 223-gpt2-text-prediction <notebooks/223-gpt2-text-prediction-with-output.html>__ | Use GPT-2 to perform text prediction on an input sequence | |n223-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
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Model Training_
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. | |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
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Live Demos_
Live inference demos that run on a webcam or video files.
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| Notebook | Description | Preview |
+===============================================================================================================================+============================================================================================================================================+===========================================+
| 401-object-detection-webcam <notebooks/401-object-detection-with-output.html>__ |br| |n401| | Object detection with a webcam or video file. | |n401-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| 402-pose-estimation-webcam <notebooks/402-pose-estimation-with-output.html>__ |br| |n402| | Human pose estimation with a webcam or video file. | |n402-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| 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| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| 405-paddle-ocr-webcam <notebooks/405-paddle-ocr-webcam-with-output.html>__ |br| |n405| | OCR with a webcam or video file | |n405-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
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Recommended Tutorials_
The following tutorials are guaranteed to provide a great experience with inference in OpenVINO:
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| Notebook | | Preview |
+===============================================================================================================================+============================================================================================================================================+===========================================+
| Vision-monodepth <notebooks/201-vision-monodepth-with-output.html>__ |br| |n201| | Monocular depth estimation with images and video. | |n201-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| CT-scan-live-inference <notebooks/210-ct-scan-live-inference-with-output.html>__ |br| |n210| | Show live inference on segmentation of CT-scan data. | |n210-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| Object-detection-webcam <notebooks/401-object-detection-with-output.html>__ |br| |n401| | Object detection with a webcam or video file. | |n401-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| Pose-estimation-webcam <notebooks/402-pose-estimation-with-output>__ |br| |n402| | Human pose estimation with a webcam or video file. | |n402-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
| Action-recognition-webcam <notebooks/403-action-recognition-webcam-with-output.html>__ |br| |n403| | Human action recognition with a webcam or video file. | |n403-img1| |
+-------------------------------------------------------------------------------------------------------------------------------+--------------------------------------------------------------------------------------------------------------------------------------------+-------------------------------------------+
.. note::
If there are any issues while running the notebooks, refer to the Troubleshooting and FAQ sections in the Installation Guide <notebooks-installation.html>__ or start a GitHub
discussion <https://github.com/openvinotoolkit/openvino_notebooks/discussions>__.
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Additional Resources_
OpenVINO™ Notebooks - Github Repository <https://github.com/openvinotoolkit/openvino_notebooks/blob/main/README.md>_Binder documentation <https://mybinder.readthedocs.io/en/latest/>_
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Contributors_
|contributors|
Made with contributors-img <https://contrib.rocks>__.
.. |br| raw:: html
.. |chinese-text| raw:: html
的人不一了是他有为在责新中任自之我们
.. |contributors| image:: https://contrib.rocks/image?repo=openvinotoolkit/openvino_notebooks :target: https://github.com/openvinotoolkit/openvino_notebooks/graphs/contributors .. |n001-img1| image:: https://user-images.githubusercontent.com/36741649/127170593-86976dc3-e5e4-40be-b0a6-206379cd7df5.jpg :target: https://user-images.githubusercontent.com/36741649/127170593-86976dc3-e5e4-40be-b0a6-206379cd7df5.jpg .. |n002-img1| image:: https://user-images.githubusercontent.com/15709723/127787560-d8ec4d92-b4a0-411f-84aa-007e90faba98.png :target: https://user-images.githubusercontent.com/15709723/127787560-d8ec4d92-b4a0-411f-84aa-007e90faba98.png .. |n003-img1| image:: https://user-images.githubusercontent.com/15709723/128290691-e2eb875c-775e-4f4d-a2f4-15134044b4bb.png :target: https://user-images.githubusercontent.com/15709723/128290691-e2eb875c-775e-4f4d-a2f4-15134044b4bb.png .. |n004-img1| image:: 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