| Name | depthai-nodes JSON |
| Version |
0.3.2
JSON |
| download |
| home_page | None |
| Summary | Community on-host nodes for DepthAI. |
| upload_time | 2025-07-16 08:16:41 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | Apache License
Version 2.0, January 2004
http://www.apache.org/licenses/
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| keywords |
ml
postprocessing
luxonis
oak
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
depthai
opencv-python-headless
numpy
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# DepthAI Nodes
[](https://opensource.org/licenses/Apache-2.0)
[](https://codecov.io/gh/luxonis/depthai-nodes)
[](https://github.com/astral-sh/ruff)
[](https://github.com/PyCQA/docformatter)
[](https://github.com/psf/black)
## 🌟 Overview
DepthAI Nodes is a Python "contrib" library designed to simplify host-side development with a growing collection of modular, high-level nodes. These cover a range of common needs - from neural network post-processing and I/O patterns to utility nodes for faster prototyping. With just a few lines of code, you can scaffold sophisticated pipelines, saving time and reducing boilerplate. In order to use these nodes you need to have your pipeline written with `DepthAIv3`.
**NOTE**:
We are always listening to the community so feel free to report and feedback, issues or contribute to the library with our own host nodes.
## 📜 Table of Contents
- [🌟 Overview](#overview)
- [🛠️ Installation](#-installation)
- [📦 Content](#-content)
- [📨 Message](#-message)
- [🧩 Node](#-node)
- [🤝 Contributing](#-contributing)
## 🛠️ Installation
The `depthai_nodes` package is hosted on PyPI, so you can install it with `pip`.
To install the package, run:
```bash
pip install depthai-nodes
```
### Manual installation
If you want to manually install the package from the GitHub repository you can run:
```bash
git clone git@github.com:luxonis/depthai-nodes.git
```
and then inside the directory run:
```bash
pip install .
```
## 📦 Content
This library is organized into two primary modules, each focused on a specific aspect of working with DepthAI on the host side:
- `message` - Custom message types
- `node` - High-level, modular host-side nodes
### 📨 Message
The `message` module defines a set of extended message types designed to simplify working with outputs from various neural networks. These go beyond the standard DepthAI messages and include richer data structures for tasks such as object detection, segmentation, classification, pose estimation, and more.
These enhanced messages aim to reduce the boilerplate code needed for parsing and interpreting NN outputs, making it easier to plug them into visualization or processing pipelines. You can learn more about each message type in the dedicated [README](./depthai_nodes/message/README.md).
### 🧩 Node
The `node` module provides a collection of ready-to-use host-side nodes that abstract common processing patterns and tasks. These nodes fall into three main categories:
- **Parser nodes** - Handle post-processing for specific model architectures such as YOLO, MediaPipe, YuNet, etc.
- **Helper nodes** - Like ParsingNeuralNetwork and ParserGenerator which help manage simple or complex model outputs more efficiently.
- **Utility nodes** – Perform common operations like detection filtering, drawing overlays, applying segmentation colormaps, and more—all in just a few lines of code.
This modular approach allows you to rapidly prototype and scale complex applications with less effort while keeping your code clean and maintainable.
To read more about the nodes and see simple examples, please refer to the [nodes documentation](./depthai_nodes/node/README.md).
## 🤝 Contributing
If you want to contribute to this project, read the instructions in [CONTRIBUTING.md](./CONTRIBUTING.md)
Raw data
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"description": "# DepthAI Nodes\n\n[](https://opensource.org/licenses/Apache-2.0)\n\n\n[](https://codecov.io/gh/luxonis/depthai-nodes)\n\n[](https://github.com/astral-sh/ruff)\n[](https://github.com/PyCQA/docformatter)\n[](https://github.com/psf/black)\n\n## \ud83c\udf1f Overview\n\nDepthAI Nodes is a Python \"contrib\" library designed to simplify host-side development with a growing collection of modular, high-level nodes. These cover a range of common needs - from neural network post-processing and I/O patterns to utility nodes for faster prototyping. With just a few lines of code, you can scaffold sophisticated pipelines, saving time and reducing boilerplate. In order to use these nodes you need to have your pipeline written with `DepthAIv3`.\n\n**NOTE**:\nWe are always listening to the community so feel free to report and feedback, issues or contribute to the library with our own host nodes.\n\n## \ud83d\udcdc Table of Contents\n\n- [\ud83c\udf1f Overview](#overview)\n- [\ud83d\udee0\ufe0f Installation](#-installation)\n- [\ud83d\udce6 Content](#-content)\n - [\ud83d\udce8 Message](#-message)\n - [\ud83e\udde9 Node](#-node)\n- [\ud83e\udd1d Contributing](#-contributing)\n\n## \ud83d\udee0\ufe0f Installation\n\nThe `depthai_nodes` package is hosted on PyPI, so you can install it with `pip`.\n\nTo install the package, run:\n\n```bash\npip install depthai-nodes\n```\n\n### Manual installation\n\nIf you want to manually install the package from the GitHub repository you can run:\n\n```bash\ngit clone git@github.com:luxonis/depthai-nodes.git\n```\n\nand then inside the directory run:\n\n```bash\npip install .\n```\n\n## \ud83d\udce6 Content\n\nThis library is organized into two primary modules, each focused on a specific aspect of working with DepthAI on the host side:\n\n- `message` - Custom message types\n- `node` - High-level, modular host-side nodes\n\n### \ud83d\udce8 Message\n\nThe `message` module defines a set of extended message types designed to simplify working with outputs from various neural networks. These go beyond the standard DepthAI messages and include richer data structures for tasks such as object detection, segmentation, classification, pose estimation, and more.\n\nThese enhanced messages aim to reduce the boilerplate code needed for parsing and interpreting NN outputs, making it easier to plug them into visualization or processing pipelines. You can learn more about each message type in the dedicated [README](./depthai_nodes/message/README.md).\n\n### \ud83e\udde9 Node\n\nThe `node` module provides a collection of ready-to-use host-side nodes that abstract common processing patterns and tasks. These nodes fall into three main categories:\n\n- **Parser nodes** - Handle post-processing for specific model architectures such as YOLO, MediaPipe, YuNet, etc.\n- **Helper nodes** - Like ParsingNeuralNetwork and ParserGenerator which help manage simple or complex model outputs more efficiently.\n- **Utility nodes** \u2013 Perform common operations like detection filtering, drawing overlays, applying segmentation colormaps, and more\u2014all in just a few lines of code.\n\nThis modular approach allows you to rapidly prototype and scale complex applications with less effort while keeping your code clean and maintainable.\n\nTo read more about the nodes and see simple examples, please refer to the [nodes documentation](./depthai_nodes/node/README.md).\n\n## \ud83e\udd1d Contributing\n\nIf you want to contribute to this project, read the instructions in [CONTRIBUTING.md](./CONTRIBUTING.md)\n",
"bugtrack_url": null,
"license": "Apache License\n Version 2.0, January 2004\n http://www.apache.org/licenses/\n \n TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION\n \n 1. Definitions.\n \n \"License\" shall mean the terms and conditions for use, reproduction,\n and distribution as defined by Sections 1 through 9 of this document.\n \n \"Licensor\" shall mean the copyright owner or entity authorized by\n the copyright owner that is granting the License.\n \n \"Legal Entity\" shall mean the union of the acting entity and all\n other entities that control, are controlled by, or are under common\n control with that entity. For the purposes of this definition,\n \"control\" means (i) the power, direct or indirect, to cause the\n direction or management of such entity, whether by contract or\n otherwise, or (ii) ownership of fifty percent (50%) or more of the\n outstanding shares, or (iii) beneficial ownership of such entity.\n \n \"You\" (or \"Your\") shall mean an individual or Legal Entity\n exercising permissions granted by this License.\n \n \"Source\" form shall mean the preferred form for making modifications,\n including but not limited to software source code, documentation\n source, and configuration files.\n \n \"Object\" form shall mean any form resulting from mechanical\n transformation or translation of a Source form, including but\n not limited to compiled object code, generated documentation,\n and conversions to other media types.\n \n \"Work\" shall mean the work of authorship, whether in Source or\n Object form, made available under the License, as indicated by a\n copyright notice that is included in or attached to the work\n (an example is provided in the Appendix below).\n \n \"Derivative Works\" shall mean any work, whether in Source or Object\n form, that is based on (or derived from) the Work and for which the\n editorial revisions, annotations, elaborations, or other modifications\n represent, as a whole, an original work of authorship. For the purposes\n of this License, Derivative Works shall not include works that remain\n separable from, or merely link (or bind by name) to the interfaces of,\n the Work and Derivative Works thereof.\n \n \"Contribution\" shall mean any work of authorship, including\n the original version of the Work and any modifications or additions\n to that Work or Derivative Works thereof, that is intentionally\n submitted to Licensor for inclusion in the Work by the copyright owner\n or by an individual or Legal Entity authorized to submit on behalf of\n the copyright owner. For the purposes of this definition, \"submitted\"\n means any form of electronic, verbal, or written communication sent\n to the Licensor or its representatives, including but not limited to\n communication on electronic mailing lists, source code control systems,\n and issue tracking systems that are managed by, or on behalf of, the\n Licensor for the purpose of discussing and improving the Work, but\n excluding communication that is conspicuously marked or otherwise\n designated in writing by the copyright owner as \"Not a Contribution.\"\n \n \"Contributor\" shall mean Licensor and any individual or Legal Entity\n on behalf of whom a Contribution has been received by Licensor and\n subsequently incorporated within the Work.\n \n 2. Grant of Copyright License. Subject to the terms and conditions of\n this License, each Contributor hereby grants to You a perpetual,\n worldwide, non-exclusive, no-charge, royalty-free, irrevocable\n copyright license to reproduce, prepare Derivative Works of,\n publicly display, publicly perform, sublicense, and distribute the\n Work and such Derivative Works in Source or Object form.\n \n 3. Grant of Patent License. Subject to the terms and conditions of\n this License, each Contributor hereby grants to You a perpetual,\n worldwide, non-exclusive, no-charge, royalty-free, irrevocable\n (except as stated in this section) patent license to make, have made,\n use, offer to sell, sell, import, and otherwise transfer the Work,\n where such license applies only to those patent claims licensable\n by such Contributor that are necessarily infringed by their\n Contribution(s) alone or by combination of their Contribution(s)\n with the Work to which such Contribution(s) was submitted. If You\n institute patent litigation against any entity (including a\n cross-claim or counterclaim in a lawsuit) alleging that the Work\n or a Contribution incorporated within the Work constitutes direct\n or contributory patent infringement, then any patent licenses\n granted to You under this License for that Work shall terminate\n as of the date such litigation is filed.\n \n 4. Redistribution. You may reproduce and distribute copies of the\n Work or Derivative Works thereof in any medium, with or without\n modifications, and in Source or Object form, provided that You\n meet the following conditions:\n \n (a) You must give any other recipients of the Work or\n Derivative Works a copy of this License; and\n \n (b) You must cause any modified files to carry prominent notices\n stating that You changed the files; and\n \n (c) You must retain, in the Source form of any Derivative Works\n that You distribute, all copyright, patent, trademark, and\n attribution notices from the Source form of the Work,\n excluding those notices that do not pertain to any part of\n the Derivative Works; and\n \n (d) If the Work includes a \"NOTICE\" text file as part of its\n distribution, then any Derivative Works that You distribute must\n include a readable copy of the attribution notices contained\n within such NOTICE file, excluding those notices that do not\n pertain to any part of the Derivative Works, in at least one\n of the following places: within a NOTICE text file distributed\n as part of the Derivative Works; within the Source form or\n documentation, if provided along with the Derivative Works; or,\n within a display generated by the Derivative Works, if and\n wherever such third-party notices normally appear. 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Unless You explicitly state otherwise,\n any Contribution intentionally submitted for inclusion in the Work\n by You to the Licensor shall be under the terms and conditions of\n this License, without any additional terms or conditions.\n Notwithstanding the above, nothing herein shall supersede or modify\n the terms of any separate license agreement you may have executed\n with Licensor regarding such Contributions.\n \n 6. Trademarks. This License does not grant permission to use the trade\n names, trademarks, service marks, or product names of the Licensor,\n except as required for reasonable and customary use in describing the\n origin of the Work and reproducing the content of the NOTICE file.\n \n 7. Disclaimer of Warranty. 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We also recommend that a\n file or class name and description of purpose be included on the\n same \"printed page\" as the copyright notice for easier\n identification within third-party archives.\n \n Copyright [yyyy] [name of copyright owner]\n \n Licensed under the Apache License, Version 2.0 (the \"License\");\n you may not use this file except in compliance with the License.\n You may obtain a copy of the License at\n \n http://www.apache.org/licenses/LICENSE-2.0\n \n Unless required by applicable law or agreed to in writing, software\n distributed under the License is distributed on an \"AS IS\" BASIS,\n WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n See the License for the specific language governing permissions and\n limitations under the License.",
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