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Dismiss alert {{ message }} pipeless-ai / pipeless Public * Notifications * Fork 17 * Star 284 An open-source computer vision framework to build and deploy apps in minutes without worrying about multimedia pipelines pipeless.ai License Apache-2.0 license 284 stars 17 forks Activity Star Notifications * Code * Issues 6 * Pull requests 0 * Discussions * Actions * Projects 0 * Security * Insights More * Code * Issues * Pull requests * Discussions * Actions * Projects * Security * Insights pipeless-ai/pipeless This commit does not belong to any branch on this repository, and may belong to a fork outside of the repository. main Switch branches/tags [ ] Branches Tags Could not load branches Nothing to show {{ refName }} default View all branches Could not load tags Nothing to show {{ refName }} default View all tags Name already in use A tag already exists with the provided branch name. 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Latest commit @miguelaeh miguelaeh fix(workflow): Set HOMEBREW_NO_INSTALLED_DEPENDENTS_CHECK ... 4d140a6 Nov 16, 2023 fix(workflow): Set HOMEBREW_NO_INSTALLED_DEPENDENTS_CHECK Signed-off-by: Miguel A. Cabrera Minagorri 4d140a6 Git stats * 487 commits Files Permalink Failed to load latest commit information. Type Name Latest commit message Commit time .github fix(workflow): Set HOMEBREW_NO_INSTALLED_DEPENDENTS_CHECK November 16, 2023 12:25 assets Delete old gif file November 15, 2023 14:46 examples fix(examples): Remove unneeded line November 12, 2023 20:16 models build(deps): Bump werkzeug from 2.3.7 to 3.0.1 in /models/tensorflow November 13, 2023 17:50 package Remove uuidgen installation November 14, 2023 14:29 pipeless Bump version in Cargo.toml November 15, 2023 18:37 .gitignore Add pipeless 1.0 November 8, 2023 11:25 CODE_OF_CONDUCT.md Create CODE_OF_CONDUCT.md September 13, 2023 12:13 CONTRIBUTING.md Create CONTRIBUTING.md September 13, 2023 12:21 LICENSE Update copyright notice on licenses August 19, 2023 17:12 README.md Add alt to README img November 15, 2023 14:51 SECURITY.md Fix some typos and unify concepts in docs October 8, 2023 14:39 install.sh Update containers to Pipeless v1 November 14, 2023 14:27 View code [ ] Pipeless Requirements [?] Installation [?] Using docker Getting Started Examples Notable Changes Contributing License Apache License 2.0 Summary README.md [pipeless-4] Pipeless [6874747073] [6874747073] [6874747073] [6874747073] [6874747073] Easily create, deploy and run computer vision applications. Loading video... Pipeless is an open-source computer vision framework to create and deploy applications without the complexity of building and maintaining multimedia pipelines. It ships everything you need to create and deploy efficient computer vision applications that work in real-time in just minutes. Pipeless is inspired by modern serverless technologies. It provides the development experience of serverless frameworks applied to computer vision. You provide some functions that are executed for new video frames and Pipeless takes care of everything else. You can easily use industry-standard models, such as YOLO, or load your custom model in one of the supported inference runtimes. Pipeless ships some of the most popular inference runtimes, such as the ONNX Runtime, allowing you to run inference with high performance on CPU or GPU out-of-the-box. You can deploy your Pipeless application to edge and IoT devices or the cloud. We provide several tools for the deployment, including container images. The following is a non-exhaustive set of relevant features: * Multi-stream support: process several streams at the same time. * Dynamic stream configuration: add, edit, and remove streams on the fly via a CLI or REST API (more adapters to come). * Multi-language support: you can Write your hooks in several languages, including Python. * Dynamic processing steps: you can add any number of steps to your stream processing, and even modify those steps dynamically. * Highly parallelized: do not worry about multi-threading and/or multi-processing, Pipeless takes care of that for you. * Several inference runtimes supported: Provide a model and select one of the supported inference runtimes to run it out-of-the-box in CPU or GPUs. We support CUDA, TensorRT, OpenVINO, CoreML, and more to come. * Well-defined project structure and highly reusable code: Pipeless uses the file system structure to load processing stages and hooks, helping you organize the code in highly reusable boxes. Each stage is a directory, each hook is defined on its own file. Join our community and contribute to making the lives of computer vision developers easier! Requirements [?] * Python. Pre-built binaries are linked to Python 3.11 in Linux and 3.12 in macOS. Just provide the --build flag to the install script if you have a different version (or update your version and use a pre-built binary). * Gstreamer 1.20.3. Verify with gst-launch-1.0 --gst-version. Installation instructions here Installation [?] curl https://raw.githubusercontent.com/pipeless-ai/pipeless/main/install.sh | bash Find more information and installation options here. Using docker Instead of installing locally, you can alternatively use docker and save the time of installing dependencies: docker run miguelaeh/pipeless --help Find the whole container documentation here. Getting Started Init a project: pipeless init my_project --template scaffold cd my_project Start Pipeless: pipeless start --stages-dir . Provide a stream: pipeless add stream --input-uri "https://pipeless-public.s3.eu-west-3.amazonaws.com/cats.mp4" --output-uri "screen" --frame-path "my-stage" Check the complete getting started guide or plunge into the complete documentation. Examples You can find some examples under the examples directory. Just copy those folders inside your project and play with them. Find here the whole list of examples and step by step guides. Notable Changes Notable changes indicate important changes between versions. Please check the whole list of notable changes. Contributing Thanks for your interest in contributing! Contributions are welcome and encouraged. While we're working on creating detailed contributing guidelines, here are a few general steps to get started: 1. Fork this repository. 2. Create a new branch: git checkout -b feature-branch. 3. Make your changes and commit them: git commit -m 'Add new feature'. 4. Push your changes to your fork: git push origin feature-branch. 5. Open a GitHub pull request describing your changes. We appreciate your help in making this project better! Please note that for major changes or new features, it's a good idea to discuss them in an issue first so we can coordinate efforts. License This project is licensed under the Apache License 2.0. Apache License 2.0 Summary The Apache License 2.0 is a permissive open-source license that allows you to use, modify, and distribute this software for personal or commercial purposes. It comes with certain obligations, including providing attribution to the original authors and including the original license text in your distributions. For the full license text, please refer to the Apache License 2.0. About An open-source computer vision framework to build and deploy apps in minutes without worrying about multimedia pipelines pipeless.ai Topics python machine-learning cloud video computer-vision deep-learning gstreamer ffmpeg multimedia cuda artificial-intelligence nvidia yolo object-detection deepstream hacktoberfest inference-server tensorrt vision-framework multimedia-applications Resources Readme License Apache-2.0 license Code of conduct Code of conduct Security policy Security policy Activity Stars 284 stars Watchers 3 watching Forks 17 forks Report repository Releases 43 v1.0.2 Latest Nov 16, 2023 + 42 releases Packages 0 No packages published Contributors 7 * * * * * * * Languages * Rust 82.5% * Shell 11.2% * Python 3.9% * Smarty 1.9% * Dockerfile 0.5% Footer (c) 2023 GitHub, Inc. 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