π― Trackers Library is Officially Released! π
If you're working in computer vision and object tracking, this one's for you!
π‘ Trackers is a powerful open-source library with support for a wide range of detection models and tracking algorithms:
β Plug-and-play compatibility with detection models from:
Roboflow Inference, Hugging Face Transformers, Ultralytics, MMDetection, and more!
β Tracking algorithms supported:
SORT, DeepSORT, and advanced trackers like StrongSORT, BoTβSORT, ByteTrack, OCβSORT β with even more coming soon!
π§© Released under the permissive Apache 2.0 license β free for everyone to use and contribute.
π Huge thanks to Piotr Skalski for co-developing this library, and to Raif Olson and Onuralp SEZER for their outstanding contributions!
π Links:
π GitHub
π Docs
π Quick-start notebooks for SORT and DeepSORT are linked ππ»
https://www.linkedin.com/posts/skalskip92_trackers-library-is-out-plugandplay-activity-7321128111503253504-3U6-?utm_source=share&utm_medium=member_desktop&rcm=ACoAAEXwhVcBcv2n3wq8JzEai3TfWmKLRLTefYo
#ComputerVision #ObjectTracking #OpenSource #DeepLearning #AI
π‘ By: https://xn--r1a.website/DataScienceN
If you're working in computer vision and object tracking, this one's for you!
π‘ Trackers is a powerful open-source library with support for a wide range of detection models and tracking algorithms:
β Plug-and-play compatibility with detection models from:
Roboflow Inference, Hugging Face Transformers, Ultralytics, MMDetection, and more!
β Tracking algorithms supported:
SORT, DeepSORT, and advanced trackers like StrongSORT, BoTβSORT, ByteTrack, OCβSORT β with even more coming soon!
π§© Released under the permissive Apache 2.0 license β free for everyone to use and contribute.
π Huge thanks to Piotr Skalski for co-developing this library, and to Raif Olson and Onuralp SEZER for their outstanding contributions!
π Links:
π GitHub
π Docs
π Quick-start notebooks for SORT and DeepSORT are linked ππ»
https://www.linkedin.com/posts/skalskip92_trackers-library-is-out-plugandplay-activity-7321128111503253504-3U6-?utm_source=share&utm_medium=member_desktop&rcm=ACoAAEXwhVcBcv2n3wq8JzEai3TfWmKLRLTefYo
#ComputerVision #ObjectTracking #OpenSource #DeepLearning #AI
π‘ By: https://xn--r1a.website/DataScienceN
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Trackers Library is Out! | Piotr Skalski
Trackers Library is Out! π₯ π₯ π₯
- Plugβandβplay integration with detectors from Transformers, Inference, Ultralytics, PaddlePaddle, MMDetection, and more.
- Builtβin support for SORT and DeepSORT today, with StrongSORT, BoTβSORT, ByteTrack, OCβSORT, andβ¦
- Plugβandβplay integration with detectors from Transformers, Inference, Ultralytics, PaddlePaddle, MMDetection, and more.
- Builtβin support for SORT and DeepSORT today, with StrongSORT, BoTβSORT, ByteTrack, OCβSORT, andβ¦
π4β€1π₯1
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β Uses Segment Anything (SAM) by Meta for object segmentation
β Leverages Inpaint-Anything for realistic background generation
β Works in your browser with an intuitive Gradio UI
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π Description: Open-Source Chrome extension for AI-powered web automation. Run multi-agent workflows using your own LLM API key. Alternative to OpenAI Operator.
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π Description: π An open and lightweight modification to Windows, designed to optimize performance, privacy and usability.
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π Description: A collaborative note taking, wiki and documentation platform that scales. Built with Django and React.
π Repository URL: https://github.com/suitenumerique/docs
π Website: https://docs.numerique.gouv.fr
π Readme: https://github.com/suitenumerique/docs#readme
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π Repository URL: https://github.com/Fincept-Corporation/FinceptTerminal
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LiteParse v2.1 β the fastest PDF β Markdown parser in the world π
And at the same time, it's more accurate than any other open-source parser without using models (pymupdf4llm, opendataloader, pdf-inspector, markitdown) according to the results of three standardized benchmarks: olmOCR0-bench, opendataloader-bench, and ParseBench. π
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LiteParse repository: https://github.com/run-llama/liteparse
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And at the same time, it's more accurate than any other open-source parser without using models (pymupdf4llm, opendataloader, pdf-inspector, markitdown) according to the results of three standardized benchmarks: olmOCR0-bench, opendataloader-bench, and ParseBench. π
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The project is completely open (Apache 2.0 license) and free. It's available via CLI, Rust, Node.js, Python, and WASM, and can also be installed as an agent skill in one click. π οΈ
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