This is the Windows app named PyTorchVideo whose latest release can be downloaded as PyTorchVideoVersion0.1.3sourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named PyTorchVideo with OnWorks for free.
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- 3. I-upload ang application na ito sa naturang filemanager.
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- 6. I-download ang application at i-install ito.
- 7. I-download ang Wine mula sa iyong mga Linux distributions software repository. Kapag na-install na, maaari mong i-double click ang app upang patakbuhin ang mga ito gamit ang Wine. Maaari mo ring subukan ang PlayOnLinux, isang magarbong interface sa ibabaw ng Wine na tutulong sa iyong mag-install ng mga sikat na programa at laro sa Windows.
Ang alak ay isang paraan upang patakbuhin ang software ng Windows sa Linux, ngunit walang kinakailangang Windows. Ang alak ay isang open-source na layer ng compatibility ng Windows na maaaring direktang magpatakbo ng mga program sa Windows sa anumang desktop ng Linux. Sa totoo lang, sinusubukan ng Wine na muling ipatupad ang sapat na Windows mula sa simula upang mapatakbo nito ang lahat ng mga Windows application na iyon nang hindi talaga nangangailangan ng Windows.
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PyTorchVideo
DESCRIPTION
PyTorchVideo is a deep learning library for video understanding, providing modular components and pretrained models for tasks like action recognition, video classification, detection, and self-supervised learning. It is tightly integrated with PyTorch and PyTorch Lightning, offering flexible APIs for building and training spatiotemporal networks. The library includes efficient implementations of state-of-the-art architectures such as SlowFast, X3D, and MViT, optimized for both research prototyping and production inference. It supports video I/O pipelines, data augmentation, distributed training, and mixed precision computation for large-scale experiments. PyTorchVideo also connects seamlessly with other Meta AI tools such as Detectron2 and PyTorch3D for multimodal video analysis. Designed to accelerate research and deployment, it serves as a unified framework for reproducible, high-performance video AI development.
Mga tampok
- Modular library for video understanding with PyTorch integration
- Pretrained models for action recognition, detection, and classification
- Efficient data loaders and augmentation pipelines for large datasets
- Optimized implementations of SlowFast, X3D, and MViT architectures
- Distributed training, mixed precision, and production-ready inference tools
- Compatibility with Detectron2 and PyTorch3D for multimodal workflows
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Kategorya
This is an application that can also be fetched from https://sourceforge.net/projects/pytorchvideo.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.