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Metadata-Version: 2.1 |
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Name: torchvision |
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Version: 0.22.1 |
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Summary: image and video datasets and models for torch deep learning |
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Home-page: https://github.com/pytorch/vision |
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Author: PyTorch Core Team |
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Author-email: soumith@pytorch.org |
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License: BSD |
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Requires-Python: >=3.9 |
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Description-Content-Type: text/markdown |
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License-File: LICENSE |
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Requires-Dist: numpy |
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Requires-Dist: torch (==2.7.1) |
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Requires-Dist: pillow (!=8.3.*,>=5.3.0) |
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Provides-Extra: gdown |
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Requires-Dist: gdown (>=4.7.3) |
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Provides-Extra: scipy |
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Requires-Dist: scipy |
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# torchvision |
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[](https://pepy.tech/project/torchvision) |
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[](https://pytorch.org/vision/stable/index.html) |
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The torchvision package consists of popular datasets, model architectures, and common image transformations for computer |
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vision. |
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## Installation |
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Please refer to the [official |
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instructions](https://pytorch.org/get-started/locally/) to install the stable |
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versions of `torch` and `torchvision` on your system. |
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To build source, refer to our [contributing |
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page](https://github.com/pytorch/vision/blob/main/CONTRIBUTING.md#development-installation). |
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The following is the corresponding `torchvision` versions and supported Python |
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versions. |
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| `torch` | `torchvision` | Python | |
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| ------------------ | ------------------ | ------------------- | |
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| `main` / `nightly` | `main` / `nightly` | `>=3.9`, `<=3.12` | |
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| `2.5` | `0.20` | `>=3.9`, `<=3.12` | |
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| `2.4` | `0.19` | `>=3.8`, `<=3.12` | |
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| `2.3` | `0.18` | `>=3.8`, `<=3.12` | |
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| `2.2` | `0.17` | `>=3.8`, `<=3.11` | |
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| `2.1` | `0.16` | `>=3.8`, `<=3.11` | |
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| `2.0` | `0.15` | `>=3.8`, `<=3.11` | |
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<details> |
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<summary>older versions</summary> |
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| `torch` | `torchvision` | Python | |
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|---------|-------------------|---------------------------| |
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| `1.13` | `0.14` | `>=3.7.2`, `<=3.10` | |
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| `1.12` | `0.13` | `>=3.7`, `<=3.10` | |
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| `1.11` | `0.12` | `>=3.7`, `<=3.10` | |
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| `1.10` | `0.11` | `>=3.6`, `<=3.9` | |
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| `1.9` | `0.10` | `>=3.6`, `<=3.9` | |
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| `1.8` | `0.9` | `>=3.6`, `<=3.9` | |
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| `1.7` | `0.8` | `>=3.6`, `<=3.9` | |
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| `1.6` | `0.7` | `>=3.6`, `<=3.8` | |
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| `1.5` | `0.6` | `>=3.5`, `<=3.8` | |
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| `1.4` | `0.5` | `==2.7`, `>=3.5`, `<=3.8` | |
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| `1.3` | `0.4.2` / `0.4.3` | `==2.7`, `>=3.5`, `<=3.7` | |
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| `1.2` | `0.4.1` | `==2.7`, `>=3.5`, `<=3.7` | |
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| `1.1` | `0.3` | `==2.7`, `>=3.5`, `<=3.7` | |
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| `<=1.0` | `0.2` | `==2.7`, `>=3.5`, `<=3.7` | |
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</details> |
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## Image Backends |
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Torchvision currently supports the following image backends: |
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- torch tensors |
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- PIL images: |
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- [Pillow](https://python-pillow.org/) |
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- [Pillow-SIMD](https://github.com/uploadcare/pillow-simd) - a **much faster** drop-in replacement for Pillow with SIMD. |
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Read more in in our [docs](https://pytorch.org/vision/stable/transforms.html). |
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## [UNSTABLE] Video Backend |
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Torchvision currently supports the following video backends: |
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- [pyav](https://github.com/PyAV-Org/PyAV) (default) - Pythonic binding for ffmpeg libraries. |
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- video_reader - This needs ffmpeg to be installed and torchvision to be built from source. There shouldn't be any |
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conflicting version of ffmpeg installed. Currently, this is only supported on Linux. |
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``` |
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conda install -c conda-forge 'ffmpeg<4.3' |
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python setup.py install |
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``` |
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# Using the models on C++ |
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Refer to [example/cpp](https://github.com/pytorch/vision/tree/main/examples/cpp). |
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**DISCLAIMER**: the `libtorchvision` library includes the torchvision |
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custom ops as well as most of the C++ torchvision APIs. Those APIs do not come |
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with any backward-compatibility guarantees and may change from one version to |
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the next. Only the Python APIs are stable and with backward-compatibility |
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guarantees. So, if you need stability within a C++ environment, your best bet is |
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to export the Python APIs via torchscript. |
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## Documentation |
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You can find the API documentation on the pytorch website: <https://pytorch.org/vision/stable/index.html> |
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## Contributing |
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See the [CONTRIBUTING](CONTRIBUTING.md) file for how to help out. |
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## Disclaimer on Datasets |
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This is a utility library that downloads and prepares public datasets. We do not host or distribute these datasets, |
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vouch for their quality or fairness, or claim that you have license to use the dataset. It is your responsibility to |
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determine whether you have permission to use the dataset under the dataset's license. |
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If you're a dataset owner and wish to update any part of it (description, citation, etc.), or do not want your dataset |
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to be included in this library, please get in touch through a GitHub issue. Thanks for your contribution to the ML |
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community! |
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## Pre-trained Model License |
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The pre-trained models provided in this library may have their own licenses or terms and conditions derived from the |
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dataset used for training. It is your responsibility to determine whether you have permission to use the models for your |
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use case. |
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More specifically, SWAG models are released under the CC-BY-NC 4.0 license. See |
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[SWAG LICENSE](https://github.com/facebookresearch/SWAG/blob/main/LICENSE) for additional details. |
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## Citing TorchVision |
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If you find TorchVision useful in your work, please consider citing the following BibTeX entry: |
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```bibtex |
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@software{torchvision2016, |
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title = {TorchVision: PyTorch's Computer Vision library}, |
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author = {TorchVision maintainers and contributors}, |
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year = 2016, |
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journal = {GitHub repository}, |
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publisher = {GitHub}, |
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howpublished = {\url{https://github.com/pytorch/vision}} |
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} |
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``` |
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