More Transforms, Typing and Docs Improvements

Changes

New transforms

• Added RFFT2D and IRFFT2D transforms @snehilchatterjee
• Add RandomFrequencyMaskTransform @payo101
• Add GaussianMixtureMaskTransform @snehilchatterjee
• Add AmplitudeRescaleTransform @payo101
• Better support for both torchvision.transforms v1 and v2 without warnings/errors.

Added and updated docstrings

• Many improvements by @Prathamesh010, @ayush22iitbhu, @ChiragAgg5k @HarshitVashisht11

Docs improvements

• Improvements of the README.md @bhargavshirin and @kushal34712 @eltociear @Mefisto04 @ayush22iitbhu
• Improvements of other parts of the the docs and tutorials @jizhang02
• Fix examples on Windows @snehilchatterjee
• Improve CONTRIBUTING.md @Prathamesh010
• Added a back to top button for easier navigation @hackit-coder

More and better typing

• Testing typing for all python versions
• Typing of serve.py @ishaanagw
• Cleanup: _image.py and _utils.py file in data subpackage @ChiragAgg5k

Better formatting

• Move classes and public functions to top of file @fadkeabhi and @SauravMaheshkar

Other

• Print Aggregate Metrics at End of Benchmarks as Markdown Table @EricLiclair

Many thanks to all of our contributors!

Models

• AIM: Scalable Pre-training of Large Autoregressive Image Models
• Barlow Twins: Self-Supervised Learning via Redundancy Reduction, 2021
• Bootstrap your own latent: A new approach to self-supervised Learning, 2020
• DCL: Decoupled Contrastive Learning, 2021
• DenseCL: Dense Contrastive Learning for Self-Supervised Visual Pre-Training, 2021
• DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021
• FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU, 2022
• I-JEPA: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, 2023
• MAE: Masked Autoencoders Are Scalable Vision Learners, 2021
• MSN: Masked Siamese Networks for Label-Efficient Learning, 2022
• MoCo: Momentum Contrast for Unsupervised Visual Representation Learning, 2019
• NNCLR: Nearest-Neighbor Contrastive Learning of Visual Representations, 2021
• PMSN: Prior Matching for Siamese Networks, 2022
• SimCLR: A Simple Framework for Contrastive Learning of Visual Representations, 2020
• SimMIM: A Simple Framework for Masked Image Modeling, 2021
• SimSiam: Exploring Simple Siamese Representation Learning, 2020
• SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022
• SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020
• TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022
• VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022
• VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022