Lightly

Latest version: v1.5.15

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1.5.9

- Lightly is now compatible with pydantic2
- migrated to pyproject

Models
- [AIM: Scalable Pre-training of Large Autoregressive Image Models](https://arxiv.org/pdf/2401.08541.pdf)
- [Barlow Twins: Self-Supervised Learning via Redundancy Reduction, 2021](https://arxiv.org/abs/2103.03230)
- [Bootstrap your own latent: A new approach to self-supervised Learning, 2020](https://arxiv.org/abs/2006.07733)
- [DCL: Decoupled Contrastive Learning, 2021](https://arxiv.org/abs/2110.06848)
- [DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021](https://arxiv.org/abs/2104.14294)
- [FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU, 2022](https://link.springer.com/chapter/10.1007/978-3-031-16788-1_4)
- [I-JEPA: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, 2023](https://arxiv.org/abs/2301.08243)
- [MAE: Masked Autoencoders Are Scalable Vision Learners, 2021](https://arxiv.org/abs/2111.06377)
- [MSN: Masked Siamese Networks for Label-Efficient Learning, 2022](https://arxiv.org/abs/2204.07141)
- [MoCo: Momentum Contrast for Unsupervised Visual Representation Learning, 2019](https://arxiv.org/abs/1911.05722)
- [NNCLR: Nearest-Neighbor Contrastive Learning of Visual Representations, 2021](https://arxiv.org/pdf/2104.14548.pdf)
- [PMSN: Prior Matching for Siamese Networks, 2022](https://arxiv.org/abs/2210.07277)
- [SimCLR: A Simple Framework for Contrastive Learning of Visual Representations, 2020](https://arxiv.org/abs/2002.05709)
- [SimMIM: A Simple Framework for Masked Image Modeling, 2021](https://arxiv.org/abs/2111.09886)
- [SimSiam: Exploring Simple Siamese Representation Learning, 2020](https://arxiv.org/abs/2011.10566)
- [SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022](https://arxiv.org/pdf/2207.06167.pdf)
- [SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020](https://arxiv.org/abs/2006.09882)
- [TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022](https://arxiv.org/pdf/2206.10698.pdf)
- [VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022](https://arxiv.org/abs/2105.04906)
- [VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022](https://arxiv.org/abs/2210.01571)

1.5.8

Two changes w.r.t numpy version 2:
- Make lightly itself support numpy version 2: https://github.com/lightly-ai/lightly/pull/1561
- Disallow numpy 2.0 in the requirements, as torchvision is not yet compatible with numpy 2: https://github.com/lightly-ai/lightly/pull/1562

For more context, see https://github.com/lightly-ai/lightly/issues/1558

Models
- [AIM: Scalable Pre-training of Large Autoregressive Image Models](https://arxiv.org/pdf/2401.08541.pdf)
- [Barlow Twins: Self-Supervised Learning via Redundancy Reduction, 2021](https://arxiv.org/abs/2103.03230)
- [Bootstrap your own latent: A new approach to self-supervised Learning, 2020](https://arxiv.org/abs/2006.07733)
- [DCL: Decoupled Contrastive Learning, 2021](https://arxiv.org/abs/2110.06848)
- [DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021](https://arxiv.org/abs/2104.14294)
- [FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU, 2022](https://link.springer.com/chapter/10.1007/978-3-031-16788-1_4)
- [I-JEPA: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, 2023](https://arxiv.org/abs/2301.08243)
- [MAE: Masked Autoencoders Are Scalable Vision Learners, 2021](https://arxiv.org/abs/2111.06377)
- [MSN: Masked Siamese Networks for Label-Efficient Learning, 2022](https://arxiv.org/abs/2204.07141)
- [MoCo: Momentum Contrast for Unsupervised Visual Representation Learning, 2019](https://arxiv.org/abs/1911.05722)
- [NNCLR: Nearest-Neighbor Contrastive Learning of Visual Representations, 2021](https://arxiv.org/pdf/2104.14548.pdf)
- [PMSN: Prior Matching for Siamese Networks, 2022](https://arxiv.org/abs/2210.07277)
- [SimCLR: A Simple Framework for Contrastive Learning of Visual Representations, 2020](https://arxiv.org/abs/2002.05709)
- [SimMIM: A Simple Framework for Masked Image Modeling, 2021](https://arxiv.org/abs/2111.09886)
- [SimSiam: Exploring Simple Siamese Representation Learning, 2020](https://arxiv.org/abs/2011.10566)
- [SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022](https://arxiv.org/pdf/2207.06167.pdf)
- [SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020](https://arxiv.org/abs/2006.09882)
- [TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022](https://arxiv.org/pdf/2206.10698.pdf)
- [VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022](https://arxiv.org/abs/2105.04906)
- [VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022](https://arxiv.org/abs/2210.01571)

1.5.7

Tiny improvements
* Increase download timeout for json files ([1556](https://github.com/lightly-ai/lightly/issues/1556))
* Migrate `coverage` and `mypy` configuration to `pyproject.toml` [1549](https://github.com/lightly-ai/lightly/issues/1549)). Many thanks to SauravMaheshkar for this improvement!

Models
- [AIM: Scalable Pre-training of Large Autoregressive Image Models](https://arxiv.org/pdf/2401.08541.pdf)
- [Barlow Twins: Self-Supervised Learning via Redundancy Reduction, 2021](https://arxiv.org/abs/2103.03230)
- [Bootstrap your own latent: A new approach to self-supervised Learning, 2020](https://arxiv.org/abs/2006.07733)
- [DCL: Decoupled Contrastive Learning, 2021](https://arxiv.org/abs/2110.06848)
- [DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021](https://arxiv.org/abs/2104.14294)
- [FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU, 2022](https://link.springer.com/chapter/10.1007/978-3-031-16788-1_4)
- [I-JEPA: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, 2023](https://arxiv.org/abs/2301.08243)
- [MAE: Masked Autoencoders Are Scalable Vision Learners, 2021](https://arxiv.org/abs/2111.06377)
- [MSN: Masked Siamese Networks for Label-Efficient Learning, 2022](https://arxiv.org/abs/2204.07141)
- [MoCo: Momentum Contrast for Unsupervised Visual Representation Learning, 2019](https://arxiv.org/abs/1911.05722)
- [NNCLR: Nearest-Neighbor Contrastive Learning of Visual Representations, 2021](https://arxiv.org/pdf/2104.14548.pdf)
- [PMSN: Prior Matching for Siamese Networks, 2022](https://arxiv.org/abs/2210.07277)
- [SimCLR: A Simple Framework for Contrastive Learning of Visual Representations, 2020](https://arxiv.org/abs/2002.05709)
- [SimMIM: A Simple Framework for Masked Image Modeling, 2021](https://arxiv.org/abs/2111.09886)
- [SimSiam: Exploring Simple Siamese Representation Learning, 2020](https://arxiv.org/abs/2011.10566)
- [SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022](https://arxiv.org/pdf/2207.06167.pdf)
- [SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020](https://arxiv.org/abs/2006.09882)
- [TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022](https://arxiv.org/pdf/2206.10698.pdf)
- [VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022](https://arxiv.org/abs/2105.04906)
- [VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022](https://arxiv.org/abs/2210.01571)

1.5.6

Changes
* Allow lightly-serve to run securely via https by passing ssl_cert and ssl_key

Models
- [AIM: Scalable Pre-training of Large Autoregressive Image Models](https://arxiv.org/pdf/2401.08541.pdf)
- [Barlow Twins: Self-Supervised Learning via Redundancy Reduction, 2021](https://arxiv.org/abs/2103.03230)
- [Bootstrap your own latent: A new approach to self-supervised Learning, 2020](https://arxiv.org/abs/2006.07733)
- [DCL: Decoupled Contrastive Learning, 2021](https://arxiv.org/abs/2110.06848)
- [DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021](https://arxiv.org/abs/2104.14294)
- [FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU, 2022](https://link.springer.com/chapter/10.1007/978-3-031-16788-1_4)
- [I-JEPA: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, 2023](https://arxiv.org/abs/2301.08243)
- [MAE: Masked Autoencoders Are Scalable Vision Learners, 2021](https://arxiv.org/abs/2111.06377)
- [MSN: Masked Siamese Networks for Label-Efficient Learning, 2022](https://arxiv.org/abs/2204.07141)
- [MoCo: Momentum Contrast for Unsupervised Visual Representation Learning, 2019](https://arxiv.org/abs/1911.05722)
- [NNCLR: Nearest-Neighbor Contrastive Learning of Visual Representations, 2021](https://arxiv.org/pdf/2104.14548.pdf)
- [PMSN: Prior Matching for Siamese Networks, 2022](https://arxiv.org/abs/2210.07277)
- [SimCLR: A Simple Framework for Contrastive Learning of Visual Representations, 2020](https://arxiv.org/abs/2002.05709)
- [SimMIM: A Simple Framework for Masked Image Modeling, 2021](https://arxiv.org/abs/2111.09886)
- [SimSiam: Exploring Simple Siamese Representation Learning, 2020](https://arxiv.org/abs/2011.10566)
- [SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022](https://arxiv.org/pdf/2207.06167.pdf)
- [SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020](https://arxiv.org/abs/2006.09882)
- [TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022](https://arxiv.org/pdf/2206.10698.pdf)
- [VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022](https://arxiv.org/abs/2105.04906)
- [VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022](https://arxiv.org/abs/2210.01571)

1.5.5

Changes
* Add unpatchify model utils operation to reconstruct an image from its patches. See the [PR](https://github.com/lightly-ai/lightly/pull/1544) for more information. Thanks to randombenj for implementing this!
* Fixes in CI regarding coverage.
* Fixes in lightly-serve that the server was sometimes not shut down correctly.

Models
- [AIM: Scalable Pre-training of Large Autoregressive Image Models](https://arxiv.org/pdf/2401.08541.pdf)
- [Barlow Twins: Self-Supervised Learning via Redundancy Reduction, 2021](https://arxiv.org/abs/2103.03230)
- [Bootstrap your own latent: A new approach to self-supervised Learning, 2020](https://arxiv.org/abs/2006.07733)
- [DCL: Decoupled Contrastive Learning, 2021](https://arxiv.org/abs/2110.06848)
- [DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021](https://arxiv.org/abs/2104.14294)
- [FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU, 2022](https://link.springer.com/chapter/10.1007/978-3-031-16788-1_4)
- [I-JEPA: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, 2023](https://arxiv.org/abs/2301.08243)
- [MAE: Masked Autoencoders Are Scalable Vision Learners, 2021](https://arxiv.org/abs/2111.06377)
- [MSN: Masked Siamese Networks for Label-Efficient Learning, 2022](https://arxiv.org/abs/2204.07141)
- [MoCo: Momentum Contrast for Unsupervised Visual Representation Learning, 2019](https://arxiv.org/abs/1911.05722)
- [NNCLR: Nearest-Neighbor Contrastive Learning of Visual Representations, 2021](https://arxiv.org/pdf/2104.14548.pdf)
- [PMSN: Prior Matching for Siamese Networks, 2022](https://arxiv.org/abs/2210.07277)
- [SimCLR: A Simple Framework for Contrastive Learning of Visual Representations, 2020](https://arxiv.org/abs/2002.05709)
- [SimMIM: A Simple Framework for Masked Image Modeling, 2021](https://arxiv.org/abs/2111.09886)
- [SimSiam: Exploring Simple Siamese Representation Learning, 2020](https://arxiv.org/abs/2011.10566)
- [SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022](https://arxiv.org/pdf/2207.06167.pdf)
- [SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020](https://arxiv.org/abs/2006.09882)
- [TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022](https://arxiv.org/pdf/2206.10698.pdf)
- [VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022](https://arxiv.org/abs/2105.04906)
- [VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022](https://arxiv.org/abs/2210.01571)

1.5.4

Changes
* Fixes the GatherLayer for multiple GPUs. See [PR](https://github.com/lightly-ai/lightly/pull/1531) for more information.
* Different typos in tutorials

Models
- [AIM: Scalable Pre-training of Large Autoregressive Image Models](https://arxiv.org/pdf/2401.08541.pdf)
- [Barlow Twins: Self-Supervised Learning via Redundancy Reduction, 2021](https://arxiv.org/abs/2103.03230)
- [Bootstrap your own latent: A new approach to self-supervised Learning, 2020](https://arxiv.org/abs/2006.07733)
- [DCL: Decoupled Contrastive Learning, 2021](https://arxiv.org/abs/2110.06848)
- [DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021](https://arxiv.org/abs/2104.14294)
- [FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU, 2022](https://link.springer.com/chapter/10.1007/978-3-031-16788-1_4)
- [I-JEPA: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, 2023](https://arxiv.org/abs/2301.08243)
- [MAE: Masked Autoencoders Are Scalable Vision Learners, 2021](https://arxiv.org/abs/2111.06377)
- [MSN: Masked Siamese Networks for Label-Efficient Learning, 2022](https://arxiv.org/abs/2204.07141)
- [MoCo: Momentum Contrast for Unsupervised Visual Representation Learning, 2019](https://arxiv.org/abs/1911.05722)
- [NNCLR: Nearest-Neighbor Contrastive Learning of Visual Representations, 2021](https://arxiv.org/pdf/2104.14548.pdf)
- [PMSN: Prior Matching for Siamese Networks, 2022](https://arxiv.org/abs/2210.07277)
- [SimCLR: A Simple Framework for Contrastive Learning of Visual Representations, 2020](https://arxiv.org/abs/2002.05709)
- [SimMIM: A Simple Framework for Masked Image Modeling, 2021](https://arxiv.org/abs/2111.09886)
- [SimSiam: Exploring Simple Siamese Representation Learning, 2020](https://arxiv.org/abs/2011.10566)
- [SMoG: Unsupervised Visual Representation Learning by Synchronous Momentum Grouping, 2022](https://arxiv.org/pdf/2207.06167.pdf)
- [SwAV: Unsupervised Learning of Visual Features by Contrasting Cluster Assignments, M. Caron, 2020](https://arxiv.org/abs/2006.09882)
- [TiCo: Transformation Invariance and Covariance Contrast for Self-Supervised Visual Representation Learning, 2022](https://arxiv.org/pdf/2206.10698.pdf)
- [VICReg: Variance-Invariance-Covariance Regularization for Self-Supervised Learning, Bardes, A. et. al, 2022](https://arxiv.org/abs/2105.04906)
- [VICRegL: VICRegL: Self-Supervised Learning of Local Visual Features, 2022](https://arxiv.org/abs/2210.01571)

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