VICReg benchmarks on Imagenet

Changes

• We have evaluated our VICReg implementation on Imagenet (check it out).
• Docs update to emphasize difference between Lightly SSL and the company.
• Allow filenames with commas in embedding files and datasets.
• Fix: Imagenet benchmarks memory problems.

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
• 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

Types!

Changes

• Add mypy and type the package partially (#1382). lightly.transforms is fully typed. We'll gradually add types for the other modules.
• Add py.typed files for typed parts of the package (#1382). This makes types available when working with lightly from other codebases.
• Add support to resume benchmark training (#1347). Thanks a lot to @sadimanna!
• Remove docs for outdated/internal API methods (#1385).
• Make the relative_path argument optional when scheduling a Lightly Worker run with local storage (#1384).

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
• 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

BarlowTwins Benchmark on ImageNet

Changes

• Added a new benchmark of BarlowTwins on ImageNet.
• Optimized performance of the BarlowTwinsLoss computation, making it much faster
• Fixed a bug in the CosineWarmupScheduler. Thanks to @anishacharya for pointing out the problem.
• Cleaned the setup.py

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
• 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

Lightly Local Workflow

Changes

• Prepare for local workflow support:
  • add lightly-serve command
  • regenerate specs
• Fix docstrings

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
• 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

Patch generated API client

Changes

• Patch generated API client.

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
• 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

BYOLTransform

Changes

• Add BYOLTransform which replaces SimCLRTransform in BYOL benchmarks.
• Log benchmark results only on rank0.
• Fix bug in PMSNLoss where probabilities were not converted to log-space before the loss calculation. Thanks to @Cloudy1225 for reporting this!
• Version check now runs in background and no longer requires SIGALRM.
• Add support for scheduling Lightly Worker runs with the new selection strategy strength option.

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
• 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

I-JEPA

Changes

• Basic support for I-JEPA (thanks to @Natyren!)
• add BYOL imagenet resnet50 benchmark

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
• DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021
• FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU, 2022
• 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
• I-JEPA: Self-Supervised Learning from Images with a Joint-Embedding Predictive Architecture, 2023

Paginate API client endpoints

Changes

• Paginate API client endpoints
• Cleaned up API client codebase

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
• DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021
• FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU, 2022
• 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

Remove prefetch-generator

Changes

• Remove prefetch_generator as this is supported natively by PyTorch 1.7 and higher.
• Improve error messages for scheduled jobs with invalid configurations.
• Correctly create SelectionConfig with repeated object references.

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
• DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021
• FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU, 2022
• 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

SimCLR with finetuning benchmark

Changes

• updates SimCLR benchmark results with finetuning added
• fixes swav imagenet benchmark
• it is now possible to fetch team datasets

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
• DINO: Emerging Properties in Self-Supervised Vision Transformers, 2021
• FastSiam: Resource-Efficient Self-supervised Learning on a Single GPU, 2022
• 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