I've streamlined the DinoV2 code repository and integrated a wrapper for clarity. This allows you to easily understand the core mechanics of how the model functions, without being sidetracked by the complexities of distributed computing and other extraneous add-ons that obscure the model's primary operations.
1. Dataloading an Augmentation
2. Dino Model
3. Training Methods
4. Model Demo
5. Pretrained Model
‣ 2021 Emerging Properties in Self-Supervised Vision Transformers
‣ 2023 DINOv2: Learning Robust Visual Features without Supervision