PaddleViT

Why we included this project

PaddleViT is a practical model collection for teams building computer vision systems on PaddlePaddle. It packages working implementations of well-known transformer and MLP architectures like ViT, DeiT, Swin, and BEiT, along with pretrained weights you can fine-tune on your own data instead of training from scratch. Each architecture is a standalone Python module, so you can pull out a single model for a quick experiment without importing the whole codebase. The same repo also covers object detection, semantic segmentation, and GANs, and bundles the training and validation scripts, mixed-precision and multi-GPU support, and export tooling that help when a model needs to move from research into a deployed service. For researchers and engineers who build on PaddlePaddle, it saves the trouble of reimplementing current vision models by hand.