Why should we build a new framework every time starting a new research?
Welcome to VRT by PyTorch!
- VRT is a high robust PyTorch-based framework for deep learning in computer vision, which aimed at easy-to-use, high efficiency, clean code and research.
- The dataset in VRT is efficient enough to support all kind of task (seg, det, class, etc..)
- All the parameters in VRT can be controlled in one config file.
- VRT support single GPU and multi GPU, but do not support CPU.
- The idea was inspired by the project torchcv.
- The base framework is heavily influenced by maskrcnn-benchmark, which is a really cool implementation of PyTorch.