Recognite is a library to kickstart your next PyTorch-based recognition project.
Some interesting features include:
- You can choose from nearly 80 different base models for your recognition model: classics like AlexNet, GoogLeNet, VGG, Inception, ResNet, but also more recent models like ResNeXt, EfficientNet, and transformer-based models like ViT and SwinTransformer.
- You can easily evaluate your model model directly for a recognition task, where query samples are compared with a gallery, and none of the samples have a class that was used during training.
- By changing only a single argument, you can cross-validate sets of hyperparameters without much effort.
:caption: User guide
:maxdepth: 2
guide/01-getting_started
guide/02-data
guide/03-model
guide/04-evaluation
guide/05-utils
:caption: API
:maxdepth: 4
recognite.data <api/data>
recognite.eval <api/eval>
recognite.model <api/model>
recognite.utils <api/utils>