This is the Linux app named Pytorch-toolbelt whose latest release can be downloaded as PytorchToolbelt0.6.2.zip. It can be run online in the free hosting provider OnWorks for workstations.
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Pytorch-toolbelt
DESCRIPTION
A pytorch-toolbelt is a Python library with a set of bells and whistles for PyTorch for fast R&D prototyping and Kaggle farming. Easy model building using flexible encoder-decoder architecture. Modules: CoordConv, SCSE, Hypercolumn, Depthwise separable convolution and more. GPU-friendly test-time augmentation TTA for segmentation and classification. GPU-friendly inference on huge (5000x5000) images. Every-day common routines (fix/restore random seed, filesystem utils, metrics). Losses: BinaryFocalLoss, Focal, ReducedFocal, Lovasz, Jaccard and Dice losses, Wing Loss and more. Extras for Catalyst library (Visualization of batch predictions, additional metrics). By design, both encoder and decoder produces a list of tensors, from fine (high-resolution, indexed 0) to coarse (low-resolution) feature maps. Access to all intermediate feature maps is beneficial if you want to apply deep supervision losses on them or encoder-decoder of object detection task.
Features
- Create Encoder-Decoder FPN model with pretrained encoder
- Create Encoder-Decoder U-Net model
- Create Encoder-Decoder FPN model with pretrained encoder
- Change number of input channels for the Encoder
- Count number of parameters in encoder/decoder and other modules
- Compose multiple losses
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/pytorch-toolbelt.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
