A PyTorch-based library for working with 3D and 2D convolutional neural networks, with focus on semantic segmentation of volumetric biomedical image data
Currently, only training scenarios are handled by elektronn3. Tools for large-scale model deployment on big data volumes will be needed eventually. This needs some discussion and careful planning first, because there are many open questions in this regard, e.g. w.r.t. if we should start working on multi-node distributed prediction in PyTorch or instead use another framework such as Caffe2 for this via ONNX export.
Currently, only training scenarios are handled by elektronn3. Tools for large-scale model deployment on big data volumes will be needed eventually. This needs some discussion and careful planning first, because there are many open questions in this regard, e.g. w.r.t. if we should start working on multi-node distributed prediction in PyTorch or instead use another framework such as Caffe2 for this via ONNX export.