Here, we provide pre-trained weight files for various U-Nets. These were trained to recognize, segment or classify various structures in 2D or 3D volume stacks.
Most networks were trained with the U-Net Fiji plugin as described in Falk et al., Nature Methods, 2019. Please find detailed installation instructions on the website of the Computer Vision Group, Faculty of Computer Sciences, University of Freiburg or the corresponding github project page.
To run each network, please download the zip archive, which contains:
- a model file (modeldef.h5)
- the weights file of the trained model (caffemodel.h5)
- a sample input file
- the corresponding output file
- a short description of the network (readme file)