.. -*- coding: utf-8 -*- .. _bob.ip.binseg.results.xtest: ========================== Cross-Database (X-)Tests ========================== * Models are trained and tested on the same dataset (numbers in parenthesis indicate number of parameters per model), and then evaluated across the test sets of other databases. X-tested datasets therefore represent *unseen* data and can be a good proxy for generalisation analysis. * Each table row indicates a base trained model and each column the databases the model was tested against. The native performance (intra-database) is marked **in bold**. Thresholds are chosen *a priori* on the training set of the database used to generate the model being cross-tested. Hence, the threshold used for all experiments in a same row is always the same. * You can cross check the analysis numbers provided in this table by downloading this software package, the raw data, and running ``bob binseg analyze`` providing the model URL as ``--weight`` parameter, and then the ``-xtest`` resource variant of the dataset the model was trained on. For example, to run cross-evaluation tests for the DRIVE dataset, use the configuration resource :py:mod:`drive-xtest `. * For each row, the peak performance is always obtained in an intra-database test (training and testing on the same database). Conversely, we observe a performance degradation (albeit not catastrophic in most cases) for all other datasets in the cross test. * We only show results for select systems in :ref:`baseline analysis `. You may run analysis on the other models by downloading them from our website (via the ``--weight`` parameter on the :ref:`analyze script `). Models on Specific Tasks ------------------------ .. toctree:: :maxdepth: 2 vessel/driu vessel/m2unet vessel/unet disc/hed disc/m2unet disc/unet cup/hed cup/m2unet cup/unet lung/lwnet lung/m2unet lung/unet .. include:: ../../links.rst