Implementations of the oriented difference of gaussians model for brightness perception by Blakeslee and McCourt, and Dakin and Bex's model of brightness perception. Basic usage is
>>> import odog_model >>> om = odog_model.OdogModel() >>> result = om.evaluate(stimulus)
>>> import dakin_bex_model as dbm >>> model = dbm.DBmodel() >>> result = model.evaluate(stimulus)
where stimulus is the image you want to analyze as a 2D numpy array. An example stimulus (White's illusion) that can be used with the default parameters of the model can be loaded with
>>> import matplotlib.pyplot as plt >>> stimulus = plt.imread('example_stimulus.png')
See docstrings for further details and model parameters.
Get in touch with Torsten in case you have questions.