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View Code? Open in Web Editor NEWA python library for contrast maximization and voxel creation using events
A python library for contrast maximization and voxel creation using events
Hello, I didn't understand the code line from 362 to 365 in the utils/event_utils.py
pxs = (xs.floor()).float()
pys = (ys.floor()).float()
dxs = (xs-pxs).float()
dys = (ys-pys).float()
Since x
and y
are pixel coordinates, they are all integers. So, the .floor()
function will not be different from original values. And dxs
and dys
will be 0
then. Is it right?
In the function get_iwe:
events_contrast_maximization/utils/objectives.py
Lines 68 to 69 in ab74aba
The parameter img_size isn't passed into events_to_image_drv as sensor_size. As a result, the code fails to deal with sensors with size other than (180, 240).
Hi Timo Stoffregen. Thanks for your work.
I am confused about the objective functions in your code. For example , the sosa_objective in objectives.py, it is written as:
exp = np.exp(-self.p*iwe.astype(np.double))
sosa = np.sum(exp)
return -sosa
In your paper Event Cameras, Contrast Maximization and Reward Functions: an Analysis , it is said that 'This
reward is maximized at the optimal trajectory '. But here you used the negative
So I want to know that in your code, will the optimizer maximize or minimize the objective functions? Or dose it just assume that the objective functions are used as loss functions in the deep learning networks?
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