jzbontar / mc-cnn

Stereo Matching by Training a Convolutional Neural Network to Compare Image Patches

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What are the correct dimension and ndisp values for Middlebury datasets?

tltsilveira opened this issue · comments

Hey everybody. I am trying to predict depth from the test images of Middlebury 2006. However the obtained results are very poor and they have a large portion of estimated map the with no disparity (like the maximum value).

In particular I am using the mb slow model on full size images.

ndisp is set as
ndisp = max(gtDisp) * 1.1
where gtDisp is the ground-truth disparity map for of a given stereo pair of interest.

Do you know this issue?

Thank you in advance.

commented

if you open the calib.txt file for each image, you will find it. Files contain information like this:
cam0=[1038.018 0 322.037; 0 1038.018 243.393; 0 0 1]
cam1=[1038.018 0 375.308; 0 1038.018 243.393; 0 0 1]
doffs=53.271
baseline=176.252
width=718
height=496
ndisp=73
isint=0
vmin=8
vmax=65
dyavg=0.184
dymax=0.423