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Depth in float32 in meters units #36
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PFM files contain the results as the original, unaltered float32 values. The PNGs contain the quantized values since the format requires integer data. If you need the original data as predicted by the model, use the PFM files. You can find a reader here: https://github.com/intel-isl/MiDaS/blob/master/utils.py As for getting results in meters: The model provides results up to unknown scale and shift, i.e. only relative depth is available. You'd need additional measurements to find the scale and the shift to get absolute measurements. |
Closing due to inactivity. |
Hi, |
We align in inverse depth space; i.e. the procedure is
Section C in the supplementary provides more details on the evaluation procedure. |
@ranftlr di = np.concatenate([pred_idepth[:, None], np.ones((len(pred_idepth), 1))], 1)
di_star = gt_idepth
val1, val2 = np.zeros((1, 2)), np.zeros((1, 2))
for i in range(len(di)):
val1 = val1 + di[i]*di[i].T
val2 = val2 + di[i]*di_star[i]
st = (np.linalg.pinv(val1) * val2).reshape(-1, )
# st = (1/val1 * val2).reshape(-1, ) or this ??? st should be the estimated scale and translation (hopt in paper). |
Embarrassingly enough, I'm not able to find the supplementary material online. Does anyone have the link? |
@tarashakhurana |
Thank you! By any chance, were you able to reproduce the test set results in the paper? I'm trying to evaluate on Sintel (on its 1064 images) but I'm getting a much higher error with my evaluation code than what is reported in the paper (0.327 vs 0.605). |
Hello! Thanks for you work!
I have two questions:
.pmf
format and what is it used for?.png
depth maps how to convert them into float32 in meters units?The text was updated successfully, but these errors were encountered: