jspenmar/slowtv_monodepth

Simple evaluation on monodepth2's code

Opened this issue · 1 comments

xapaxca commented

Hi Jaime,

Again, thank you for the work!

I am trying to evaluate your KBR weights on Monodepth2's evaluation code with Eigen split and median scaling.

See the code: evaluate_depth_kbr

However, the results I'm obtaining are worse than anticipated. Please see the details below:

Loading weights with prefix 'nets.depth.encoder.':
        Total number of keys: 340
        Number of missing keys: 0
        Number of unexpected keys: 0
Loading weights with prefix 'nets.depth.decoders.disp.':
        Total number of keys: 28
        Number of missing keys: 0
        Number of unexpected keys: 0
-> Computing predictions with size 640x192
-> Evaluating
   Mono evaluation - using median scaling
 Scaling ratios | med: 1.755 | std: 0.170

   abs_rel |   sq_rel |     rmse | rmse_log |       a1 |       a2 |       a3 |
&   0.137  &   1.731  &   5.461  &   0.215  &   0.851  &   0.944  &   0.974  \\

-> Done!

Scaling disparities does not significantly influence the outcomes:
pred_disp, _ = disp_to_depth(pred_disp, opt.min_depth, opt.max_depth)

Could I be overlooking something?

Thank you for your assistance!

jspenmar commented

Hi xapaxca,

At the moment I don't have time to look in too much detail at the code you sent. For now, some "off the top of my head" recommendations:

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