Closed wanmeihuali closed 11 months ago
Training job grad-pose-709bdb0-230704-090041-tat-truck created
Training job grad-pose-709bdb0-230704-090041-tat-truck final metrics:
train:loss | train:num_valid_points | val:ssim | val:psnr | train:ssimloss | train:iteration | train:ssim | train:psnr | val:loss | train:l1loss |
---|---|---|---|---|---|---|---|---|---|
0.06078709661960602 | 439065.0 | 0.8400789499282837 | 24.494356155395508 | 0.15725672245025635 | 30000.0 | 0.8427432775497437 | 23.737594604492188 | 0.06027264520525932 | 0.036669690161943436 |
val:7kpsnr | train:5kpsnr | val:5kssim | train:7kpsnr | val:ssim | train:5kssim | val:psnr | val:7kssim | train:ssim | train:psnr | val:5kpsnr | train:7kssim |
---|---|---|---|---|---|---|---|---|---|---|---|
23.05255699157715 | 23.579914093017578 | 0.7748168706893921 | 23.98195457458496 | 0.8400789499282837 | 0.8155559301376343 | 24.494356155395508 | 0.802121102809906 | 0.8427432775497437 | 23.737594604492188 | 22.16150665283203 | 0.8366769552230835 |
Running experiment on sagemaker with git sha 1df60520bb2861e7bcfb7fd27426b1289e586c4a
Training job grad-pose-1df6052-230705-231308-tat-truck created
Running experiment on sagemaker with git sha 0208816f5dc3ed1eb7ff78edcef288b0427a2776
Training job grad-pose-0208816-230706-002435-tat-truck created
Training job grad-pose-1df6052-230705-231308-tat-truck final metrics:
train:psnr | val:ssim | val:psnr | train:l1loss | train:ssim | train:iteration | train:loss | val:loss | train:num_valid_points | train:ssimloss |
---|---|---|---|---|---|---|---|---|---|
24.532657623291016 | 0.8387011289596558 | 24.460512161254883 | 0.0327344574034214 | 0.826497495174408 | 30000.0 | 0.06088806688785553 | 0.060897521674633026 | 432029.0 | 0.17350250482559204 |
val:7kssim | train:psnr | val:psnr | val:ssim | val:5kssim | train:ssim | train:7kssim | val:7kpsnr | train:5kpsnr | train:7kpsnr | train:5kssim | val:5kpsnr |
---|---|---|---|---|---|---|---|---|---|---|---|
0.8007435202598572 | 24.532657623291016 | 24.460512161254883 | 0.8387011289596558 | 0.7761763334274292 | 0.826497495174408 | 0.796715259552002 | 22.98880386352539 | 21.92499542236328 | 23.079547882080078 | 0.7811781764030457 | 22.268699645996094 |
Training job grad-pose-0208816-230706-002435-tat-truck final metrics:
train:num_valid_points | train:iteration | train:psnr | train:loss | val:loss | val:ssim | train:l1loss | train:ssimloss | val:psnr | train:ssim |
---|---|---|---|---|---|---|---|---|---|
441032.0 | 30000.0 | 25.386234283447266 | 0.04868044704198837 | 0.06080722063779831 | 0.8391211628913879 | 0.0295904278755188 | 0.12504053115844727 | 24.44965171813965 | 0.8749594688415527 |
val:5kssim | val:7kpsnr | train:5kssim | train:psnr | train:7kpsnr | train:7kssim | val:ssim | val:7kssim | train:5kpsnr | val:psnr | train:ssim | val:5kpsnr |
---|---|---|---|---|---|---|---|---|---|---|---|
0.7760491967201233 | 23.110506057739258 | 0.7793401479721069 | 25.386234283447266 | 22.138338088989258 | 0.7807836532592773 | 0.8391211628913879 | 0.8031792640686035 | 22.830810546875 | 24.44965171813965 | 0.8749594688415527 | 22.251619338989258 |
Running experiment on sagemaker with git sha 57791f79ce697ad9e7fb43c8ac1e6df8831749b2
Training job grad-pose-57791f7-230707-044608-tat-truck created
Training job grad-pose-57791f7-230707-044608-tat-truck final metrics:
train:iteration | train:l1loss | val:loss | train:loss | train:num_valid_points | train:ssimloss | train:psnr | train:ssim | val:ssim | val:psnr |
---|---|---|---|---|---|---|---|---|---|
30000.0 | 0.03323899954557419 | 0.06086798757314682 | 0.061937350779771805 | 432880.0 | 0.17673075199127197 | 24.97323226928711 | 0.823269248008728 | 0.839034914970398 | 24.441146850585938 |
val:7kssim | train:7kssim | val:7kpsnr | train:5kpsnr | val:5kpsnr | train:5kssim | train:7kpsnr | train:psnr | train:ssim | val:ssim | val:5kssim | val:psnr |
---|---|---|---|---|---|---|---|---|---|---|---|
0.8007597327232361 | 0.8006725311279297 | 22.96923828125 | 24.135854721069336 | 22.243276596069336 | 0.8431853652000427 | 22.518848419189453 | 24.97323226928711 | 0.823269248008728 | 0.839034914970398 | 0.7759909629821777 | 24.441146850585938 |
Although the NeRF training seems does not improve with pose optimization, the grad for camera pose shall work. The script in pose_estimation.py optimizes the camera pose for a trained scene, and it can refine the camera pose with noise. If the pose grad does not make anything worse, we can try merge it first.
Running experiment on sagemaker with git sha 0111719df8fdc48764ce44cc53f40bcd7ebd9c23
Training job grad-pose-0111719-230709-062247-tat-truck created
Running experiment on sagemaker with git sha a2309cdf47c91cc4b9b5c4f7018f76b9c292f4fe
Training job grad-pose-a2309cd-230709-063055-tat-truck created
Training job grad-pose-0111719-230709-062247-tat-truck final metrics:
val:ssim | train:l1loss | train:num_valid_points | train:iteration | val:loss | train:loss | train:ssimloss | train:ssim | val:psnr | train:psnr |
---|---|---|---|---|---|---|---|---|---|
0.4716382622718811 | 0.15424515306949615 | 166307.0 | 30000.0 | 0.23722197115421295 | 0.23633933067321777 | 0.5647160410881042 | 0.43528395891189575 | 13.317609786987305 | 13.638601303100586 |
train:7kssim | val:ssim | val:7kpsnr | val:5kssim | train:5kssim | val:5kpsnr | train:5kpsnr | val:psnr | train:7kpsnr | train:ssim | val:7kssim | train:psnr |
---|---|---|---|---|---|---|---|---|---|---|---|
0.47828158736228943 | 0.4716382622718811 | 17.74064064025879 | 0.7760130167007446 | 0.8111699819564819 | 22.261547088623047 | 23.88247299194336 | 13.317609786987305 | 17.27647590637207 | 0.43528395891189575 | 0.5434229969978333 | 13.638601303100586 |
Training job grad-pose-a2309cd-230709-063055-tat-truck final metrics:
train:psnr | train:ssim | val:psnr | val:loss | train:loss | train:iteration | val:ssim | train:l1loss | train:num_valid_points | train:ssimloss |
---|---|---|---|---|---|---|---|---|---|
15.990808486938477 | 0.4629014730453491 | 12.337618827819824 | 0.2595042884349823 | 0.19545842707157135 | 30000.0 | 0.45191073417663574 | 0.11004839837551117 | 323516.0 | 0.5370985269546509 |
train:psnr | train:ssim | val:psnr | train:7kssim | val:7kpsnr | train:7kpsnr | val:ssim | val:5kpsnr | train:5kpsnr | val:5kssim | val:7kssim | train:5kssim |
---|---|---|---|---|---|---|---|---|---|---|---|
15.990808486938477 | 0.4629014730453491 | 12.337618827819824 | 0.4875752925872803 | 14.27987289428711 | 15.284371376037598 | 0.45191073417663574 | 22.11170768737793 | 22.80233383178711 | 0.772071361541748 | 0.47993865609169006 | 0.7824743986129761 |
Running experiment on sagemaker with git sha 81541884575489e397885796a274e78c891e6023
Training job grad-pose-8154188-230709-175345-tat-truck created
Training job grad-pose-8154188-230709-175345-tat-truck final metrics:
train:psnr | train:ssim | train:loss | train:l1loss | val:loss | val:ssim | train:ssimloss | train:iteration | val:psnr | train:num_valid_points |
---|---|---|---|---|---|---|---|---|---|
24.723766326904297 | 0.8404524326324463 | 0.056935884058475494 | 0.03128296136856079 | 0.060437630861997604 | 0.8397347331047058 | 0.1595475673675537 | 30000.0 | 24.469940185546875 | 432427.0 |
train:psnr | train:ssim | train:5kssim | val:5kpsnr | train:5kpsnr | train:7kpsnr | val:ssim | train:7kssim | val:7kssim | val:5kssim | val:7kpsnr | val:psnr |
---|---|---|---|---|---|---|---|---|---|---|---|
24.723766326904297 | 0.8404524326324463 | 0.7363717555999756 | 22.2385311126709 | 21.535194396972656 | 23.574939727783203 | 0.8397347331047058 | 0.8256381750106812 | 0.8007689714431763 | 0.7736835479736328 | 23.058002471923828 | 24.469940185546875 |
Running experiment on sagemaker with git sha 709bdb05d4f2500180302416e1e70bdff96cebbe