For a trained model, use relpose/eval/eval_joint.py
for evaluation. For example,
to evaluate using a maximum spanning tree over 5 frames from seen object categories,
use:
python -m relpose.eval.eval_joint \
--checkpoint data/pretrained_co3dv1/checkpoints/ckpt_000400000.pth \
--num_frames 5 \
--use_pbar \
--dataset co3dv1 \
--categories_type seen \
--mode mst
To simplify evaluation, we provide a script to generate a shell file with the commands
for different numbers of frames, evaluation modes, etc. Please see
relpose/eval/eval_driver.py
which generate a script eval_jobs.sh
. You can then run
this script with sh eval_jobs.sh
.
Note: coordinate ascent must be run after the MST evaluation because it is initialized from the MST solution.
These models were retrained and may not match the numbers in the paper. There may also be some stochasticiy in the runs.
Expected evaluation results (Uniform, seen categories):
Sequential N=3 N=5 N=10 N=20
Acc <15° 0.38 0.36 0.33 0.29
Acc <30° 0.61 0.59 0.57 0.54
MST N=3 N=5 N=10 N=20
Acc <15° 0.38 0.44 0.46 0.43
Acc <30° 0.61 0.63 0.64 0.61
Coord Asc N=3 N=5 N=10 N=20
Acc <15° 0.44 0.51 0.54 0.56
Acc <30° 0.63 0.69 0.71 0.72
Expected evaluation results (Uniform, unseen categories):
Sequential N=3 N=5 N=10 N=20
Acc <15° 0.28 0.27 0.27 0.24
Acc <30° 0.48 0.46 0.47 0.47
MST N=3 N=5 N=10 N=20
Acc <15° 0.29 0.32 0.37 0.37
Acc <30° 0.48 0.50 0.52 0.53
Coord Asc N=3 N=5 N=10 N=20
Acc <15° 0.33 0.37 0.43 0.46
Acc <30° 0.51 0.55 0.58 0.61
Expected evaluation results (Uniform, seen categories):
Sequential N=3 N=5 N=10 N=20
Acc <15° 0.31 0.30 0.30 0.28
Acc <30° 0.54 0.51 0.51 0.51
MST N=3 N=5 N=10 N=20
Acc <15° 0.30 0.33 0.35 0.34
Acc <30° 0.53 0.54 0.55 0.53
Coord Asc N=3 N=5 N=10 N=20
Acc <15° 0.35 0.38 0.43 0.45
Acc <30° 0.56 0.58 0.62 0.64
Expected evaluation results (Uniform, unseen categories):
Sequential N=3 N=5 N=10 N=20
Acc <15° 0.18 0.21 0.23 0.25
Acc <30° 0.39 0.38 0.43 0.46
MST N=3 N=5 N=10 N=20
Acc <15° 0.19 0.22 0.25 0.27
Acc <30° 0.41 0.42 0.42 0.43
Coord Asc N=3 N=5 N=10 N=20
Acc <15° 0.20 0.25 0.31 0.34
Acc <30° 0.42 0.45 0.51 0.52