The parameters for test_KVNet.py
:
exp_name
: The name for the experiment. The results will be saved in ../results/${exp_name}
sigma_soft_max
: the sigma value used for getting the DPV. Should be the same as during training.
t_win
: the time window radius. The time window will be centered around the current frame
d_min, d_max
: the minimal and maximal depth values
feature_dim
: PSM feature dimension in DNet, should be the same as in the training session
dataset
: the dataset name. Should one of scanNet, 7scenes, kitti
dataset_path
: the path to the specified dataset
split_file
: the spilt txt file, specifying which scenes/videos to use.
model_path
: the path to the trained model
Suppose the decoded ScanNet dataset, with 5-frame interval, is at /datasets/scan-net-5-frame
, to test on ScanNet dataset:
CUDA_VISIBLE_DEVICES=0 python3 test_KVNet.py \
--exp_name te_scannet/ \
--sigma_soft_max 10\
--t_win 2 \
--d_min .1 \
--d_max 5 \
--feature_dim 64 \
--ndepth 64 \
--dataset scanNet \
--dataset_path /datasets/scan-net-5-frame \
--split_file ./mdataloader/scanNet_split/scannet_val.txt \
--model_path ./saved_models/kvnet_scannet.tar
The results will be saved at ../results/te_scannet
.
Suppose the KITTI dataset is at /datasets/kitti
, and the folders are organized as
/datasets/kitti/rawdata
/datasets/kitti/train
/datasets/kitti/val
to test on KITTI dataset:
CUDA_VISIBLE_DEVICES=0 python3 test_KVNet.py \
--exp_name te_kitti/ \
--sigma_soft_max 10\
--t_win 2 \
--d_min 1 \
--d_max 60 \
--feature_dim 64 \
--ndepth 64 \
--dataset kitti \
--dataset_path /datasets/kitti \
--split_file ./mdataloader/kitti_split/test_eigen.txt \
--model_path ./saved_models/kvnet_kitti.tar
The results will be saved at ../results/te_kitti
.
Suppose the 7Scenes dataset is at /datasets/7scenes
,
CUDA_VISIBLE_DEVICES=0 python3 test_KVNet.py \
--exp_name te_7scenes/ \
--sigma_soft_max 10\
--t_win 2 \
--d_min .1 \
--d_max 5 \
--feature_dim 64 \
--ndepth 64 \
--dataset 7scenes \
--dataset_path /datasets/7scenes \
--model_path ./saved_models/kvnet_scannet.tar
The results will be saved at ../results/te_7scenes
.