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#! /bin/bash
GPU_ID=0
DATA_ROOT_DIR="results"
DATASETS=(
davis_rearranged
)
SCENES=(
blackswan
camel
car-shadow
dog
horsejump-high
motocross-jump
parkour
soapbox
)
N_VIEWS=(
50
50
40
50
50
40
50
50
)
# increase iteration to get better metrics (e.g. gs_train_iter=5000)
gs_train_iter=4000
tag="testing_pnsr"
for i in "${!SCENES[@]}"; do
for DATASET in "${DATASETS[@]}"; do
SCENE=${SCENES[$i]}
N_VIEW=${N_VIEWS[$i]}
# SOURCE_PATH must be Absolute path
SOURCE_PATH=${DATA_ROOT_DIR}/${DATASET}/${SCENE}/
MODEL_PATH=${DATA_ROOT_DIR}/${DATASET}/${SCENE}/${tag}_${gs_train_iter}/
CMD_T="CUDA_VISIBLE_DEVICES=${GPU_ID} python -W ignore ./train_test_psnr.py \
-s ${SOURCE_PATH} \
-m ${MODEL_PATH} \
--n_views ${N_VIEW} \
--scene ${SCENE} \
--iter ${gs_train_iter} \
--optim_pose \
--dataset davis \
--gt_dynamic_mask data/davis/DAVIS/Annotations/480p \
"
echo "========= ${DATASET}/${SCENE}: Train: jointly optimize pose with dynamic masking ========="
echo $CMD_T
eval $CMD_T
done
done
python scripts/get_testing_psnr_davis.py |