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#!/bin/bash -l
SCRIPTPATH=$(dirname $(readlink -f "$0"))
PROJECT_DIR="${SCRIPTPATH}/../../"
# conda activate loftr
export PYTHONPATH=$PROJECT_DIR:$PYTHONPATH
cd $PROJECT_DIR
data_cfg_path="configs/data/scannet_test_1500.py"
main_cfg_path="configs/model/indoor/model_cfg_test.py"
ckpt_path="pretrained/model_best.ckpt"
dump_dir="dump/loftr_ds_indoor"
profiler_name="inference"
n_nodes=1 # mannually keep this the same with --nodes
n_gpus_per_node=-1
torch_num_workers=4
batch_size=1 # per gpu
python -u ./test.py \
${data_cfg_path} \
${main_cfg_path} \
--ckpt_path=${ckpt_path} \
--dump_dir=${dump_dir} \
--gpus=${n_gpus_per_node} --num_nodes=${n_nodes} --accelerator="ddp" \
--batch_size=${batch_size} --num_workers=${torch_num_workers}\
--profiler_name=${profiler_name} \
--benchmark
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