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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/loftr/indoor/buggy_pos_enc/loftr_ot.py"
- ckpt_path="weights/indoor_ot.ckpt"
- dump_dir="dump/loftr_ot_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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