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train_fcot_2stages.sh
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#! /bin/bash
cd ../ltr
#WORKSPACE_STAGE1="/home/cyt/data/experiments/FCOT-jointly"
#WORKSPACE_STAGE2="/home/cyt/data/experiments/FCOT-jointly-online-reg"
WORKSPACE_STAGE1="/your/workspace/for/trianing/stage1"
WORKSPACE_STAGE2="/your/workspace/for/trianing/stage2"
LOAD_MODEL_EPOCH=70
# stage1: train backbone, classifier-72, classifier-18 and regression branch (except for optimizer)
python run_training.py fcot fcot \
--samples_per_epoch 40000 \
--use_pretrained_dimp 'True' \
--pretrained_dimp50 "../models/dimp50.pth" \
--train_cls_72_and_reg_init 'True' \
--train_cls_18 'True' \
--workspace_dir $WORKSPACE_STAGE1 \
--lasot_rate 1 \
--total_epochs 70 \
--batch_size 40 \
--devices_id 0 1 2 3 4 5 6 7 # used gpus
# stage2: train regression optimizer
python run_training.py fcot fcot \
--samples_per_epoch 26000 \
--load_model 'True' \
--fcot_model "${WORKSPACE_STAGE1}/checkpoints/ltr/fcot/fcot/FCOTNet_ep00${LOAD_MODEL_EPOCH}.pth.tar"\
--train_reg_optimizer 'True' \
--workspace_dir $WORKSPACE_STAGE2 \
--total_epochs 5 \
--batch_size 40 \
--devices_id 0 1 2 3 4 5 6 7 # used gpus