We currently support four SOT methods for inference: DiMP, SiamRPN++, Stark, and our UTT. More methods could be easily reproduced with our codebase.
Data and Checkpoint structures
data
|——————coco
| └——————train2017
| └——————annotations
└——————GOT10k
| └——————train
| └——————val
| └——————test
└——————LaSOTBenchmark
| └——————airplane
| | ...
| └——————volleyball
└——————OTB
| └——————Basketball
| | ...
| └——————Woman
└——————TrackingNet
| └——————TRAIN_0
| | ...
| └——————TRAIN_11
| └——————TEST
checkpoints
|——————dimp
| └——————dimp50.pth
| └——————super_dimp50.pth
|——————siamrpn
| └—————siamrpn50.pth
|——————stark
| └——————stark50.pth
|——————utt
| └——————utt_sot50.pth
Test SiamRPN
torchrun --nproc_per_node 8 --master_port 9999 tools/train_dist.py --config-file configs/siamrpn/siamrpn++.yaml --config-func siamrpn --eval-only
Test DiMP
torchrun --nproc_per_node 8 --master_port 9999 tools/train_dist.py --config-file configs/dimp/dimp50.yaml --config-func dimp --eval-only
Test Stark
torchrun --nproc_per_node 8 --master_port 9999 tools/train_dist.py --config-file configs/stark/stark50.yaml --config-func stark --eval-only
Test UTT
torchrun --nproc_per_node 8 --master_port 9999 tools/train_dist.py --config-file configs/utt/utt.yaml --config-func utt --eval-only