It failed to evaluate annotation type *bbox* for training fgfa_faste_rcnn_r101_dc5_1x_imagenetvid.

[lively2018]

My environment is the following:
$ python mmtrack/utils/collect_env.py
sys.platform: linux
Python: 3.7.5 (default, Dec 9 2021, 17:04:37) [GCC 8.4.0]
CUDA available: True
GPU 0: NVIDIA RTX A6000
CUDA_HOME: /usr/local/cuda-11.1
NVCC: Build cuda_11.1.TC455_06.29069683_0
GCC: gcc (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0
PyTorch: 1.10.0+cu111
PyTorch compiling details: PyTorch built with:

• GCC 7.3
• C++ Version: 201402
• Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications
• Intel(R) MKL-DNN v2.2.3 (Git Hash 7336ca9f055cf1bfa13efb658fe15dc9b41f0740)
• OpenMP 201511 (a.k.a. OpenMP 4.5)
• LAPACK is enabled (usually provided by MKL)
• NNPACK is enabled
• CPU capability usage: AVX2
• CUDA Runtime 11.1
• NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80;-gencode;arch=compute_86,code=sm_86
• CuDNN 8.0.5
• Magma 2.5.2
• Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.1, CUDNN_VERSION=8.0.5, CXX_COMPILER=/opt/rh/devtoolset-7/root/usr/bin/c++, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_KINETO -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DSYMBOLICATE_MOBILE_DEBUG_HANDLE -DEDGE_PROFILER_USE_KINETO -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, LAPACK_INFO=mkl, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, TORCH_VERSION=1.10.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON,

TorchVision: 0.11.1+cu111
OpenCV: 4.10.0
MMCV: 1.4.2
MMCV Compiler: GCC 7.5
MMCV CUDA Compiler: 11.1
MMTracking: 0.14.0+e79491e

2. Error Message
   $ python tools/train.py ./configs/vid/fgfa/fgfa_faster_rcnn_r101_dc5_1x_imagenetvid.py --work-dir ./work_dirs/
   ...skip
   2024-08-09 10:42:17,152 - mmtrack - INFO - workflow: [('train', 1)], max: 7 epochs
   2024-08-09 10:42:17,152 - mmtrack - INFO - Checkpoints will be saved to /home/kssong/mmtracking-0.14.0/work_dirs by HardDiskBackend.
   /home/kssong/mmtracking-0.14.0/.venv/lib/python3.7/site-packages/torch/nn/functional.py:3680: UserWarning: The default behavior for interpolate/upsample with float scale_factor changed in 1.6.0 to align with other frameworks/libraries, and now uses scale_factor directly, instead of relying on the computed output size. If you wish to restore the old behavior, please set recompute_scale_factor=True. See the documentation of nn.Upsample for details.
   "The default behavior for interpolate/upsample with float scale_factor changed "

.....skip.....

2024-08-11 02:25:50,004 - mmtrack - INFO - Saving checkpoint at 7 epochs
[>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>] 176126/176126, 10.2 task/s, elapsed: 17310s, ETA: 0s2024-08-11 07:17:35,811 - mmtrack - INFO - Evaluating bbox...
Loading and preparing results...
DONE (t=43.05s)
creating index...
index created!
Running per image evaluation...
Evaluate annotation type bbox
Killed
----------------------------><----------------------------------

Please see the attached log file.
20240809_104155.log

I need to keep the version of MMtracking 0.14.0. Please let me know how to remove this error based on that version.