Behavior for no predictions during visualization

[holtvogt]

Describe the bug
A RuntimeError is thrown during visualization with no predictions.

Discussion
I'd like to know how this error should be handled. As a check for None predicted labels is already done, I assume that the behavior on zero predictions should be the same. See below in Bug fix.

Reproduction
Use a model which does not predict labels on a test run.

1. What command or script did you run?

python ./tools/test.py <config.py> <checkpoint.pth> --show --show-dir <show-dir>

2. Did you make any modifications on the code or config? Did you understand what you have modified?

• Yes, I used my own config
• Yes, I understood

3. What dataset did you use?

• I used my own custom dataset

Environment

1. Please run python mmdet3d/utils/collect_env.py to collect necessary environment information and paste it here.

sys.platform: linux
Python: 3.8.13 (default, Mar 28 2022, 11:38:47) [GCC 7.5.0]
CUDA available: True
GPU 0: NVIDIA GeForce GTX 1080 Ti
CUDA_HOME: /usr/local/cuda
NVCC: Cuda compilation tools, release 11.6, V11.6.124
GCC: gcc (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0
PyTorch: 1.10.1
PyTorch compiling details: PyTorch built with:
  - GCC 7.3
  - C++ Version: 201402
  - Intel(R) oneAPI Math Kernel Library Version 2021.4-Product Build 20210904 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 11.3
  - 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_61,code=sm_61;-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;-gencode;arch=compute_37,code=compute_37
  - CuDNN 8.2
  - Magma 2.5.2
  - Build settings: BLAS_INFO=mkl, BUILD_TYPE=Release, CUDA_VERSION=11.3, CUDNN_VERSION=8.2.0, 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=1.10.1, 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: 0.11.2
OpenCV: 4.6.0
MMCV: 1.5.2
MMCV Compiler: GCC 7.3
MMCV CUDA Compiler: 11.3
MMDetection: 2.25.1
MMSegmentation: 0.27.0
MMDetection3D: 1.0.0rc3+eb5a5a2
spconv2.0: True

Error traceback

  File "/workspace/mmdetection3d/tools/test.py", line 260, in <module>
    main()
  File "/workspace/mmdetection3d/tools/test.py", line 230, in main
    outputs = single_gpu_test(model, data_loader, args.show, args.show_dir)
  File "/workspace/mmdetection3d/mmdet3d/apis/test.py", line 48, in single_gpu_test
    model.module.show_results(
  File "/workspace/mmdetection3d/mmdet3d/models/detectors/base.py", line 120, in show_results
    show_result(
  File "/workspace/mmdetection3d/mmdet3d/core/visualizer/show_result.py", line 110, in show_result
    0, 255, size=(pred_labels.max() + 1, 3)) / 256
RuntimeError: max(): Expected reduction dim to be specified for input.numel() == 0. Specify the reduction dim with the 'dim' argument.

Bug fix
As mentioned in #1461, we could add pred_labels.numel() == 0 check in line

mmdetection3d/mmdet3d/core/visualizer/show_result.py

Line 106 in 073f353

if pred_labels is None:

here to start visualization without available predictions. I can open a pull request to do so.

[ZCMax]

I think it's a reasonable solution, you can open a PR to fix this issue.

[holtvogt]

Solved with #1725