[Reimplementation]

[FengRongYue]

Prerequisite

• [X] I have searched Issues and Discussions but cannot get the expected help.
• [X] I have read the FAQ documentation but cannot get the expected help.
• [X] The bug has not been fixed in the latest version (master) or latest version (3.x).

💬 Describe the reimplementation questions

1. 我通过继承的方式写了一个centernet的配置文件，但是训练起来后总是报类似于AssertionError: The num_classes (3) in DeformableDETRHead of MMDataParallel does not matches the length of CLASSES 80) in CocoDataset这样的错误。我尝试修改 mmdet/datasets/coco.py 下的CoCoDataset和mmdet/core/evaluation/class_names.py下的coco_classes()这个问题不再出现。我觉的改源码应该不是一个好的解决办法，那么应该怎么办？ 这是我用的配置文件 centernet_resnet18_dcnv2_140e_coco.zip

2. 我的训练时间非常长，我只是训练常见的模型如fasterrcnn和centernet,但是耗费的时间是两天和一天，不知道怎么解决。

Environment

sys.platform: linux Python: 3.8.10 (default, Jun 4 2021, 15:09:15) [GCC 7.5.0] CUDA available: True GPU 0: NVIDIA GeForce RTX 3090 CUDA_HOME: /usr/local/cuda NVCC: Cuda compilation tools, release 11.3, V11.3.109 GCC: gcc (Ubuntu 9.4.0-1ubuntu1~20.04.1) 9.4.0 PyTorch: 1.11.0+cu113 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 v2.5.2 (Git Hash a9302535553c73243c632ad3c4c80beec3d19a1e)
• 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_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 8.2
• 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-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=1.11.0, USE_CUDA=ON, USE_CUDNN=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=OFF, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, USE_ROCM=OFF,

TorchVision: 0.12.0+cu113 OpenCV: 4.6.0 MMCV: 1.7.1 MMCV Compiler: GCC 9.3 MMCV CUDA Compiler: 11.3 MMDetection: 2.28.1+c14dd6c root@autodl-container-995011b452-9370f589:~/autodl-tmp/mubiaojiance/mmdetection/mmdet#

Expected results

No response

Additional information

1.我使用了自己的配置文件，文件在上面给出来了。 2.我使用的是自己的数据集，数据集已经按照COCO格式处理了。

[FengRongYue]

上面Describe the reimplementation questions 里面的配置文件是我所继承的配置文件，我使用的配置文件是 AGAR_config.zip

[ZwwWayne]

You should also modify the dataset class, to make its number of classes to be 3. You can simple pass classes to the dataset

[FengRongYue]

You should also modify the dataset class, to make its number of classes to be 3. You can simple pass classes to the dataset

我试了，有用，谢谢。 我还有一个问题，我训练很慢该从哪方面找问题呢？我的数据集也不是很大5000张4000*4000的图片