Comments (5)
In theory, it should be. However, currently we have not added the script but it should be doable. As official MGAN repo does not provide configs for the training part. Based on the paper, my impression is that they are quite similar/ or exactly are that of Adaptive Faster R-CNN, of course they use the visible box/mask additionally.
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Great thanks.
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Hi, I also found that the config file of the MGAN doesn't provide the training script until now, if it means until now we still cannot train the MGAN using Pedestron? @hasanirtiza
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True, unfortunately the authors never released the training configs for MGAN. You can check on the official repo. However, I did stumble upon this config, it does provide training configs, I have never tried it myself, may be you can see if it works.
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Thanks! Because I saw the pre-trained MAGN model in the benchmark table listed in the README is available, but the config for the training MGAN doesn't exist so I was little confused. How did you generate the pre-trained MGAN model?
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Related Issues (20)
- Impact of mean_teacher on the training process HOT 1
- CSP pretrained weights HOT 1
- Reproduce resutls on Caltech dataset HOT 3
- Information regarding the training HOT 1
- Image_scale of Caltech while training HOT 6
- ImportError: /pedestron/tools/../mmdet/ops/dcn/deform_conv_cuda.cpython-36m-x86_64-linux-gnu.so: undefined symbol: _ZN6caffe26detail37_typeMetaDataInstance_preallocated_32E HOT 1
- RuntimeError: Expected cudaMemcpy(&mask_host[0], mask_dev, sizeof(unsigned long long) * boxes_num * col_blocks, cudaMemcpyDeviceToHost) == cudaSuccess to be true, but got false. (Could this error message be improved? If so, please report an enhancement request to PyTorch.) HOT 1
- Training citypersons with all the instances? HOT 1
- Welcome update to OpenMMLab 2.0
- Runtime error - Training with EuroCity persons HOT 1
- Training Caltech using CSP HOT 1
- What's ignore_other_vru in ECP evaluation? HOT 2
- result has no bbox HOT 5
- mmdet/ops/roi_align/src/roi_align_kernel.cu(145): error: identifier "THCudaCheck" is undefined HOT 1
- Update instruction for 2023 HOT 1
- custom dataset test HOT 1
- Evaluate different pre-trained model
- A request for advice on pedestrian tracking work. HOT 2
- a bug when converting crowdhuman to coco format
- Testing a CP trained model on ECP val dataset HOT 3
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