some questions about keypoints training? about multiposenet.pytorch

[LiMeng95]

hi,

1. The task Keypoint Estimation Subnet with person segmentation mask is still in to-do list, I have not added it in keypoints subnet yet.

2. The batch-size of dataloader is linearly related to the number of GPUs. Specifically, batch-size will be multiplied by the number of GPUs you enabled in CUDA_VISIBLES_DEVICES. Related code is in multipose_keypoint_train.py#L61.
   That is more GPUs means more pre-processing such as data agumentation, GT generation and so on. All of these pre-processing are on CPUs. So, I think the training speed maybe limited by not only the GPU but the CPUs' computational ability.

[lunalulu]

@LiMeng95 thanks very much~

Another question, I trained a resnet50 as backbone, but compared to ckpt_baseline_resnet101.h5 in your project, the inference FPS went up by only 2 frames.
Do you have training with resnet50? How fast is the result compared with resnet101?Can you provide one resnet50?
thanks

[LiMeng95]

Sorry, I didn't train with resnet50. Maybe the backbone is not the main limitation of inference FPS, other parts like person detection will also take some time.