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A PyTorch re-implementation of CPN (Cascaded Pyramid Network for Multi-Person Pose Estimation)

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https://github.com/elixir-lsp/vscode-elixir-ls/blob/b645862891c3d8c92b0a286848be8a999f29072b/src/test/suite/index.ts

Hello, I want to ask the use of parameter "symmetry" in the config file.

Can pre-trained model be loaded during training? I don't see the pretrained model loading code in the train.py

Hi, I'm trying to use the pretrained model but none of the tar files seem to be in working order. I get the following error: An error occurred while extracting...

I am running custom images through this model. All the images have been pre-proceed and cropped as to just include the human, and I've removed all annotation files and hardcoded...

How to use the pre-training network model to visualize the image test results? Is there a demo?

in this paper, I see that CPN used the image cropped in raw image with the bounding box of FPN as input. Where is the FPN in your reimplement ?

for global_output, label in zip(global_outputs, targets): num_points = global_output.size()[1] global_label = label * (valid > 1.1).type(torch.FloatTensor).view(-1, num_points, 1, 1) global_loss = criterion1(global_output, torch.autograd.Variable(global_label.cuda(async=True))) / 2.0 loss += global_loss global_loss_record +=...

enhancement
help wanted

There are 4 vars: target15 target11 target9 target7 what's the means of them?

相关资料不是很直观,想问下我直接把 ``` refine_target_var = torch.autograd.Variable(target7.cuda(async=True)) valid_var = torch.autograd.Variable(valid.cuda(async=True)) ``` 改成如下可以吗? ``` refine_target_var = torch.autograd.Variable(target7.cuda()) valid_var = torch.autograd.Variable(valid.cuda()) ```