dong-x16 / portraitnet Goto Github PK

I use the tar command as below...

tar xvf mobilenetv2_total_with_prior_channel.tar

The error message as follows

tar: This does not look like a tar archive
tar: Skipping to next header
tar: A lone zero block at 290
tar: Exiting with failure status due to previous errors

How can I get model from .tar file ?
Please help me.
Thanks

Dear dong-x16,
Thank you for sharing your model code.
But I can't extract the model tar files that stored in Baidu cloud.

When I run tar xvf, following error occurs.

$ tar -xvf mobilenetv2_eg1800_with_two_auxiliary_losses.tar
tar: This does not look like a tar archive
tar: Skipping to next header
tar: Exiting with failure status due to previous errors

All 3 model tars are same.
Please check it again.

Best regards.

Hello
How are you?
Thanks for contributing this project.
I found a strange part in your code.

I know that background is 0 and foreground is 1 in case of portrait mask.
Is it right?

您好，根据您提供的源码，本人已经全部调试完成，可以进行训练。但是为什么EG1800数据集的labels是全黑，而不是人像的掩膜呢？所以在测试时也只是显示背景，而没有人像显示？

Thanks for contributing this project.
When I was training, I changed the value of 'resume' to continue training, but an error occurred. I don’t know if there are any details that I didn’t notice.

Hello,

You seem to have a good work here, could you please add a license to the code you are distributing?
https://help.github.com/en/github/creating-cloning-and-archiving-repositories/licensing-a-repository
"You're under no obligation to choose a license. However, without a license, the default copyright laws apply, meaning that you retain all rights to your source code and no one may reproduce, distribute, or create derivative works from your work. If you're creating an open source project, we strongly encourage you to include an open source license. The Open Source Guide provides additional guidance on choosing the correct license for your project."

Thanks

Hello
How are you?
Thanks for contributing this project.
I am training a new model with config model_mobilenetv2_with_two_auxiliary_losses and AISegment dataset for 8 days.
But it is strange that the best model is not updated for 7 days.
What do u think the reason?

when processing the images in supervisely_face_train_easy.txt and supervisely_face_test_easy.txt, I found these following images appear both in the train set and the test set.

[('Supervisely_face/SuperviselyPerson_ds4/img/pexels-photo-785667.png',
  'Supervisely_face/SuperviselyPerson_ds2/img/pexels-photo-785667.png'),
 ('Supervisely_face/SuperviselyPerson_ds5/img/pexels-photo-356170.png',
  'Supervisely_face/SuperviselyPerson_ds1/img/pexels-photo-356170.png'),
 ('Supervisely_face/SuperviselyPerson_ds5/img/pexels-photo-681294.png',
  'Supervisely_face/SuperviselyPerson_ds1/img/pexels-photo-681294.png'),
 ('Supervisely_face/SuperviselyPerson_ds5/img/pexels-photo-681294.png',
  'Supervisely_face/SuperviselyPerson_ds1/img/pexels-photo-681294.png'),
 ('Supervisely_face/SuperviselyPerson_ds5/img/pexels-photo-681294.png',
  'Supervisely_face/SuperviselyPerson_ds1/img/pexels-photo-681294.png'),
 ('Supervisely_face/SuperviselyPerson_ds5/img/pexels-photo-681294.png',
  'Supervisely_face/SuperviselyPerson_ds1/img/pexels-photo-681294.png'),
 ('Supervisely_face/SuperviselyPerson_ds2/img/pexels-photo-221212.png',
  'Supervisely_face/SuperviselyPerson_ds4/img/pexels-photo-221212.png'),
 ('Supervisely_face/SuperviselyPerson_ds3/img/pexels-photo-681294.png',
  'Supervisely_face/SuperviselyPerson_ds1/img/pexels-photo-681294.png'),
 ('Supervisely_face/SuperviselyPerson_ds3/img/pexels-photo-681294.png',
  'Supervisely_face/SuperviselyPerson_ds1/img/pexels-photo-681294.png'),
 ('Supervisely_face/SuperviselyPerson_ds3/img/pexels-photo-681294.png',
  'Supervisely_face/SuperviselyPerson_ds1/img/pexels-photo-681294.png'),
 ('Supervisely_face/SuperviselyPerson_ds3/img/pexels-photo-681294.png',
  'Supervisely_face/SuperviselyPerson_ds1/img/pexels-photo-681294.png'),
 ('Supervisely_face/SuperviselyPerson_ds5/img/pexels-photo-365373.png',
  'Supervisely_face/SuperviselyPerson_ds1/img/pexels-photo-365373.png'),
 ('Supervisely_face/SuperviselyPerson_ds2/img/pexels-photo-432506.png',
  'Supervisely_face/SuperviselyPerson_ds5/img/pexels-photo-432506.png'),
 ('Supervisely_face/SuperviselyPerson_ds5/img/pexels-photo-316680.png',
  'Supervisely_face/SuperviselyPerson_ds2/img/pexels-photo-316680.png'),
 ('Supervisely_face/SuperviselyPerson_ds1/img/pexels-photo-569163.png',
  'Supervisely_face/SuperviselyPerson_ds5/img/pexels-photo-569163.png'),
 ('Supervisely_face/SuperviselyPerson_ds5/img/light-sunset-man-trees.png',
  'Supervisely_face/SuperviselyPerson_ds2/img/light-sunset-man-trees.png')]

In each tuple, the first dir appears in the train set and the second one appears in the test set. Though in different folder, the images are actually the same.

Thanks for your sharing @dong-x16 .

I have an issue. When I train my model without the prior channel, the mIoU of the model can reach 94%, but when I add prior channel, the mIoU of the model is much lower than without the prior channel, which even cannot reach 90%.

Could you give me a piece of advice about how to set the parameters of every loss?

Thanks a lot.

HI,参照myTest目录下的video测试demo脚本,
下载页面提供的模型链接文件
将 154行 ：File = os.path.join(exp_args.model_root, 'model_best.pth.tar')
改成
bestModelFile = os.path.join(exp_args.model_root, 'mobilenetv2_total_with_prior_channel.tar')
运行后产生如下错误

videotest.py:101: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details.
cf = load(cont)
finish load config file ...
Traceback (most recent call last):
File "videotest.py", line 158, in
netmodel_video.load_state_dict(checkpoint_video['state_dict'])
File "/home/hcruise/.local/lib/python2.7/site-packages/torch/nn/modules/module.py", line 487, in load_state_dict
.format(name, own_state[name].size(), param.size()))
RuntimeError: While copying the parameter named stage0.0.weight, whose dimensions in the model are torch.Size([32, 4, 3, 3]) and whose dimensions in the checkpoint are torch.Size([32, 3, 3, 3]).

这是什么情况，我是安装主页上说的安装的pytorch 0.3.0post4, 及torchvision 0.2.0
为什么load模型后又说自己的模型dimension不对呢？

mobilenetv2_total_with_prior_channel(Training on Human with prior channel)
which human dataset？ 谢了

Hi Thanks for your effort.
Is there available google drive link for Supervisely portrait dataset?
I cannot access in baidu drive...

感谢作者！本人利用您训练的模型pretrained_mobilenetv2_base.pth，进行图片和视频测试时，都无法成功测试，只显示了黑色背景，并没有将人像抠出来的实际效果图，然后我又看了您的EG1800数据集，labels标签都是黑色背景，并不是人像掩膜。希望作者看到后提供我一个合理的解释。谢谢！

I can't unarchive them by tar or 7zip.
Here are the log:

7z.exe a mobilenetv2_total_with_prior_channel.tar

7-Zip 19.00 (x64) : Copyright (c) 1999-2018 Igor Pavlov : 2019-02-21

Open archive: mobilenetv2_total_with_prior_channel.tar
ERROR: mobilenetv2_total_with_prior_channel.tar
mobilenetv2_total_with_prior_channel.tar
Open ERROR: Can not open the file as [tar] archive

ERRORS:
Is not archive