Open Ned09 opened 2 years ago
How do you get the five faces of every subject? (vggface2_val_list_max_normal_100_ring_5_1_serial.npy') I could get landmarks or skin mask. Author choose five normoal faces with every identity. It is more important!
@littlePrince126 Can you please help me on generating facial masks? I couldn't install https://github.com/YuvalNirkin/face_segmentation
when I run the repository I get this error
@littlePrince126 I want to try with some simple data just to run the code so I didnt get the five faces from every object yet. we can work on it together if you want.
@Ned09 It seems that you don't set the variables in a right way. You can have a try by using the python script.
@littlePrince126 Do you mean without installing this repository and just by running the python script in the "face-segmentation/interfaces/python/face-seg.py" , I can generate the segmentation images?
@Ned09 Yes, because you should compile caffe and opencv if you want to install this repo. Anyway, you need a caffe environment at first.
@littlePrince126 Hi, what's your GPU used when runing face-segmentation? when I use caffe-gpu env with docker,
F1103 05:56:53.555362 430 pooling_layer.cu:212] Check failed: error == cudaSuccess (8 vs. 0) invalid device function
I got this error, It may because the difference of GPU computation ability between authur's and mine.
What's your situation?
@Shelomith Telsa P100
identity. It is more important!
Have you got the file(vggface2_val_list_max_normal_100_ring_5_1_serial.npy)? I would really appreciate it , if you share it with me.
@1180800817 I generate it by myself. You can generate it with dataset(VggFace2,BUPT-Face,voxceleb2 ). voxceleb2 is a video dataset, you should choose good quality videos first, then get the images from videos.
@littlePrince126 Can you reproduce the reported result on NoW using your generated data? Additionally, could you please share vggface2_val_list_max_normal_100_ring_5_1_serial.npy with me? Even a demo is helpful! I just want to know the explicit format of this file.
@lhyfst I trained the model without any pretrained model. Finally, I get median1.217mm mean1.517mm std 1.249mm with NOW validation set. (DECA median:1.18, mean:1.46mm,std:1.25mm)
I've test DECA pretrained model in NoW dataset, result is median:1.15, mean:1.44mm,std:1.24mm... but in DECA paper they report median:1.09, mean:1.38mm,std:1.18mm @littlePrince126 朋友,方便加个微信讨论吗?
@Shelomith Because your results is based on validation set. (median:1.09, mean:1.38mm,std:1.18mm )This result is based on test set. But I only get results(meadian:1.1778,Mean:1.4636,std:1.2529) with DECA model.
meadian:1.1778,Mean:1.4636,std:1.2529 This result is the same as papr(DECA)
I've test DECA pretrained model in NoW dataset, result is median:1.15, mean:1.44mm,std:1.24mm... but in DECA paper they report median:1.09, mean:1.38mm,std:1.18mm @littlePrince126 朋友,方便加个微信讨论吗? hello 你好 最近也在跑这个代码 方便加个微信讨论吗?或者邮箱?
@super3kl wx: shelomith1001
@littlePrince126 Hi,can you share the method of choosing five normoal faces?Thank you!
@littlePrince126 你好,我最近在跑这个代码实验,我想请教一下你是怎么进行数据处理的,可以的话能否分享一下数据处理的代码,非常感谢!
@lhyfst I trained the model without any pretrained model. Finally, I get median1.217mm mean1.517mm std 1.249mm with NOW validation set. (DECA median:1.18, mean:1.46mm,std:1.25mm)
您好,方便给个联系方式吗?想请教一下怎么训练的,有偿。
@chen990627 @pfeducode @Eric3778 你们复现出来了吗?方便微信交流一下吗?
choose good quality videos
Hi, how do you choose good quality videos? @littlePrince126
@YalanHe 你好,查找不到该微信账号,是否账号有误
你能帮我制作面膜吗?我无法安装 https://github.com/YuvalNirkin/face_segmentation
当我运行存储库时,出现此错误
May I ask how you resolved this issue and ultimately achieved training?
How do you get the five faces of every subject? (vggface2_val_list_max_normal_100_ring_5_1_serial.npy') I could get landmarks or skin mask. Author choose five normoal faces with every identity. It is more important!
Hi!Can you reproduce the model training?
Can you please give me more explanation about preparing data for training the model from scratch? I want to use VGGFace2 for the first step. Do I need to generate landmarks for every image and save the landmarks as a text file or npy file? and what about masks? I really appreciate it if you give me some clue
I am trying to do this step: b. Prepare label FAN to predict 68 2D landmark face_segmentation to get skin mask