face-alignment-training

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Hi Adrian, First of all, Thanks for this great work. I was following the PyTorch version of this code for the training of the FAN model on my own dataset....

Mujtaba-Saeed

How can I get the whole Network structure of FAN ?

1

I have tried your python code of FAN which actually has a very good result. But I have a visualize problem. Sorry that i am unfamiliar with lua and torch....

colacool

I met a problem when I run this code.

1

Following the README document,I run: ``` th main.lua -data /media/john/Documents/Dataset/300W_LP/ ``` The construction of dataset directory is: . ├── AFW ├── AFW_Flip ├── Code │   ├── Mex │   └── ModelGeneration...

ghost

Error in building dataset, confusion on training data directory structure?

3

Hi, thanks for posting the code for the face alignment training, really appreciate the awesome work! I'm trying to simply recreate the training results for my own understanding, although I'm...

joseph-zhong

you codes seem just for 300W-LP, if I want to train on 300W dataset, how can I change the codes, or just change the the load to image file?

wqz960

Training code for pytorch?

4

Hi, great job! I have tested your pytorch code, but wondering if the training code will be available for pytorch? Thanks.

wenxuanmou

Batchnorm parameter

1

``` local function convBlock(numIn, numOut, order) local cnet = nn.Sequential() :add(batchnorm(numIn,1e-5,false)) :add(relu(true)) :add(conv(numIn,numOut/2,3,3,1,1,1,1):noBias()) :add(nn.ConcatTable() :add(nn.Identity()) :add(nn.Sequential() :add(nn.Sequential() :add(batchnorm(numOut/2,1e-5,false)) :add(relu(true)) :add(conv(numOut/2,numOut/4,3,3,1,1,1,1):noBias()) ) ``` batchnorm(numIn,1e-5,false) Dose this statement want to set affine...

zhengge

I have my own dataset with the landmark annotations like .pts file, txt file or csv file, how can I convert my annotation consistent with your dataset annotation in .t7?...

kwkwvenusgod

Hope to get a dockerfile

1

I have tested your demo,it's exiciting!And I want to trian my model,thank you

PyJulie