about the input of fit.fit_point about face3d HOT 6 OPEN

I guess the x should be the 68 2d points. But I get 68 points from 2d image. But I get non-ideal result. How to normalization the points?

I resolve the question by x= x - np.mean(x,axis=0) x[:1] = -x[:,1] . But I don't sure if it is right.

from face3d.

hello professor, i don't know it exactly what is the two input:
x: (n, 2) image points
X_ind: (n,) corresponding Model vertex indices
is x just a picture?
and is X_ind generated by morphable.generate_vertices?

the ame problem .do you got it?

from face3d.

the same question, can anyone have explantion?

from face3d.

I have get a good result.


I use the code bellow, x is 68d face keypoint
x = x / np.max(x) * 255
x -= np.mean(x)

from face3d.

I have get a good result. I use the code bellow, x is 68d face keypoint x = x / np.max(x) * 255 x -= np.mean(x)

Hi, can you please share how you get the 2D point? And how to get fitted texture?

from face3d.

Have you solved this problem? Why is my output image reversed?
The generated picture is as follows

the orignial pose image

and I use 68 key points to fit the generated image, and the fit picture is as follows，I dont know why i get such a strange picture

from face3d.