Custom image
hbinol opened this issue · 16 comments
Nice work!
I wonder how can I apply this for a custom image?
I guess I need both
- a landmark file ( landmarkpath = os.path.sep.join([input_folder, image_name + '.npy']) )
- image mask file ( image_mask_path = os.path.sep.join([image_mask_folder, image_name + '.npy']) )
for the custom image, right? Do I need more than this? How can I obtain these files for a custom image?
Thanks!
Yes, you would need both, as we've described in the readme file.
Thank you for your answer.
The next question is how can I generate these .npy files? Is there any sample script for those applications (face_alignment & face_seg)?
Thank you for your answer.
The next question is how can I generate these .npy files? Is there any sample script for those applications (face_alignment & face_seg)?
my fork solves the custom image
Thank you so much @JacksonL1
Do you have any idea about how I can pick a point (or points) on the neck of the initial 3D mesh template and follow its trajectory during photometric optimization? In a nutshell, I want to know where are the neck points of the final mesh compared to 2D or 3D landmarks.
Thank you so much @JacksonL1
Do you have any idea about how I can pick a point (or points) on the neck of the initial 3D mesh template and follow its trajectory during photometric optimization? In a nutshell, I want to know where are the neck points of the final mesh compared to 2D or 3D landmarks.
I just know that at face-parsing.Pytorch project, the 14th part is neck.
use this part to generate the mask and calculate the photometric loss.
Hope answered your question
That's great! Thank you @JacksonL1
I need to solve the problem of distance calculation between a neck point and chin on the final 3D mesh.
I don't know how to get points on the neck. I'm sorry about that~
Hi @JacksonL1
For your work, I got an error like below
No such file or directory: './model/s3fd.pth'
I found that later, but now there is another missing file
/model/face_seg.pth
@hbinol
if you can not use the Baidu Cloud, also can find the model at Google Cloud
@JacksonL1 I need access to Google Cloud. I believe I've already requested access.
@hbinol download official pre-train model and rename to face_seg.pth
@hbinol download official pre-train model and rename to face_seg.pth
Hi @JacksonL1 Thanks for your work.
I just met a problem 'Expected object of scalar double but got scalar type float for sequence element 4 when running your package. It comes from 'wj_fitting.py, line 175, in optimize'. Do you have any idea about this? Thank you.
@hbinol download official pre-train model and rename to face_seg.pth
Hi @JacksonL1 Thanks for your work.
I just met a problem 'Expected object of scalar double but got scalar type float for sequence element 4 when running your package. It comes from 'wj_fitting.py, line 175, in optimize'. Do you have any idea about this? Thank you.
I just run the code, it will run smoothly.
The error seems like data type is wrong. Could you show me the code near by 175 and full error message?