How can I change the cartoon character?

[CheungBH]

Hello. Thanks for your work.
I successfully ran your demo webcam.sh, which generates a cartoon character like this.

I wonder how to generate such a character, and can I change it? Any there any references about it?

[Arthur151]

Here is the guidance
https://github.com/Arthur151/ROMP/blob/master/docs/config_guide.md#mesh_cloth-str
By setting the mesh color, you can change the color of naked mesh or change the cloth/appearance of the mesh.
We provide a wordrobe for you to choose.

[CheungBH]

Thank you for your reply. I saw the constants.
And I wonder where are the parameters controlling the current color?

[Arthur151]

Set it at

ROMP/configs/webcam.yml

Line 36 in 653a0c9

mesh_cloth: '001' # 'random' #

It incluence the code at

ROMP/romp/lib/visualization/create_meshes.py

Line 51 in 653a0c9

def create_smpl_mesh():

[CheungBH]

Thank you. I have successfully change the character clothes.
By the way, I wonder how to generate the .jpg files in the model_data/wardrobe? Are there any tools you are using?

[Arthur151]

Those are texture UV maps of SMPL mesh.
Some of those are obtained from
https://github.com/bharat-b7/MultiGarmentNetwork#dress-smpl-body-model-with-our-digital-wardrobe

[CheungBH]

Thank you so much!
I ran your demo and it works. However, I can only see one person even I am inputting a multiple people video. Are there any limitations on showing multiple people?
My target is that I want to read different video sources, and then merge the extracted human mesh into one image. How do you think of its feasibility?

[Arthur151]

Please set the config setting

show_largest: False

Besides, I think it is highly feasible.

[CheungBH]

Thank you for your help! Maybe I have achieved.
BTW, I found that the inference is two times lower when feeding 2 videos, which results from inferring with the function forwarding single image twice.

ROMP/romp/predict/base_predictor.py

Line 43 in 653a0c9

def single_image_forward(self,image):

In this situation, I want to achieve inference with a batch of multiple images and obtain multiple outputs instead.
Are there any functions provided? I think it may be contained in the train or validation functions?