A2S with ModelAgency data about shapy

[jongunee]

Solved!

it was because of the unit

/shapy/attributes/attributes/dataloader/demo.py

class DEMO_A2S():
    def __init__(
        self,
        #betas_folder='../samples/shapy_fit/',
        ds_gender='female',
        model_gender='neutral',
        model_type='smplx',
        rating_folder='../samples/attributes/'
    ):
        
        ....

        #self.db['height_gt'] = self.db['heights'].astype(np.float32) #before
        self.db['height_gt'] = self.db['heights'].astype(np.float32) / 100 #after
        self.db['chest'] = self.db['bust'].astype(np.float32) / 100
        self.db['waist'] = self.db['waist'].astype(np.float32) / 100
        self.db['hips'] = self.db['hips'].astype(np.float32) / 100

In ModelAgency dataset file, units are all "cm", so i think it was not matched.

I have another question.
There are no "weights" GT data in ModelAgency file, so i cannot execute "ahwcwh2s".
Is there any dataset that satisfies all conditions?

• linguistic attributes
• heights
• weights
• waist
• hips
• bust

[Rut-B]

@jongunee
I'm trying to figure out how to run the shapy model on my own RGB images, without needing any additional files like keypoints or vertices.

I would greatly appreciate it if you could provide me an explanation of how to run the code with my RGB images only - to get the measurements of the body

Thank you very much!

[jongunee]

Oh sorry for late reply...
I completely forgot about it.

Unfortunately, �what I've done is inferred using the A2S function.
That means, i inferred 3d mesh using linguistic attributes like below.

"attributes": [
    2.4285714285714284,
    2.5,
    3.2857142857142856,
    2.0714285714285716,
    4.285714285714286,
    3.0,
    3.5,
    3.9285714285714284,
    3.357142857142857,
    2.857142857142857,
    1.4285714285714286,
    1.7857142857142858,
    3.0,
    1.6428571428571428,
    4.142857142857143
]

to 3d mesh output.

So i didn't use RGB images in this case.
If i test your case, let you know.