edit headpose only and keep the expression

[Farewell-ME]

hi there, great project!
in the inference.py --flame mode, in the demo that edits exp, it seems that the exp coef is randomly given rather than keep the source image expression
for i in range(10):
exp = torch.zeros(1, 100).to(src_img.device) # (1, 100)
exp[0, 0] = 2 * i / 10
Is there any way to edit the head pose only and keep the input face expression the same?

[HowieMa]

You can keep the exp as a None value. i.e., if you don't pass the exp value, it will follow the original expression coefficient. The logic is here:

CVTHead/models/cvthead.py

Line 436 in 8f75b22

if exp is not None:

[Farewell-ME]

i see, then the drv_codedict['exp'] will keep the same as：
src_codedict = self.deca.encode(crop_src_img, use_detail=True)
however, when I input './examples/2.png' and print its src_codedict['exp'] the 50-dims FLAME exp coeff, it is very close to zeors like tensor([[ 0.6193, -0.2783, 0.2837, 0.3630, -0.0149, -0.3751, -0.2054, 0.2826,
-0.1413, 0.4739, 0.0610, 0.7318, 0.3283, -0.2038, 0.0750, -0.2088,
-0.2746, -0.0101, 0.1676, 0.3696, -0.0183, -0.1984, -0.0575, -0.1980,
-0.0062, -0.0128, 0.1302, 0.0862, -0.1784, 0.0785, -0.1404, 0.1140,
0.0795, -0.0530, 0.0306, -0.0548, 0.0012, -0.0391, 0.0938, -0.1831,
-0.4531, 0.1092, -0.0538, -0.0640, -0.1024, -0.0648, 0.0657, 0.1505,
0.1055, 0.0444]], device='cuda:0')
and the output pose.gif is close to neutral face and not consistent with the source image

is there any tricks in deca.encode and deca.decode?

[HowieMa]

Oh you also need to keep the original jaw pose.
In the flame model, the model is always closed if you keep the default jaw pose.