Comments (2)
Thanks for releasing the fitting code! I found that the implementation of weakProjection_gpu is "not" correct. In simple terms, in your implementation, the projection is computed as spts + t. In the original HMR/SPIN implementation, it implies that the projection should be s(pts + t). In this way, this projection can be perfectly converted to perspective projection by setting the camera translation to [tx, ty, 2*f/s * img_res].
Anyway, it a fitting procedure, the network's parameters will be updated to output the correct t under this projection.
您好,我在使用作者制造的数据集标签的时候,我想利用它的弱透视标签对网格进行渲染,但是我遇到了一些问题,可以向您请教一下吗,如果可以的话加我一个微信,谢谢啦,我的微信号是zzydddd
from eft.
The easiest way to convert it to a weak perspective would be to get 2D image space cordinates as target_2d = ((scale * joint3d)[...,2] + translation)
and original 3D joints as origin_2d = joint3d[...,:2]
and estimate weak perspective translation
tmp_o = origin_2d - origin_2d.mean(axis=0)
tmp_t = target_2d - target_2d.mean(axis=0)
scale = (tmp_t * tmp_o).sum() / (tmp_o * tmp_o).sum()
trans = target_2d.mean(axis=0) / scale - origin_2d.mean(axis=0)
cam = np.zeros(3)
cam[0] = scale
cam[1:] = trans
#cam[0] = 2 * focal_length / (img_res * cam[0] + 1e-9)
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Related Issues (20)
- Visualising the prediction HOT 1
- fps? HOT 1
- How to set a perspective camera? HOT 1
- Could you please release the extrmly half-body cropping script? HOT 1
- OpenGL.error.GLError HOT 3
- code for the fitting procedure HOT 8
- 3DHP smpl parameters
- model weights for the pre-trained SPIN model
- about the fine-tuning part
- Output format and rescaling HOT 1
- about the data of parm_cam in render HOT 3
- how to render results by pytorch3d?
- JOINT_REGRESSOR_TRAIN_EXTRA_SMPLX
- which version of posetrack is used by eft
- About EFT Fitting data format
- The model trained with EFT datasets
- Can the MPJPE of fitting results be evaluated on the human 3.6m dataset HOT 1
- if、、、
- Use EFT as a Post-processing method in my test videos
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