Args: body_model: config or an object of body model. num_epochs: number of epochs of registration camera: config or an object of camera img_res: image resolution. If tuple, values are (width, height) stages: config of registration
(self,
body_model: Union[dict, torch.nn.Module],
num_epochs: int = 20,
camera: Union[dict, torch.nn.Module] = None,
img_res: Union[Tuple[int], int] = 224,
stages: dict = None,
optimizer: dict = None,
keypoints2d_loss: dict = None,
keypoints3d_loss: dict = None,
shape_prior_loss: dict = None,
joint_prior_loss: dict = None,
smooth_loss: dict = None,
pose_prior_loss: dict = None,
pose_reg_loss: dict = None,
limb_length_loss: dict = None,
use_one_betas_per_video: bool = False,
ignore_keypoints: List[int] = None,
device=torch.device(
'cuda' if torch.cuda.is_available() else 'cpu'),
verbose: bool = False)
| 52 | """ |
| 53 | |
| 54 | def __init__(self, |
| 55 | body_model: Union[dict, torch.nn.Module], |
| 56 | num_epochs: int = 20, |
| 57 | camera: Union[dict, torch.nn.Module] = None, |
| 58 | img_res: Union[Tuple[int], int] = 224, |
| 59 | stages: dict = None, |
| 60 | optimizer: dict = None, |
| 61 | keypoints2d_loss: dict = None, |
| 62 | keypoints3d_loss: dict = None, |
| 63 | shape_prior_loss: dict = None, |
| 64 | joint_prior_loss: dict = None, |
| 65 | smooth_loss: dict = None, |
| 66 | pose_prior_loss: dict = None, |
| 67 | pose_reg_loss: dict = None, |
| 68 | limb_length_loss: dict = None, |
| 69 | use_one_betas_per_video: bool = False, |
| 70 | ignore_keypoints: List[int] = None, |
| 71 | device=torch.device( |
| 72 | 'cuda' if torch.cuda.is_available() else 'cpu'), |
| 73 | verbose: bool = False) -> None: |
| 74 | """ |
| 75 | Args: |
| 76 | body_model: config or an object of body model. |
| 77 | num_epochs: number of epochs of registration |
| 78 | camera: config or an object of camera |
| 79 | img_res: image resolution. If tuple, values are (width, height) |
| 80 | stages: config of registration stages |
| 81 | optimizer: config of optimizer |
| 82 | keypoints2d_loss: config of keypoint 2D loss |
| 83 | keypoints3d_loss: config of keypoint 3D loss |
| 84 | shape_prior_loss: config of shape prior loss. |
| 85 | Used to prevent extreme shapes. |
| 86 | joint_prior_loss: config of joint prior loss. |
| 87 | Used to prevent large joint rotations. |
| 88 | smooth_loss: config of smooth loss. |
| 89 | Used to prevent jittering by temporal smoothing. |
| 90 | pose_prior_loss: config of pose prior loss. |
| 91 | Used to prevent unnatural pose. |
| 92 | pose_reg_loss: config of pose regularizer loss. |
| 93 | Used to prevent pose being too large. |
| 94 | limb_length_loss: config of limb length loss. |
| 95 | Used to prevent the change of body shape. |
| 96 | use_one_betas_per_video: whether to use the same beta parameters |
| 97 | for all frames in a single video sequence. |
| 98 | ignore_keypoints: list of keypoint names to ignore in keypoint |
| 99 | loss computation |
| 100 | device: torch device |
| 101 | verbose: whether to print information during registration |
| 102 | |
| 103 | Returns: |
| 104 | None |
| 105 | """ |
| 106 | |
| 107 | self.use_one_betas_per_video = use_one_betas_per_video |
| 108 | self.num_epochs = num_epochs |
| 109 | self.img_res = img_res |
| 110 | self.device = device |
| 111 | self.stage_config = stages |
nothing calls this directly
no test coverage detected