$ rg camera
smplifyx/cmd_parser.py
101: parser.add_argument('--camera_type', type=str, default='persp',
103: help='The type of camera used')
168: help='Which joints to use for initializing the camera')
174: ' the initial depth of the camera. The format' +
236: ' z coordinate of the camera translation')
smplifyx/main.py
38:from camera import create_camera
123: # Create the camera object
125: camera = create_camera(focal_length_x=focal_length,
130: if hasattr(camera, 'rotation'):
131: camera.rotation.requires_grad = False
178: camera = camera.to(device=device)
247: camera=camera,
smplifyx/mesh_viewer.py
50: camera_pose = np.eye(4)
51: camera_pose[:3, 3] = np.array([0, 0, 3])
52: self.scene.add(pc, pose=camera_pose)
smplifyx/camera.py
35:def create_camera(camera_type='persp', **kwargs):
36: if camera_type.lower() == 'persp':
39: raise ValueError('Uknown camera type: {}'.format(camera_type))
54: # the camera matrix
97: camera_mat = torch.zeros([self.batch_size, 2, 2],
99: camera_mat[:, 0, 0] = self.focal_length_x
100: camera_mat[:, 1, 1] = self.focal_length_y
102: camera_transform = transform_mat(self.rotation,
111: [camera_transform, points_h])
115: img_points = torch.einsum('bki,bji->bjk', [camera_mat, img_points]) \
smplifyx/fitting.py
47: ''' Initializes the camera translation vector
57: the camera translation
59: The focal length of the camera
70: The vector with the estimated camera location
217: optimizer, body_model, camera=None,
246: total_loss = loss(body_model_output, camera=camera,
275: elif loss_type == 'camera_init':
365: def forward(self, body_model_output, camera, gt_joints, joints_conf,
369: projected_joints = camera(body_model_output.joints)
486: def forward(self, body_model_output, camera, gt_joints,
489: projected_joints = camera(body_model_output.joints)
501: camera.translation[:, 2] - self.trans_estimation[:, 2]).pow(2))
smplifyx/fit_single_frame.py
52: camera,
266: # The indices of the joints used for the initialization of the camera
276: camera_loss = fitting.create_loss('camera_init',
281: camera_loss.trans_estimation[:] = init_t
314: camera_loss.reset_loss_weights({'data_weight': data_weight})
327: # Update the value of the translation of the camera as well as
330: camera.translation[:] = init_t.view_as(camera.translation)
331: camera.center[:] = torch.tensor([W, H], dtype=dtype) * 0.5
333: # Re-enable gradient calculation for the camera translation
334: camera.translation.requires_grad = True
336: camera_opt_params = [camera.translation, body_model.global_orient]
338: camera_optimizer, camera_create_graph = optim_factory.create_optimizer(
339: camera_opt_params,
343: fit_camera = monitor.create_fitting_closure(
344: camera_optimizer, body_model, camera, gt_joints,
345: camera_loss, create_graph=camera_create_graph,
350: # Step 1: Optimize over the torso joints the camera translation
352: # of the camera and the initial pose of the body model.
353: camera_init_start = time.time()
354: cam_init_loss_val = monitor.run_fitting(camera_optimizer,
355: fit_camera,
356: camera_opt_params, body_model,
365: time.time() - camera_init_start))
427: camera=camera, gt_joints=gt_joints,
467: result = {'camera_' + str(key): val.detach().cpu().numpy()
468: for key, val in camera.named_parameters()}
524: camera_center = camera.center.detach().cpu().numpy().squeeze()
525: camera_transl = camera.translation.detach().cpu().numpy().squeeze()
528: camera_transl[0] *= -1.0
530: camera_pose = np.eye(4)
531: camera_pose[:3, 3] = camera_transl
533: camera = pyrender.camera.IntrinsicsCamera(
535: cx=camera_center[0], cy=camera_center[1])
536: scene.add(camera, pose=camera_pose)
4938/31772MB(smplifyx)
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