change to-1 to to_world
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@@ -20,7 +20,7 @@ class PoseDiff:
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rot_angle_list = []
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trans_dist_list = []
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for output, data in zip(output_list, data_list):
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gt_pose_9d = data['best_to_1_pose_9d']
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gt_pose_9d = data['best_to_world_pose_9d']
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pred_pose_9d = output['pred_pose_9d']
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gt_rot_6d = gt_pose_9d[:, :6]
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gt_trans = gt_pose_9d[:, 6:]
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@@ -62,10 +62,10 @@ class ConverageRateIncrease:
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voxel_threshold_list = data["voxel_threshold"]
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filter_degree_list = data["filter_degree"]
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first_frame_to_world = data["first_frame_to_world"]
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pred_n_to_1_pose_mats = torch.eye(4, device=pred_pose_9ds.device).unsqueeze(0).repeat(pred_pose_9ds.shape[0], 1, 1)
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pred_n_to_1_pose_mats[:,:3,:3] = PoseUtil.rotation_6d_to_matrix_tensor_batch(pred_pose_9ds[:, :6])
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pred_n_to_1_pose_mats[:,:3,3] = pred_pose_9ds[:, 6:]
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pred_n_to_world_pose_mats = torch.matmul(first_frame_to_world, pred_n_to_1_pose_mats)
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pred_n_to_world_pose_mats = torch.eye(4, device=pred_pose_9ds.device).unsqueeze(0).repeat(pred_pose_9ds.shape[0], 1, 1)
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pred_n_to_world_pose_mats[:,:3,:3] = PoseUtil.rotation_6d_to_matrix_tensor_batch(pred_pose_9ds[:, :6])
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pred_n_to_world_pose_mats[:,:3,3] = pred_pose_9ds[:, 6:]
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pred_n_to_world_pose_mats = torch.matmul(first_frame_to_world, pred_n_to_world_pose_mats)
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for idx in range(len(scanned_cr)):
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model_points_normals = model_points_normals_list[idx]
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scanned_view_pts = scanned_view_pts_list[idx]
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