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Functions736 in github.com/InternRobotics/NavDP

⨍ Functions 736◇ Types & classes 227↳ Endpoints 36
Method__init__
(self, size)
baselines/logoplanner/depth_anything/metric_depth/dataset/transform.py:251
Method__init__
(self, filelist_path, mode, size=(518, 518))
baselines/logoplanner/depth_anything/metric_depth/dataset/hypersim.py:27
Method__init__
(self, in_feature, out_feature)
baselines/logoplanner/depth_anything/metric_depth/depth_anything_v2/dpt.py:25
Method__init__
( self, encoder='vitl', features=256, out_channels=[256, 512, 1024, 1024],
baselines/logoplanner/depth_anything/metric_depth/depth_anything_v2/dpt.py:153
Method__init__
Args: img_size (int, tuple): input image size patch_size (int, tuple): patch size in_chans (int): number
baselines/logoplanner/depth_anything/metric_depth/depth_anything_v2/dinov2.py:45
Method__init__
Init. Args: features (int): number of features
baselines/logoplanner/depth_anything/metric_depth/depth_anything_v2/util/blocks.py:87
Method__init__
Init. Args: width (int): desired output width height (int): desired output height resize_target (bool, op
baselines/logoplanner/depth_anything/metric_depth/depth_anything_v2/util/transform.py:9
Method__init__
(self, mean, std)
baselines/logoplanner/depth_anything/metric_depth/depth_anything_v2/util/transform.py:129
Method__init__
(self)
baselines/logoplanner/depth_anything/metric_depth/depth_anything_v2/util/transform.py:143
Method__init__
(self, drop_prob=None)
baselines/logoplanner/depth_anything/metric_depth/depth_anything_v2/dinov2_layers/drop_path.py:30
Method__init__
( self, dim: int, num_heads: int, mlp_ratio: float = 4.0, qkv_bias: bo
baselines/logoplanner/depth_anything/metric_depth/depth_anything_v2/dinov2_layers/block.py:37
Method__init__
( self, dim: int, init_values: Union[float, Tensor] = 1e-5, inplace: bool = Fa
baselines/logoplanner/depth_anything/metric_depth/depth_anything_v2/dinov2_layers/layer_scale.py:17
Method__init__
( self, dim: int, num_heads: int = 8, qkv_bias: bool = False, proj_bia
baselines/logoplanner/depth_anything/metric_depth/depth_anything_v2/dinov2_layers/attention.py:30
Method__init__
( self, in_features: int, hidden_features: Optional[int] = None, out_features:
baselines/logoplanner/depth_anything/metric_depth/depth_anything_v2/dinov2_layers/mlp.py:18
Method__init__
( self, in_features: int, hidden_features: Optional[int] = None, out_features:
baselines/logoplanner/depth_anything/metric_depth/depth_anything_v2/dinov2_layers/swiglu_ffn.py:46
Method__init__
( self, img_size: Union[int, Tuple[int, int]] = 224, patch_size: Union[int, Tuple[int,
baselines/logoplanner/depth_anything/metric_depth/depth_anything_v2/dinov2_layers/patch_embed.py:38
Method__init__
(self, lambd=0.5)
baselines/logoplanner/depth_anything/metric_depth/util/loss.py:6
Method__init__
(self, global_planed_traj, N=20, desired_v=0.3, vx_max=0.4, vy_max=0.4, wz_max=0.4, ref_gap=
baselines/logoplanner/deployment/mpc_controller.py:7
Method__init__
( self, ckpt_path: str, device: Union[str, torch.device] = "cuda", )
baselines/ddppo/pointnav_network.py:46
Method__init__
( self, image_intrinsic: torch.Tensor, m2f_path: str, m2f_config_path: str,
baselines/viplanner/viplanner_agent.py:11
Method__init__
(self)
baselines/viplanner/traj_opt.py:15
Method__init__
(self)
baselines/viplanner/traj_opt.py:39
Method__init__
( self, layers, block=BasicBlock, groups=1, width_per_group=64,
baselines/viplanner/plannernet.py:72
Method__init__
( self, config_file="configs/coco/panoptic-segmentation/maskformer2_R50_bs16_50ep.yaml",
baselines/viplanner/m2f_inference.py:17
Method__init__
(self, encoder_channel=64, k=5)
baselines/viplanner/autoencoder.py:20
Method__init__
( self, train_cfg: TrainCfg, m2f_cfg=None, weight_path: Optional[str] = None,
baselines/viplanner/autoencoder.py:33
Method__init__
(self, in_channels, goal_channels, k=5)
baselines/viplanner/autoencoder.py:113
Method__init__
(self, cfg, weight_path: Optional[str] = None, freeze: bool = True)
baselines/viplanner/rgb_encoder.py:43
Method__init__
(self)
baselines/viplanner/configs/viplanner_sem_meta.py:238
Method__init__
(self, embed_dim, max_len=5000)
baselines/navdp/policy_backbone.py:20
Method__init__
(self, image_size=224, embed_size=512, memory_size=8,
baselines/navdp/policy_backbone.py:34
Method__init__
(self, image_size=224, embed_size=512, device='cuda:0')
baselines/navdp/policy_backbone.py:90
Method__init__
(self, image_size=224, embed_size=512, device='cuda:0')
baselines/navdp/policy_backbone.py:118
Method__init__
(self, image_size=224, memory_size=8, predict_size=24,
baselines/navdp/policy_network.py:10
Method__init__
(self, image_intrinsic, image_size=224, memory_size=8,
baselines/navdp/policy_agent.py:9
Method__init__
(self, in_feature, out_feature)
baselines/navdp/depth_anything/depth_anything_v2/dpt.py:25
Method__init__
( self, encoder='vitl', features=256, out_channels=[256, 512, 1024, 1024],
baselines/navdp/depth_anything/depth_anything_v2/dpt.py:154
Method__init__
Args: img_size (int, tuple): input image size patch_size (int, tuple): patch size in_chans (int): number
baselines/navdp/depth_anything/depth_anything_v2/dinov2.py:45
Method__init__
Init. Args: features (int): number of features
baselines/navdp/depth_anything/depth_anything_v2/util/blocks.py:87
Method__init__
Init. Args: width (int): desired output width height (int): desired output height resize_target (bool, op
baselines/navdp/depth_anything/depth_anything_v2/util/transform.py:9
Method__init__
(self, mean, std)
baselines/navdp/depth_anything/depth_anything_v2/util/transform.py:129
Method__init__
(self)
baselines/navdp/depth_anything/depth_anything_v2/util/transform.py:143
Method__init__
(self, drop_prob=None)
baselines/navdp/depth_anything/depth_anything_v2/dinov2_layers/drop_path.py:30
Method__init__
( self, dim: int, num_heads: int, mlp_ratio: float = 4.0, qkv_bias: bo
baselines/navdp/depth_anything/depth_anything_v2/dinov2_layers/block.py:37
Method__init__
( self, dim: int, init_values: Union[float, Tensor] = 1e-5, inplace: bool = Fa
baselines/navdp/depth_anything/depth_anything_v2/dinov2_layers/layer_scale.py:17
Method__init__
( self, dim: int, num_heads: int = 8, qkv_bias: bool = False, proj_bia
baselines/navdp/depth_anything/depth_anything_v2/dinov2_layers/attention.py:30
Method__init__
( self, in_features: int, hidden_features: Optional[int] = None, out_features:
baselines/navdp/depth_anything/depth_anything_v2/dinov2_layers/mlp.py:18
Method__init__
( self, in_features: int, hidden_features: Optional[int] = None, out_features:
baselines/navdp/depth_anything/depth_anything_v2/dinov2_layers/swiglu_ffn.py:46
Method__init__
( self, img_size: Union[int, Tuple[int, int]] = 224, patch_size: Union[int, Tuple[int,
baselines/navdp/depth_anything/depth_anything_v2/dinov2_layers/patch_embed.py:38
Method__init__
(self, filelist_path, mode, size=(518, 518))
baselines/navdp/depth_anything/metric_depth/dataset/kitti.py:10
Method__init__
(self, filelist_path, mode, size=(518, 518))
baselines/navdp/depth_anything/metric_depth/dataset/vkitti2.py:10
Method__init__
Init. Args: width (int): desired output width height (int): desired output height resize_target (bool, op
baselines/navdp/depth_anything/metric_depth/dataset/transform.py:54
Method__init__
(self, mean, std)
baselines/navdp/depth_anything/metric_depth/dataset/transform.py:211
Method__init__
(self)
baselines/navdp/depth_anything/metric_depth/dataset/transform.py:225
Method__init__
(self, size)
baselines/navdp/depth_anything/metric_depth/dataset/transform.py:251
Method__init__
(self, filelist_path, mode, size=(518, 518))
baselines/navdp/depth_anything/metric_depth/dataset/hypersim.py:27
Method__init__
(self, in_feature, out_feature)
baselines/navdp/depth_anything/metric_depth/depth_anything_v2/dpt.py:25
Method__init__
( self, encoder='vitl', features=256, out_channels=[256, 512, 1024, 1024],
baselines/navdp/depth_anything/metric_depth/depth_anything_v2/dpt.py:153
Method__init__
Args: img_size (int, tuple): input image size patch_size (int, tuple): patch size in_chans (int): number
baselines/navdp/depth_anything/metric_depth/depth_anything_v2/dinov2.py:45
Method__init__
Init. Args: features (int): number of features
baselines/navdp/depth_anything/metric_depth/depth_anything_v2/util/blocks.py:87
Method__init__
Init. Args: width (int): desired output width height (int): desired output height resize_target (bool, op
baselines/navdp/depth_anything/metric_depth/depth_anything_v2/util/transform.py:9
Method__init__
(self, mean, std)
baselines/navdp/depth_anything/metric_depth/depth_anything_v2/util/transform.py:129
Method__init__
(self)
baselines/navdp/depth_anything/metric_depth/depth_anything_v2/util/transform.py:143
Method__init__
(self, drop_prob=None)
baselines/navdp/depth_anything/metric_depth/depth_anything_v2/dinov2_layers/drop_path.py:30
Method__init__
( self, dim: int, num_heads: int, mlp_ratio: float = 4.0, qkv_bias: bo
baselines/navdp/depth_anything/metric_depth/depth_anything_v2/dinov2_layers/block.py:37
Method__init__
( self, dim: int, init_values: Union[float, Tensor] = 1e-5, inplace: bool = Fa
baselines/navdp/depth_anything/metric_depth/depth_anything_v2/dinov2_layers/layer_scale.py:17
Method__init__
( self, dim: int, num_heads: int = 8, qkv_bias: bool = False, proj_bia
baselines/navdp/depth_anything/metric_depth/depth_anything_v2/dinov2_layers/attention.py:30
Method__init__
( self, in_features: int, hidden_features: Optional[int] = None, out_features:
baselines/navdp/depth_anything/metric_depth/depth_anything_v2/dinov2_layers/mlp.py:18
Method__init__
( self, in_features: int, hidden_features: Optional[int] = None, out_features:
baselines/navdp/depth_anything/metric_depth/depth_anything_v2/dinov2_layers/swiglu_ffn.py:46
Method__init__
( self, img_size: Union[int, Tuple[int, int]] = 224, patch_size: Union[int, Tuple[int,
baselines/navdp/depth_anything/metric_depth/depth_anything_v2/dinov2_layers/patch_embed.py:38
Method__init__
(self, lambd=0.5)
baselines/navdp/depth_anything/metric_depth/util/loss.py:6
Method__init__
( self, image_intrinsic: torch.Tensor, model_path: str, model_config_path: str
baselines/iplanner/iplanner_agent.py:10
Method__init__
(self)
baselines/iplanner/traj_opt.py:15
Method__init__
(self)
baselines/iplanner/traj_opt.py:39
Method__init__
(self, encoder_channel=64, k=5)
baselines/iplanner/planner_net.py:15
Method__init__
(self, layers, block=BasicBlock, groups=1, width_per_group=64, replace_stride_with_dilation=
baselines/iplanner/percept_net.py:50
Method__init__
(self, history_size=5)
utils_tasks/visualization_utils.py:7
Method__init__
(self, global_planed_traj, N = 15, desired_v = 0.5, v_max = 0.5, w_max = 0.5, ref_gap = 3)
utils_tasks/tracking_utils.py:29
Method__init__
(self, name: str)
wheeled_robots/controllers/base_controller.py:21
Method__init__
( self, name: str, wheel_radius: float, wheel_base: float, max_linear_
wheeled_robots/controllers/differential_controller.py:37
Method__len__
(self)
baselines/logoplanner/depth_anything/metric_depth/dataset/kitti.py:56
Method__len__
(self)
baselines/logoplanner/depth_anything/metric_depth/dataset/vkitti2.py:53
Method__len__
(self)
baselines/logoplanner/depth_anything/metric_depth/dataset/hypersim.py:73
Method__len__
(self)
baselines/navdp/depth_anything/metric_depth/dataset/kitti.py:56
Method__len__
(self)
baselines/navdp/depth_anything/metric_depth/dataset/vkitti2.py:53
Method__len__
(self)
baselines/navdp/depth_anything/metric_depth/dataset/hypersim.py:73
Method__post_init__
(self)
configs/tasks/wheeled_task.py:334
Method__post_init__
(self)
configs/tasks/wheeled_task.py:378
Method__post_init__
(self)
configs/tasks/wheeled_task.py:416
Method__post_init__
(self)
configs/tasks/wheeled_task.py:462
Method__post_init__
(self)
configs/tasks/wheeled_task.py:583
Method__post_init__
(self)
configs/tasks/wheeled_task.py:598
Method__post_init__
(self)
configs/tasks/wheeled_task.py:613
Method__post_init__
(self)
configs/tasks/wheeled_task.py:627
Methodact
(self, *args: Any, **kwargs: Any)
baselines/ddppo/pointnav_network.py:21
Methodall_model_dir
(self)
baselines/viplanner/configs/learning_config.py:211
Functionapply_min_size
Rezise the sample to ensure the given size. Keeps aspect ratio. Args: sample (dict): sample size (tuple): image size Returns
baselines/logoplanner/depth_anything/metric_depth/dataset/transform.py:8
Functionapply_min_size
Rezise the sample to ensure the given size. Keeps aspect ratio. Args: sample (dict): sample size (tuple): image size Returns
baselines/navdp/depth_anything/metric_depth/dataset/transform.py:8
Functionarrival_terminal_check
(env: ManagerBasedEnv, robot_asset_cfg: SceneEntityCfg = SceneEntityCfg("robot"))
configs/tasks/wheeled_task.py:87
Methodattn_residual_func
(x: Tensor)
baselines/logoplanner/depth_anything/depth_anything_v2/dinov2_layers/block.py:83
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