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Functions216 in github.com/PINTO0309/gazelle-dinov3

↓ 18 callersMethod__init__
(self, in_features, hidden_features=None, out_features=None, act_layer=nn.GELU, drop=0.)
gazelle/backbone.py:267
↓ 12 callersMethodload_gazelle_state_dict
(self, ckpt_state_dict: Dict, include_backbone=False)
gazelle/model.py:127
↓ 11 callersFunctionget_gazelle_model
(model_name: str, onnx_export: bool=False, finetune_backbone: bool=False, apply_sigmoid: bool=True)
gazelle/model.py:327
↓ 10 callersMethodget_transform
(self, in_size)
gazelle/backbone.py:600
↓ 8 callersMethodget_transform
(self, in_size)
gazelle/backbone.py:1292
↓ 4 callersMethod_find_most_relevant_obj
( self, *, base_objs: List[Box], target_objs: List[Box], )
demo_deimv2_onnx_wholebody34_with_edges.py:660
↓ 4 callersFunction_normalize_state
(state)
scripts/train_vat.py:206
↓ 4 callersFunction_torch_load
(weights_only_flag: bool)
scripts/train_vat.py:198
↓ 4 callersFunctionconfigure_backbone_finetune
Freeze the backbone and selectively re-enable gradients on the last `num_layers` transformer blocks. When `num_layers` is None or <= 0, the e
gazelle/backbone.py:65
↓ 4 callersFunctiondraw_dashed_line
Function to draw a dashed line
demo_deimv2_onnx_wholebody34_with_edges.py:1008
↓ 4 callersMethodget_transform
(self, in_size)
gazelle/backbone.py:147
↓ 4 callersFunctionsmooth_by_conv
Temporal smoothing on labels to match original VideoAttTarget evaluation. Adapted from https://github.com/ejcgt/attention-target-detection/blob/ac
data_prep/preprocess_vat.py:26
↓ 4 callersMethodupdate
(self, boxes: List[Box])
demo_deimv2_onnx_wholebody34_with_edges.py:132
↓ 3 callersFunctiondraw_dashed_rectangle
Function to draw a dashed rectangle
demo_deimv2_onnx_wholebody34_with_edges.py:1024
↓ 3 callersMethodforward_features
(self, x: torch.Tensor, register_hook=False)
gazelle/backbone.py:436
↓ 3 callersFunctionis_package_installed
Checks if the specified package is installed. Parameters ---------- package_name: str Name of the package to be checked. Ret
demo_deimv2_onnx_wholebody34_with_edges.py:993
↓ 3 callersFunctionregister_parameter
(param: nn.Parameter)
gazelle/backbone.py:78
↓ 2 callersMethod__call__
(self, s)
demo_deimv2_onnx_wholebody34_with_edges.py:78
↓ 2 callersMethod_calculate_iou
( self, *, base_obj: Box, target_obj: Box, )
demo_deimv2_onnx_wholebody34_with_edges.py:791
↓ 2 callersFunction_find_transformer_container
Identify the module that hosts transformer blocks for a backbone. Returns the container module together with the ordered list of its blocks.
gazelle/backbone.py:35
↓ 2 callersMethod_freeze_parameters
(self, m: nn.Module)
gazelle/backbone.py:1270
↓ 2 callersMethod_init_weights
(self)
gazelle/backbone.py:242
↓ 2 callersFunction_log_param_summary
(model: GazeLLE, backbone_params)
scripts/train_gazefollow.py:219
↓ 2 callersFunction_log_param_summary
(model: GazeLLE, backbone_params)
scripts/train_vat.py:320
↓ 2 callersFunction_target_layers_for_epoch
(epoch_index: int)
scripts/train_gazefollow.py:330
↓ 2 callersFunction_target_layers_for_epoch
(epoch_index: int)
scripts/train_vat.py:464
↓ 2 callersFunctionapply_rope
Applies RoPE to the input tensor.
gazelle/backbone.py:261
↓ 2 callersFunctionenable_module
(module: Optional[nn.Module])
gazelle/backbone.py:87
↓ 2 callersMethodforward
(self, x: torch.Tensor)
gazelle/backbone.py:275
↓ 2 callersFunctiongazefollow_auc
(heatmap: torch.Tensor, gt_gazex, gt_gazey, height, width)
gazelle/utils.py:147
↓ 2 callersFunctiongazefollow_l2
(heatmap: torch.Tensor, gt_gazex, gt_gazey)
gazelle/utils.py:167
↓ 2 callersFunctionget_backbone_num_blocks
Return the number of transformer blocks available for progressive unfreezing. When no blocks can be identified, returns 0.
gazelle/backbone.py:118
↓ 2 callersMethodget_dimension
(self)
gazelle/backbone.py:24
↓ 2 callersMethodget_gazelle_state_dict
(self, include_backbone=False)
gazelle/model.py:121
↓ 2 callersMethodget_out_size
(self, in_size)
gazelle/backbone.py:28
↓ 2 callersMethodis_ready
(self)
demo_deimv2_onnx_wholebody34_with_edges.py:873
↓ 2 callersFunctionnorm_cdf
(x)
gazelle/backbone.py:310
↓ 2 callersFunctionpositionalencoding2d
:param d_model: dimension of the model :param height: height of the positions :param width: width of the positions :return: d_model*h
gazelle/model.py:303
↓ 2 callersFunctionsave_checkpoint
(path, model, optimizer: torch.optim.Optimizer, scheduler: torch.optim.lr_scheduler.LRScheduler, scaler: torch
scripts/train_gazefollow.py:151
↓ 2 callersFunctionsave_checkpoint
(path, model: GazeLLE, optimizer: torch.optim.Optimizer, epoch, train_global_step, best_inout_ap,
scripts/train_vat.py:254
↓ 2 callersFunctiontrunc_normal_
(tensor: torch.Tensor, mean=0., std=1., a=-2., b=2.)
gazelle/backbone.py:319
↓ 2 callersFunctionvat_auc
(heatmap: torch.Tensor, gt_gazex, gt_gazey)
gazelle/utils.py:186
↓ 2 callersFunctionvat_l2
(heatmap: torch.Tensor, gt_gazex, gt_gazey)
gazelle/utils.py:201
↓ 1 callersMethod__init__
Parameters ---------- runtime: Optional[str] Runtime for DEIMv2. Default: onnx model_path: Optional[str
demo_deimv2_onnx_wholebody34_with_edges.py:383
↓ 1 callersMethod__init__
( self, backbone: DinoV2Backbone | DinoV3Backbone | HGNetv2Backbone, inout=False,
gazelle/model.py:14
↓ 1 callersFunction_collect_rng_state
()
scripts/train_gazefollow.py:60
↓ 1 callersFunction_collect_rng_state
()
scripts/train_vat.py:91
↓ 1 callersFunction_cosine_anneal
(start: float, end: float, step: int, total_steps: int)
scripts/train_gazefollow.py:97
↓ 1 callersFunction_cosine_anneal
(start: float, end: float, step: int, total_steps: int)
scripts/train_vat.py:141
↓ 1 callersMethod_freeze_norm
(self, module: nn.Module)
gazelle/backbone.py:1251
↓ 1 callersMethod_iou
(bbox_a: Tuple[int, int, int, int], bbox_b: Tuple[int, int, int, int])
demo_deimv2_onnx_wholebody34_with_edges.py:110
↓ 1 callersFunction_load_init_checkpoint
(path: str)
scripts/train_vat.py:195
↓ 1 callersFunction_load_teacher_weights
(model: GazeLLE, ckpt_path: Path)
scripts/train_gazefollow.py:129
↓ 1 callersFunction_load_teacher_weights
(model: GazeLLE, ckpt_path: Path)
scripts/train_vat.py:173
↓ 1 callersFunction_move_optimizer_state_to_device
(optimizer: torch.optim.Optimizer, device)
scripts/train_gazefollow.py:89
↓ 1 callersFunction_move_optimizer_state_to_device
(optimizer: torch.optim.Optimizer, device)
scripts/train_vat.py:133
↓ 1 callersMethod_nms
( self, *, target_objs: List[Box], iou_threshold: float, )
demo_deimv2_onnx_wholebody34_with_edges.py:745
↓ 1 callersFunction_no_grad_trunc_normal_
(tensor: torch.Tensor, mean, std, a, b)
gazelle/backbone.py:309
↓ 1 callersMethod_postprocess
_postprocess Parameters ---------- image: np.ndarray Entire image. boxes: np.ndarray float32
demo_deimv2_onnx_wholebody34_with_edges.py:500
↓ 1 callersFunction_prepare_model_state_dict
(model: GazeLLE, include_backbone: bool = True)
scripts/train_gazefollow.py:84
↓ 1 callersFunction_prepare_model_state_dict
(model: GazeLLE, include_backbone: bool = True)
scripts/train_vat.py:115
↓ 1 callersMethod_preprocess
_preprocess Parameters ---------- image: np.ndarray Entire image Returns ------- resized
demo_deimv2_onnx_wholebody34_with_edges.py:476
↓ 1 callersMethod_preprocess
( self, *, image: np.ndarray, swap: Optional[Tuple[int, int, int]] = (2, 0, 1)
demo_deimv2_onnx_wholebody34_with_edges.py:933
↓ 1 callersFunction_reinit_inout_head
(model: GazeLLE)
scripts/train_vat.py:120
↓ 1 callersFunction_resolve_teacher_ckpt
(model_name: str, override: Optional[str])
scripts/train_gazefollow.py:120
↓ 1 callersFunction_resolve_teacher_ckpt
(model_name: str, override: Optional[str])
scripts/train_vat.py:164
↓ 1 callersFunction_restore_rng_state
(state: Dict)
scripts/train_gazefollow.py:71
↓ 1 callersFunction_restore_rng_state
(state: Dict)
scripts/train_vat.py:102
↓ 1 callersFunctiondistance_euclid
2点 (x1, y1), (x2, y2) のユークリッド距離を返す
demo_deimv2_onnx_wholebody34_with_edges.py:1040
↓ 1 callersFunctiondraw_skeleton
与えられた boxes (各クラスIDの関節候補) を基に、EDGESで定義された親子を 「もっとも近い距離のペアから順番に」接合していく。ただし、 classid=0 (人物) のバウンディングボックス内にあるキーポイント同士のみを 接続対象とする。
demo_deimv2_onnx_wholebody34_with_edges.py:1044
↓ 1 callersFunctiondrop_path
(x: torch.Tensor, drop_prob: float = 0., training: bool = False)
gazelle/backbone.py:292
↓ 1 callersMethodforward
(self, input)
gazelle/model.py:59
↓ 1 callersFunctiongazelle_dinov2_vitb14
(onnx_export, apply_sigmoid=True)
gazelle/model.py:540
↓ 1 callersFunctiongazelle_dinov2_vitb14_inout
(onnx_export, apply_sigmoid=True)
gazelle/model.py:558
↓ 1 callersFunctiongazelle_dinov2_vitl14
(onnx_export, apply_sigmoid=True)
gazelle/model.py:549
↓ 1 callersFunctiongazelle_dinov2_vitl14_inout
(onnx_export, apply_sigmoid=True)
gazelle/model.py:567
↓ 1 callersFunctiongazelle_dinov3_vit_tiny
( weights_path: str, interaction_indexes: List[int], finetune: bool, embed_dim: int, num_h
gazelle/model.py:577
↓ 1 callersFunctiongazelle_dinov3_vit_tiny_inout
( weights_path: str, interaction_indexes: List[int], finetune: bool, embed_dim: int, num_h
gazelle/model.py:829
↓ 1 callersFunctiongazelle_dinov3_vit_tinyplus
( weights_path: str, interaction_indexes: List[int], finetune: bool, embed_dim: int, num_h
gazelle/model.py:603
↓ 1 callersFunctiongazelle_dinov3_vit_tinyplus_inout
( weights_path: str, interaction_indexes: List[int], finetune: bool, embed_dim: int, num_h
gazelle/model.py:855
↓ 1 callersFunctiongazelle_dinov3_vitb16
( weights_path: str, interaction_indexes: List[int], finetune: bool, embed_dim: int, num_h
gazelle/model.py:681
↓ 1 callersFunctiongazelle_dinov3_vitb16_inout
( weights_path: str, interaction_indexes: List[int], finetune: bool, embed_dim: int, num_h
gazelle/model.py:933
↓ 1 callersFunctiongazelle_dinov3_vits16
( weights_path: str, interaction_indexes: List[int], finetune: bool, embed_dim: int, num_h
gazelle/model.py:629
↓ 1 callersFunctiongazelle_dinov3_vits16_inout
( weights_path: str, interaction_indexes: List[int], finetune: bool, embed_dim: int, num_h
gazelle/model.py:881
↓ 1 callersFunctiongazelle_dinov3_vits16plus
( weights_path: str, interaction_indexes: List[int], finetune: bool, embed_dim: int, num_h
gazelle/model.py:655
↓ 1 callersFunctiongazelle_dinov3_vits16plus_inout
( weights_path: str, interaction_indexes: List[int], finetune: bool, embed_dim: int, num_h
gazelle/model.py:907
↓ 1 callersFunctiongazelle_hgnetv2_atto
( weights_path: str, use_lab: bool, return_idx: List[int], freeze_stem_only: bool, freeze_
gazelle/model.py:708
↓ 1 callersFunctiongazelle_hgnetv2_atto_inout
( weights_path: str, use_lab: bool, return_idx: List[int], freeze_stem_only: bool, freeze_
gazelle/model.py:960
↓ 1 callersFunctiongazelle_hgnetv2_femto
( weights_path: str, use_lab: bool, return_idx: List[int], freeze_stem_only: bool, freeze_
gazelle/model.py:738
↓ 1 callersFunctiongazelle_hgnetv2_femto_inout
( weights_path: str, use_lab: bool, return_idx: List[int], freeze_stem_only: bool, freeze_
gazelle/model.py:990
↓ 1 callersFunctiongazelle_hgnetv2_n
( weights_path: str, use_lab: bool, return_idx: List[int], freeze_stem_only: bool, freeze_
gazelle/model.py:798
↓ 1 callersFunctiongazelle_hgnetv2_n_inout
( weights_path: str, use_lab: bool, return_idx: List[int], freeze_stem_only: bool, freeze_
gazelle/model.py:1050
↓ 1 callersFunctiongazelle_hgnetv2_pico
( weights_path: str, use_lab: bool, return_idx: List[int], freeze_stem_only: bool, freeze_
gazelle/model.py:768
↓ 1 callersFunctiongazelle_hgnetv2_pico_inout
( weights_path: str, use_lab: bool, return_idx: List[int], freeze_stem_only: bool, freeze_
gazelle/model.py:1020
↓ 1 callersMethodget_activation
get activation
gazelle/backbone.py:682
↓ 1 callersMethodget_input_head_maps
(self, bboxes)
gazelle/model.py:100
↓ 1 callersMethodget_input_head_maps
(self, bboxes: torch.Tensor)
gazelle/model.py:243
↓ 1 callersMethodget_out_size
(self, in_size)
gazelle/backbone.py:143
↓ 1 callersMethodget_out_size
(self, in_size)
gazelle/backbone.py:596
↓ 1 callersMethodinit_weights
(self)
gazelle/backbone.py:413
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