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Functions4,346 in github.com/MrZihan/Dynam3D

↓ 2 callersMethod_initialize_policy
( self, config: Config, load_from_ckpt: bool, observation_space: Space,
Dynam3D_Pretrain/src_3dff/common/base_il_trainer.py:76
↓ 2 callersMethod_localize
(self, qpos, kpos_dict, ignore_height=False)
Dynam3D_VLN/vlnce_baselines/vlnce_baselines/models/graph_utils.py:163
↓ 2 callersMethod_localize
(self, qpos, kpos_dict, ignore_height=False)
Dynam3D_VLN/vlnce_baselines/models/graph_utils.py:163
↓ 2 callersFunction_log_confusion_matrix
Log the confusion matrix to Comet experiment.
Dynam3D_VLN/ultralytics/yolo/utils/callbacks/comet.py:198
↓ 2 callersFunction_log_confusion_matrix
Log the confusion matrix to Comet experiment.
Dynam3D_Pretrain/ultralytics/yolo/utils/callbacks/comet.py:198
↓ 2 callersFunction_log_debug_samples
Log files (images) as debug samples in the ClearML task. Args: files (list): A list of file paths in PosixPath format. title
Dynam3D_VLN/ultralytics/yolo/utils/callbacks/clearml.py:23
↓ 2 callersFunction_log_debug_samples
Log files (images) as debug samples in the ClearML task. Args: files (list): A list of file paths in PosixPath format. title
Dynam3D_Pretrain/ultralytics/yolo/utils/callbacks/clearml.py:23
↓ 2 callersFunction_log_image_predictions
Logs predicted boxes for a single image during training.
Dynam3D_VLN/ultralytics/yolo/utils/callbacks/comet.py:222
↓ 2 callersFunction_log_image_predictions
Logs predicted boxes for a single image during training.
Dynam3D_Pretrain/ultralytics/yolo/utils/callbacks/comet.py:222
↓ 2 callersFunction_log_images
Log scalars to the NeptuneAI experiment logger.
Dynam3D_VLN/ultralytics/yolo/utils/callbacks/neptune.py:28
↓ 2 callersFunction_log_images
Log scalars to the NeptuneAI experiment logger.
Dynam3D_Pretrain/ultralytics/yolo/utils/callbacks/neptune.py:28
↓ 2 callersFunction_log_model
Log the best-trained model to Comet.ml.
Dynam3D_VLN/ultralytics/yolo/utils/callbacks/comet.py:276
↓ 2 callersFunction_log_model
Log the best-trained model to Comet.ml.
Dynam3D_Pretrain/ultralytics/yolo/utils/callbacks/comet.py:276
↓ 2 callersFunction_log_scalars
Logs scalar values to TensorBoard.
Dynam3D_VLN/ultralytics/yolo/utils/callbacks/tensorboard.py:15
↓ 2 callersFunction_log_scalars
Logs scalar values to TensorBoard.
Dynam3D_Pretrain/ultralytics/yolo/utils/callbacks/tensorboard.py:15
↓ 2 callersMethod_new_video
Create a new video capture object.
Dynam3D_VLN/ultralytics/yolo/data/dataloaders/v5loader.py:331
↓ 2 callersMethod_new_video
Create a new video capture object.
Dynam3D_VLN/ultralytics/yolo/data/dataloaders/stream_loaders.py:229
↓ 2 callersMethod_new_video
Create a new video capture object.
Dynam3D_Pretrain/ultralytics/yolo/data/dataloaders/v5loader.py:331
↓ 2 callersMethod_new_video
Create a new video capture object.
Dynam3D_Pretrain/ultralytics/yolo/data/dataloaders/stream_loaders.py:229
↓ 2 callersMethod_pause_envs
(envs, batch, envs_to_pause)
Dynam3D_VLN/vlnce_baselines/ss_trainer_Dynam3D.py:253
↓ 2 callersMethod_pause_envs
(envs, batch, envs_to_pause)
Dynam3D_VLN/vlnce_baselines/vlnce_baselines/ss_trainer_Dynam3D.py:246
↓ 2 callersMethod_pause_envs
( envs_to_pause, envs, recurrent_hidden_states, not_done_masks, prev_a
Dynam3D_VLN/vlnce_baselines/vlnce_baselines/common/base_il_trainer.py:222
↓ 2 callersMethod_pause_envs
( envs_to_pause, envs, recurrent_hidden_states, not_done_masks, prev_a
Dynam3D_VLN/vlnce_baselines/common/base_il_trainer.py:222
↓ 2 callersMethod_pause_envs
( envs_to_pause, envs, recurrent_hidden_states, not_done_masks, prev_a
Dynam3D_Pretrain/src_3dff/common/base_il_trainer.py:221
↓ 2 callersMethod_pe_encoding
Positionally encode points that are normalized to [0,1].
Dynam3D_VLN/ultralytics/vit/sam/modules/encoders.py:284
↓ 2 callersMethod_pe_encoding
Positionally encode points that are normalized to [0,1].
Dynam3D_Pretrain/ultralytics/vit/sam/modules/encoders.py:284
↓ 2 callersMethod_process_batch
( self, points: np.ndarray, im_size: Tuple[int, ...], crop_box: List[int],
Dynam3D_VLN/ultralytics/vit/sam/modules/mask_generator.py:250
↓ 2 callersMethod_process_batch
Return correct prediction matrix Arguments: detections (array[N, 6]), x1, y1, x2, y2, conf, class labels (arr
Dynam3D_VLN/ultralytics/yolo/v8/segment/val.py:131
↓ 2 callersMethod_process_batch
Return correct prediction matrix Arguments: detections (array[N, 6]), x1, y1, x2, y2, conf, class labels (arr
Dynam3D_VLN/ultralytics/yolo/v8/pose/val.py:110
↓ 2 callersMethod_process_batch
( self, points: np.ndarray, im_size: Tuple[int, ...], crop_box: List[int],
Dynam3D_Pretrain/ultralytics/vit/sam/modules/mask_generator.py:250
↓ 2 callersMethod_process_batch
Return correct prediction matrix Arguments: detections (array[N, 6]), x1, y1, x2, y2, conf, class labels (arr
Dynam3D_Pretrain/ultralytics/yolo/v8/segment/val.py:131
↓ 2 callersMethod_process_batch
Return correct prediction matrix Arguments: detections (array[N, 6]), x1, y1, x2, y2, conf, class labels (arr
Dynam3D_Pretrain/ultralytics/yolo/v8/pose/val.py:110
↓ 2 callersMethod_profile_one_layer
Profile the computation time and FLOPs of a single layer of the model on a given input. Appends the results to the provided list.
Dynam3D_VLN/ultralytics/nn/tasks.py:95
↓ 2 callersMethod_profile_one_layer
Profile the computation time and FLOPs of a single layer of the model on a given input. Appends the results to the provided list.
Dynam3D_Pretrain/ultralytics/nn/tasks.py:95
↓ 2 callersMethod_reset_agent_state
(self, state: habitat_sim.AgentState)
Dynam3D_VLN/habitat_extensions/shortest_path_follower.py:105
↓ 2 callersMethod_reset_agent_state
(self, state: habitat_sim.AgentState)
Dynam3D_Pretrain/habitat_extensions/shortest_path_follower.py:105
↓ 2 callersFunction_scale_confidence_score
(score)
Dynam3D_VLN/ultralytics/yolo/utils/callbacks/comet.py:43
↓ 2 callersFunction_scale_confidence_score
(score)
Dynam3D_Pretrain/ultralytics/yolo/utils/callbacks/comet.py:43
↓ 2 callersFunction_should_log_confusion_matrix
()
Dynam3D_VLN/ultralytics/yolo/utils/callbacks/comet.py:48
↓ 2 callersFunction_should_log_confusion_matrix
()
Dynam3D_Pretrain/ultralytics/yolo/utils/callbacks/comet.py:48
↓ 2 callersFunction_should_log_image_predictions
()
Dynam3D_VLN/ultralytics/yolo/utils/callbacks/comet.py:52
↓ 2 callersFunction_should_log_image_predictions
()
Dynam3D_Pretrain/ultralytics/yolo/utils/callbacks/comet.py:52
↓ 2 callersMethod_tie_or_clone_weights
Tie or clone module weights depending of weither we are using TorchScript or not
Dynam3D_VLN/vlnce_baselines/vlnce_baselines/waypoint_pred/transformer/pytorch_transformer/modeling_utils.py:275
↓ 2 callersMethod_tie_or_clone_weights
Tie or clone module weights depending of weither we are using TorchScript or not
Dynam3D_VLN/vlnce_baselines/waypoint_pred/transformer/pytorch_transformer/modeling_utils.py:275
↓ 2 callersMethod_tie_or_clone_weights
Tie or clone module weights depending of weither we are using TorchScript or not
Dynam3D_Pretrain/src_3dff/waypoint_pred/transformer/pytorch_transformer/modeling_utils.py:275
↓ 2 callersFunction_transform
(n_px)
Dynam3D_VLN/vlnce_baselines/vlnce_baselines/models/encoders/clip/clip.py:79
↓ 2 callersFunction_transform
(n_px)
Dynam3D_VLN/vlnce_baselines/models/encoders/clip/clip.py:79
↓ 2 callersFunction_transform
(n_px)
Dynam3D_Pretrain/src_3dff/models/encoders/clip/clip.py:79
↓ 2 callersMethod_update_labels
Update labels.
Dynam3D_VLN/ultralytics/yolo/data/augment.py:239
↓ 2 callersMethod_update_labels
Update labels.
Dynam3D_Pretrain/ultralytics/yolo/data/augment.py:239
↓ 2 callersMethodadd_callback
Add a callback.
Dynam3D_VLN/ultralytics/yolo/engine/model.py:490
↓ 2 callersMethodadd_callback
Add a callback.
Dynam3D_Pretrain/ultralytics/yolo/engine/model.py:490
↓ 2 callersMethodadd_edge
(self, x, y, dis)
Dynam3D_VLN/vlnce_baselines/vlnce_baselines/models/graph_utils.py:86
↓ 2 callersMethodadd_edge
(self, x, y, dis)
Dynam3D_VLN/vlnce_baselines/models/graph_utils.py:86
↓ 2 callersMethodadd_padding
Handle rect and mosaic situation.
Dynam3D_VLN/ultralytics/yolo/utils/instance.py:252
↓ 2 callersMethodadd_padding
Handle rect and mosaic situation.
Dynam3D_Pretrain/ultralytics/yolo/utils/instance.py:252
↓ 2 callersFunctionangle_feature_torch
(headings: torch.Tensor)
Dynam3D_VLN/vlnce_baselines/vlnce_baselines/models/utils.py:49
↓ 2 callersFunctionangle_feature_torch
(headings: torch.Tensor)
Dynam3D_VLN/vlnce_baselines/models/utils.py:49
↓ 2 callersFunctionangle_feature_torch
(headings: torch.Tensor)
Dynam3D_Pretrain/src_3dff/models/utils.py:49
↓ 2 callersFunctionappend_text_to_image
r"""Appends text underneath an image of size (height, width, channels). The returned image has white text on a black background. Uses textwrap to
Dynam3D_Pretrain/habitat_extensions/utils.py:609
↓ 2 callersMethodassign_new_instance_ids
(self, batch_id, num_instances)
Dynam3D_VLN/vlnce_baselines/vlnce_baselines/models/feature_fields.py:448
↓ 2 callersMethodassign_new_instance_ids
(self, batch_id, num_instances)
Dynam3D_VLN/vlnce_baselines/models/feature_fields.py:448
↓ 2 callersMethodassign_new_instance_ids
(self, batch_id, num_instances)
Dynam3D_Pretrain/src_3dff/models/feature_fields.py:798
↓ 2 callersMethodassign_new_patch_ids
(self, batch_id, num_patchs)
Dynam3D_VLN/vlnce_baselines/vlnce_baselines/models/feature_fields.py:433
↓ 2 callersMethodassign_new_patch_ids
(self, batch_id, num_patchs)
Dynam3D_VLN/vlnce_baselines/models/feature_fields.py:433
↓ 2 callersMethodassign_new_patch_ids
(self, batch_id, num_patchs)
Dynam3D_Pretrain/src_3dff/models/feature_fields.py:783
↓ 2 callersMethodassign_new_zone_ids
(self, batch_id, num_zones)
Dynam3D_VLN/vlnce_baselines/vlnce_baselines/models/feature_fields.py:463
↓ 2 callersMethodassign_new_zone_ids
(self, batch_id, num_zones)
Dynam3D_VLN/vlnce_baselines/models/feature_fields.py:463
↓ 2 callersMethodassign_new_zone_ids
(self, batch_id, num_zones)
Dynam3D_Pretrain/src_3dff/models/feature_fields.py:813
↓ 2 callersFunctionattempt_load_weights
Loads an ensemble of models weights=[a,b,c] or a single model weights=[a] or weights=a.
Dynam3D_VLN/ultralytics/nn/tasks.py:536
↓ 2 callersFunctionattempt_load_weights
Loads an ensemble of models weights=[a,b,c] or a single model weights=[a] or weights=a.
Dynam3D_Pretrain/ultralytics/nn/tasks.py:536
↓ 2 callersFunctionautopad
Pad to 'same' shape outputs.
Dynam3D_VLN/ultralytics/nn/modules/conv.py:16
↓ 2 callersFunctionautopad
Pad to 'same' shape outputs.
Dynam3D_Pretrain/ultralytics/nn/modules/conv.py:16
↓ 2 callersFunctionbatched_mask_to_box
Calculates boxes in XYXY format around masks. Return [0,0,0,0] for an empty mask. For input shape C1xC2x...xHxW, the output shape is C1xC2x..
Dynam3D_VLN/ultralytics/vit/sam/amg.py:277
↓ 2 callersFunctionbatched_mask_to_box
Calculates boxes in XYXY format around masks. Return [0,0,0,0] for an empty mask. For input shape C1xC2x...xHxW, the output shape is C1xC2x..
Dynam3D_Pretrain/ultralytics/vit/sam/amg.py:277
↓ 2 callersFunctionbenchmark
Benchmark a YOLO model across different formats for speed and accuracy. Args: model (str | Path | optional): Path to the model file
Dynam3D_VLN/ultralytics/yolo/utils/benchmarks.py:44
↓ 2 callersFunctionbenchmark
Benchmark a YOLO model across different formats for speed and accuracy. Args: model (str | Path | optional): Path to the model file
Dynam3D_Pretrain/ultralytics/yolo/utils/benchmarks.py:44
↓ 2 callersFunctionbox_xyxy_to_xywh
Convert bounding boxes from XYXY format to XYWH format.
Dynam3D_VLN/ultralytics/vit/sam/amg.py:94
↓ 2 callersFunctionbox_xyxy_to_xywh
Convert bounding boxes from XYXY format to XYWH format.
Dynam3D_Pretrain/ultralytics/vit/sam/amg.py:94
↓ 2 callersFunctionbuild_sam
Build a SAM model specified by ckpt.
Dynam3D_VLN/ultralytics/vit/sam/build.py:117
↓ 2 callersFunctionbuild_sam
Build a SAM model specified by ckpt.
Dynam3D_Pretrain/ultralytics/vit/sam/build.py:117
↓ 2 callersFunctionbuild_yolo_dataset
Build YOLO Dataset
Dynam3D_VLN/ultralytics/yolo/data/build.py:72
↓ 2 callersFunctionbuild_yolo_dataset
Build YOLO Dataset
Dynam3D_Pretrain/ultralytics/yolo/data/build.py:72
↓ 2 callersFunctionbytes_to_unicode
Returns list of utf-8 byte and a corresponding list of unicode strings. The reversible bpe codes work on unicode strings. This means you
Dynam3D_VLN/vlnce_baselines/vlnce_baselines/models/encoders/clip/simple_tokenizer.py:16
↓ 2 callersFunctionbytes_to_unicode
Returns list of utf-8 byte and a corresponding list of unicode strings. The reversible bpe codes work on unicode strings. This means you
Dynam3D_VLN/vlnce_baselines/models/encoders/clip/simple_tokenizer.py:16
↓ 2 callersFunctionbytes_to_unicode
Returns list of utf-8 byte and a corresponding list of unicode strings. The reversible bpe codes work on unicode strings. This means you
Dynam3D_Pretrain/src_3dff/models/encoders/clip/simple_tokenizer.py:16
↓ 2 callersFunctioncached_path
Given something that might be a URL (or might be a local path), determine which. If it's a URL, download the file and cache it, and retur
Dynam3D_VLN/vlnce_baselines/vlnce_baselines/waypoint_pred/transformer/pytorch_transformer/file_utils.py:93
↓ 2 callersFunctioncached_path
Given something that might be a URL (or might be a local path), determine which. If it's a URL, download the file and cache it, and retur
Dynam3D_VLN/vlnce_baselines/waypoint_pred/transformer/pytorch_transformer/file_utils.py:93
↓ 2 callersFunctioncached_path
Given something that might be a URL (or might be a local path), determine which. If it's a URL, download the file and cache it, and retur
Dynam3D_Pretrain/src_3dff/waypoint_pred/transformer/pytorch_transformer/file_utils.py:93
↓ 2 callersFunctioncalculate_vp_rel_pos_fts
(a, b, base_heading=0, base_elevation=0, to_clock=False)
Dynam3D_VLN/vlnce_baselines/vlnce_baselines/models/graph_utils.py:21
↓ 2 callersFunctioncalculate_vp_rel_pos_fts
(a, b, base_heading=0, base_elevation=0, to_clock=False)
Dynam3D_VLN/vlnce_baselines/models/graph_utils.py:21
↓ 2 callersFunctioncfg2dict
Convert a configuration object to a dictionary, whether it is a file path, a string, or a SimpleNamespace object. Args: cfg (str | P
Dynam3D_VLN/ultralytics/yolo/cfg/__init__.py:79
↓ 2 callersFunctioncfg2dict
Convert a configuration object to a dictionary, whether it is a file path, a string, or a SimpleNamespace object. Args: cfg (str | P
Dynam3D_Pretrain/ultralytics/yolo/cfg/__init__.py:79
↓ 2 callersFunctioncfg2task
Guess from YAML dictionary.
Dynam3D_VLN/ultralytics/nn/tasks.py:729
↓ 2 callersFunctioncfg2task
Guess from YAML dictionary.
Dynam3D_Pretrain/ultralytics/nn/tasks.py:729
↓ 2 callersFunctioncheck_cls_dataset
Check a classification dataset such as Imagenet. This function takes a `dataset` name as input and returns a dictionary containing informati
Dynam3D_VLN/ultralytics/yolo/data/utils.py:269
↓ 2 callersFunctioncheck_cls_dataset
Check a classification dataset such as Imagenet. This function takes a `dataset` name as input and returns a dictionary containing informati
Dynam3D_Pretrain/ultralytics/yolo/data/utils.py:269
↓ 2 callersMethodcheck_config_paths_exist
(config: Config)
Dynam3D_VLN/habitat_extensions/task.py:58
↓ 2 callersMethodcheck_config_paths_exist
(config: Config)
Dynam3D_Pretrain/habitat_extensions/task.py:59
↓ 2 callersFunctioncheck_font
Find font locally or download to user's configuration directory if it does not already exist. Args: font (str): Path or name of font
Dynam3D_VLN/ultralytics/yolo/utils/checks.py:157
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