SYMBOL INDEX (422 symbols across 44 files)

FILE: src/generate_coco_from_crowdhuman.py
  function generate_coco_from_crowdhuman (line 15) | def generate_coco_from_crowdhuman(split_name='train_val', split='train_v...

FILE: src/generate_coco_from_mot.py
  function generate_coco_from_mot (line 36) | def generate_coco_from_mot(split_name='train', seqs_names=None,
  function check_coco_from_mot (line 266) | def check_coco_from_mot(coco_dir='data/MOT17/mot17_train_coco', annotati...

FILE: src/run_with_submitit.py
  function get_shared_folder (line 24) | def get_shared_folder() -> Path:
  function get_init_file (line 33) | def get_init_file() -> Path:
  class Trainer (line 42) | class Trainer:
    method __init__ (line 43) | def __init__(self, args: Namespace) -> None:
    method __call__ (line 46) | def __call__(self) -> None:
    method checkpoint (line 53) | def checkpoint(self) -> submitit.helpers.DelayedSubmission:
    method _setup_gpu_args (line 69) | def _setup_gpu_args(self) -> None:
  function main (line 83) | def main(args: Namespace):
  function load_config (line 131) | def load_config(_config, _run):

FILE: src/track.py
  function main (line 30) | def main(seed, dataset_name, obj_detect_checkpoint_file, tracker_cfg,

FILE: src/trackformer/datasets/__init__.py
  function get_coco_api_from_dataset (line 15) | def get_coco_api_from_dataset(dataset: Subset) -> COCO:
  function build_dataset (line 29) | def build_dataset(split: str, args: Namespace) -> Dataset:

FILE: src/trackformer/datasets/coco.py
  class CocoDetection (line 21) | class CocoDetection(torchvision.datasets.CocoDetection):
    method __init__ (line 25) | def __init__(self,  img_folder, ann_file, transforms, norm_transforms,
    method _getitem_from_id (line 48) | def _getitem_from_id(self, image_id, random_state=None, random_jitter=...
    method _add_random_jitter (line 89) | def _add_random_jitter(self, img, target):
    method __getitem__ (line 146) | def __getitem__(self, idx):
    method write_result_files (line 166) | def write_result_files(self, *args):
  function convert_coco_poly_to_mask (line 170) | def convert_coco_poly_to_mask(segmentations, height, width):
  class ConvertCocoPolysToMask (line 191) | class ConvertCocoPolysToMask(object):
    method __init__ (line 192) | def __init__(self, return_masks=False, overflow_boxes=False):
    method __call__ (line 196) | def __call__(self, image, target):
  function make_coco_transforms (line 270) | def make_coco_transforms(image_set, img_transform=None, overflow_boxes=F...
  function build (line 315) | def build(image_set, args, mode='instances'):

FILE: src/trackformer/datasets/coco_eval.py
  class CocoEvaluator (line 22) | class CocoEvaluator(object):
    method __init__ (line 23) | def __init__(self, coco_gt, iou_types):
    method update (line 36) | def update(self, predictions):
    method synchronize_between_processes (line 58) | def synchronize_between_processes(self):
    method accumulate (line 66) | def accumulate(self):
    method summarize (line 70) | def summarize(self):
    method prepare (line 75) | def prepare(self, predictions, iou_type):
    method prepare_for_coco_detection (line 85) | def prepare_for_coco_detection(self, predictions):
    method prepare_for_coco_segmentation (line 109) | def prepare_for_coco_segmentation(self, predictions):
    method prepare_for_coco_keypoint (line 144) | def prepare_for_coco_keypoint(self, predictions):
  function convert_to_xywh (line 171) | def convert_to_xywh(boxes):
  function merge (line 176) | def merge(img_ids, eval_imgs):
  function create_common_coco_eval (line 198) | def create_common_coco_eval(coco_eval, img_ids, eval_imgs):
  function evaluate (line 214) | def evaluate(self):

FILE: src/trackformer/datasets/coco_panoptic.py
  class CocoPanoptic (line 15) | class CocoPanoptic:
    method __init__ (line 16) | def __init__(self, img_folder, ann_folder, ann_file, transforms=None, ...
    method __getitem__ (line 35) | def __getitem__(self, idx):
    method __len__ (line 73) | def __len__(self):
    method get_height_and_width (line 76) | def get_height_and_width(self, idx):
  function build (line 83) | def build(image_set, args):

FILE: src/trackformer/datasets/crowdhuman.py
  function build_crowdhuman (line 10) | def build_crowdhuman(image_set, args):

FILE: src/trackformer/datasets/mot.py
  class MOT (line 20) | class MOT(CocoDetection):
    method __init__ (line 22) | def __init__(self, *args, prev_frame_range=1, **kwargs):
    method sequences (line 28) | def sequences(self):
    method frame_range (line 32) | def frame_range(self):
    method seq_length (line 38) | def seq_length(self, idx):
    method sample_weight (line 41) | def sample_weight(self, idx):
    method __getitem__ (line 44) | def __getitem__(self, idx):
    method write_result_files (line 76) | def write_result_files(self, results, output_dir):
  class WeightedConcatDataset (line 114) | class WeightedConcatDataset(torch.utils.data.ConcatDataset):
    method sample_weight (line 116) | def sample_weight(self, idx):
  function build_mot (line 129) | def build_mot(image_set, args):
  function build_mot_crowdhuman (line 165) | def build_mot_crowdhuman(image_set, args):
  function build_mot_coco_person (line 184) | def build_mot_coco_person(image_set, args):

FILE: src/trackformer/datasets/panoptic_eval.py
  class PanopticEvaluator (line 13) | class PanopticEvaluator(object):
    method __init__ (line 14) | def __init__(self, ann_file, ann_folder, output_dir="panoptic_eval"):
    method update (line 23) | def update(self, predictions):
    method synchronize_between_processes (line 30) | def synchronize_between_processes(self):
    method summarize (line 37) | def summarize(self):

FILE: src/trackformer/datasets/tracking/demo_sequence.py
  class DemoSequence (line 22) | class DemoSequence(Dataset):
    method __init__ (line 26) | def __init__(self, root_dir: str = 'data', img_transform: Namespace = ...
    method __len__ (line 43) | def __len__(self) -> int:
    method __str__ (line 46) | def __str__(self) -> str:
    method __getitem__ (line 49) | def __getitem__(self, idx: int) -> dict:
    method _sequence (line 67) | def _sequence(self) -> List[dict]:
    method load_results (line 76) | def load_results(self, results_dir: str) -> dict:
    method write_results (line 79) | def write_results(self, results: dict, output_dir: str) -> None:

FILE: src/trackformer/datasets/tracking/factory.py
  class TrackDatasetFactory (line 40) | class TrackDatasetFactory:
    method __init__ (line 47) | def __init__(self, datasets: Union[str, list], **kwargs) -> None:
    method __len__ (line 66) | def __len__(self) -> int:
    method __getitem__ (line 69) | def __getitem__(self, idx: int):

FILE: src/trackformer/datasets/tracking/mot17_sequence.py
  class MOT17Sequence (line 21) | class MOT17Sequence(Dataset):
    method __init__ (line 29) | def __init__(self, root_dir: str = 'data', seq_name: Optional[str] = N...
    method __len__ (line 62) | def __len__(self) -> int:
    method __getitem__ (line 65) | def __getitem__(self, idx: int) -> dict:
    method _sequence (line 85) | def _sequence(self) -> List[dict]:
    method get_track_boxes_and_visbility (line 119) | def get_track_boxes_and_visbility(self) -> Tuple[dict, dict]:
    method get_seq_path (line 153) | def get_seq_path(self) -> str:
    method get_config_file_path (line 164) | def get_config_file_path(self) -> str:
    method get_gt_file_path (line 168) | def get_gt_file_path(self) -> str:
    method get_det_file_path (line 172) | def get_det_file_path(self) -> str:
    method config (line 180) | def config(self) -> dict:
    method seq_length (line 192) | def seq_length(self) -> int:
    method __str__ (line 196) | def __str__(self) -> str:
    method results_file_name (line 200) | def results_file_name(self) -> str:
    method write_results (line 209) | def write_results(self, results: dict, output_dir: str) -> None:
    method load_results (line 244) | def load_results(self, results_dir: str) -> dict:

FILE: src/trackformer/datasets/tracking/mot20_sequence.py
  class MOT20Sequence (line 9) | class MOT20Sequence(MOT17Sequence):

FILE: src/trackformer/datasets/tracking/mot_wrapper.py
  class MOT17Wrapper (line 12) | class MOT17Wrapper(Dataset):
    method __init__ (line 15) | def __init__(self, split: str, dets: str, **kwargs) -> None:
    method __len__ (line 50) | def __len__(self) -> int:
    method __getitem__ (line 53) | def __getitem__(self, idx: int):
  class MOT20Wrapper (line 57) | class MOT20Wrapper(Dataset):
    method __init__ (line 60) | def __init__(self, split: str, **kwargs) -> None:
    method __len__ (line 86) | def __len__(self) -> int:
    method __getitem__ (line 89) | def __getitem__(self, idx: int):
  class MOTS20Wrapper (line 93) | class MOTS20Wrapper(MOT17Wrapper):
    method __init__ (line 96) | def __init__(self, split: str, **kwargs) -> None:

FILE: src/trackformer/datasets/tracking/mots20_sequence.py
  class MOTS20Sequence (line 17) | class MOTS20Sequence(MOT17Sequence):
    method __init__ (line 25) | def __init__(self, root_dir: str = 'data', seq_name: Optional[str] = N...
    method get_track_boxes_and_visbility (line 35) | def get_track_boxes_and_visbility(self) -> Tuple[dict, dict]:
    method write_results (line 72) | def write_results(self, results: dict, output_dir: str) -> None:
    method load_results (line 93) | def load_results(self, results_dir: str) -> dict:
    method __str__ (line 136) | def __str__(self) -> str:
  class SegmentedObject (line 140) | class SegmentedObject:
    method __init__ (line 144) | def __init__(self, mask: dict, class_id: int, track_id: int) -> None:
  function load_mots_gt (line 150) | def load_mots_gt(path: str) -> dict:

FILE: src/trackformer/datasets/transforms.py
  function crop (line 17) | def crop(image, target, region, overflow_boxes=False):
  function hflip (line 85) | def hflip(image, target):
  function resize (line 115) | def resize(image, target, size, max_size=None):
  function pad (line 175) | def pad(image, target, padding):
  class RandomCrop (line 198) | class RandomCrop:
    method __init__ (line 199) | def __init__(self, size, overflow_boxes=False):
    method __call__ (line 204) | def __call__(self, img, target):
  class RandomSizeCrop (line 209) | class RandomSizeCrop:
    method __init__ (line 210) | def __init__(self,
    method __call__ (line 223) | def __call__(self, img: PIL.Image.Image, target: dict):
  class CenterCrop (line 239) | class CenterCrop:
    method __init__ (line 240) | def __init__(self, size, overflow_boxes=False):
    method __call__ (line 244) | def __call__(self, img, target):
  class RandomHorizontalFlip (line 252) | class RandomHorizontalFlip:
    method __init__ (line 253) | def __init__(self, p=0.5):
    method __call__ (line 256) | def __call__(self, img, target):
  class RepeatUntilMaxObjects (line 262) | class RepeatUntilMaxObjects:
    method __init__ (line 263) | def __init__(self, transforms, num_max_objects):
    method __call__ (line 267) | def __call__(self, img, target):
  class RandomResize (line 275) | class RandomResize:
    method __init__ (line 276) | def __init__(self, sizes, max_size=None):
    method __call__ (line 281) | def __call__(self, img, target=None):
  class RandomResizeTargets (line 286) | class RandomResizeTargets:
    method __init__ (line 287) | def __init__(self, scale=0.5):
    method __call__ (line 290) | def __call__(self, img, target=None):
  class RandomPad (line 343) | class RandomPad:
    method __init__ (line 344) | def __init__(self, max_size):
    method __call__ (line 350) | def __call__(self, img, target):
  class RandomSelect (line 365) | class RandomSelect:
    method __init__ (line 370) | def __init__(self, transforms1, transforms2, p=0.5):
    method __call__ (line 375) | def __call__(self, img, target):
  class ToTensor (line 381) | class ToTensor:
    method __call__ (line 382) | def __call__(self, img, target=None):
  class RandomErasing (line 386) | class RandomErasing:
    method __init__ (line 388) | def __init__(self, p=0.5, scale=(0.02, 0.33), ratio=(0.3, 3.3), value=...
    method __call__ (line 396) | def __call__(self, img, target):
  class Normalize (line 457) | class Normalize:
    method __init__ (line 458) | def __init__(self, mean, std):
    method __call__ (line 462) | def __call__(self, image, target=None):
  class Compose (line 476) | class Compose:
    method __init__ (line 477) | def __init__(self, transforms):
    method __call__ (line 480) | def __call__(self, image, target=None):
    method __repr__ (line 485) | def __repr__(self):

FILE: src/trackformer/engine.py
  function make_results (line 24) | def make_results(outputs, targets, postprocessors, tracking, return_only...
  function train_one_epoch (line 101) | def train_one_epoch(model: torch.nn.Module, criterion: torch.nn.Module, ...
  function evaluate (line 179) | def evaluate(model, criterion, postprocessors, data_loader, device,

FILE: src/trackformer/models/__init__.py
  function build_model (line 16) | def build_model(args):

FILE: src/trackformer/models/backbone.py
  class FrozenBatchNorm2d (line 19) | class FrozenBatchNorm2d(torch.nn.Module):
    method __init__ (line 28) | def __init__(self, n):
    method _load_from_state_dict (line 35) | def _load_from_state_dict(self, state_dict, prefix, local_metadata, st...
    method forward (line 45) | def forward(self, x):
  class BackboneBase (line 58) | class BackboneBase(nn.Module):
    method __init__ (line 60) | def __init__(self, backbone: nn.Module, train_backbone: bool,
    method forward (line 80) | def forward(self, tensor_list: NestedTensor):
  class Backbone (line 91) | class Backbone(BackboneBase):
    method __init__ (line 93) | def __init__(self, name: str,
  class Joiner (line 107) | class Joiner(nn.Sequential):
    method __init__ (line 108) | def __init__(self, backbone, position_embedding):
    method forward (line 113) | def forward(self, tensor_list: NestedTensor):
  function build_backbone (line 125) | def build_backbone(args):

FILE: src/trackformer/models/deformable_detr.py
  function _get_clones (line 25) | def _get_clones(module, N):
  class DeformableDETR (line 29) | class DeformableDETR(DETR):
    method __init__ (line 31) | def __init__(self, backbone, transformer, num_classes, num_queries, nu...
    method forward (line 124) | def forward(self, samples: NestedTensor, targets: list = None, prev_fe...
    method _set_aux_loss (line 278) | def _set_aux_loss(self, outputs_class, outputs_coord):
  class DeformablePostProcess (line 286) | class DeformablePostProcess(PostProcess):
    method forward (line 290) | def forward(self, outputs, target_sizes, results_mask=None):

FILE: src/trackformer/models/deformable_transformer.py
  class DeformableTransformer (line 21) | class DeformableTransformer(nn.Module):
    method __init__ (line 22) | def __init__(self, d_model=256, nhead=8,
    method _reset_parameters (line 65) | def _reset_parameters(self):
    method get_proposal_pos_embed (line 77) | def get_proposal_pos_embed(self, proposals):
    method gen_encoder_output_proposals (line 92) | def gen_encoder_output_proposals(self, memory, memory_padding_mask, sp...
    method get_valid_ratio (line 124) | def get_valid_ratio(self, mask):
    method forward (line 133) | def forward(self, srcs, masks, pos_embeds, query_embed=None, targets=N...
  class DeformableTransformerEncoderLayer (line 258) | class DeformableTransformerEncoderLayer(nn.Module):
    method __init__ (line 259) | def __init__(self,
    method with_pos_embed (line 279) | def with_pos_embed(tensor, pos):
    method forward_ffn (line 282) | def forward_ffn(self, src):
    method forward (line 288) | def forward(self, src, pos, reference_points, spatial_shapes, padding_...
  class DeformableTransformerEncoder (line 300) | class DeformableTransformerEncoder(nn.Module):
    method __init__ (line 301) | def __init__(self, encoder_layer, num_layers):
    method get_reference_points (line 307) | def get_reference_points(spatial_shapes, valid_ratios, device):
    method forward (line 321) | def forward(self, src, spatial_shapes, valid_ratios, pos=None, padding...
  class DeformableTransformerDecoderLayer (line 330) | class DeformableTransformerDecoderLayer(nn.Module):
    method __init__ (line 331) | def __init__(self, d_model=256, d_ffn=1024,
    method with_pos_embed (line 355) | def with_pos_embed(tensor, pos):
    method forward_ffn (line 358) | def forward_ffn(self, tgt):
    method forward (line 364) | def forward(self, tgt, query_pos, reference_points, src, src_spatial_s...
  class DeformableTransformerDecoder (line 386) | class DeformableTransformerDecoder(nn.Module):
    method __init__ (line 387) | def __init__(self, decoder_layer, num_layers, return_intermediate=False):
    method forward (line 396) | def forward(self, tgt, reference_points, src, src_spatial_shapes, src_...
  function build_deforamble_transformer (line 434) | def build_deforamble_transformer(args):

FILE: src/trackformer/models/detr.py
  class DETR (line 17) | class DETR(nn.Module):
    method __init__ (line 20) | def __init__(self, backbone, transformer, num_classes, num_queries,
    method hidden_dim (line 52) | def hidden_dim(self):
    method fpn_channels (line 57) | def fpn_channels(self):
    method forward (line 62) | def forward(self, samples: NestedTensor, targets: list = None):
    method _set_aux_loss (line 131) | def _set_aux_loss(self, outputs_class, outputs_coord):
  class SetCriterion (line 139) | class SetCriterion(nn.Module):
    method __init__ (line 145) | def __init__(self, num_classes, matcher, weight_dict, eos_coef, losses,
    method loss_labels (line 172) | def loss_labels(self, outputs, targets, indices, _, log=True):
    method loss_labels_focal (line 213) | def loss_labels_focal(self, outputs, targets, indices, num_boxes, log=...
    method loss_cardinality (line 276) | def loss_cardinality(self, outputs, targets, indices, num_boxes):
    method loss_boxes (line 290) | def loss_boxes(self, outputs, targets, indices, num_boxes):
    method loss_masks (line 330) | def loss_masks(self, outputs, targets, indices, num_boxes):
    method _get_src_permutation_idx (line 360) | def _get_src_permutation_idx(self, indices):
    method _get_tgt_permutation_idx (line 366) | def _get_tgt_permutation_idx(self, indices):
    method get_loss (line 372) | def get_loss(self, loss, outputs, targets, indices, num_boxes, **kwargs):
    method forward (line 382) | def forward(self, outputs, targets):
  class PostProcess (line 446) | class PostProcess(nn.Module):
    method process_boxes (line 449) | def process_boxes(self, boxes, target_sizes):
    method forward (line 460) | def forward(self, outputs, target_sizes, results_mask=None):
  class MLP (line 493) | class MLP(nn.Module):
    method __init__ (line 496) | def __init__(self, input_dim, hidden_dim, output_dim, num_layers):
    method forward (line 504) | def forward(self, x):

FILE: src/trackformer/models/detr_segmentation.py
  class DETRSegmBase (line 29) | class DETRSegmBase(nn.Module):
    method __init__ (line 30) | def __init__(self, freeze_detr=False):
    method forward (line 41) | def forward(self, samples: NestedTensor, targets: list = None):
  class DETRSegm (line 75) | class DETRSegm(DETRSegmBase, DETR):
    method __init__ (line 76) | def __init__(self, mask_kwargs, detr_kwargs):
  class DeformableDETRSegm (line 81) | class DeformableDETRSegm(DETRSegmBase, DeformableDETR):
    method __init__ (line 82) | def __init__(self, mask_kwargs, detr_kwargs):
  class DETRSegmTracking (line 87) | class DETRSegmTracking(DETRSegmBase, DETRTrackingBase, DETR):
    method __init__ (line 88) | def __init__(self, mask_kwargs, tracking_kwargs, detr_kwargs):
  class DeformableDETRSegmTracking (line 94) | class DeformableDETRSegmTracking(DETRSegmBase, DETRTrackingBase, Deforma...
    method __init__ (line 95) | def __init__(self, mask_kwargs, tracking_kwargs, detr_kwargs):
  function _expand (line 101) | def _expand(tensor, length: int):
  class MaskHeadSmallConv (line 105) | class MaskHeadSmallConv(nn.Module):
    method __init__ (line 111) | def __init__(self, dim, fpn_dims, context_dim):
    method forward (line 143) | def forward(self, x: Tensor, bbox_mask: Tensor, fpns: List[Tensor]):
  class MHAttentionMap (line 181) | class MHAttentionMap(nn.Module):
    method __init__ (line 185) | def __init__(self, query_dim, hidden_dim, num_heads, dropout=0.0, bias...
    method forward (line 200) | def forward(self, q, k, mask: Optional[Tensor] = None):
  class PostProcessSegm (line 219) | class PostProcessSegm(nn.Module):
    method __init__ (line 220) | def __init__(self, threshold=0.5):
    method forward (line 225) | def forward(self, results, outputs, orig_target_sizes, max_target_size...
  class PostProcessPanoptic (line 256) | class PostProcessPanoptic(nn.Module):
    method __init__ (line 260) | def __init__(self, is_thing_map, threshold=0.85):
    method forward (line 273) | def forward(self, outputs, processed_sizes, target_sizes=None):

FILE: src/trackformer/models/detr_tracking.py
  class DETRTrackingBase (line 15) | class DETRTrackingBase(nn.Module):
    method __init__ (line 17) | def __init__(self,
    method train (line 29) | def train(self, mode: bool = True):
    method tracking (line 34) | def tracking(self):
    method add_track_queries_to_targets (line 39) | def add_track_queries_to_targets(self, targets, prev_indices, prev_out...
    method forward (line 219) | def forward(self, samples: NestedTensor, targets: list = None, prev_fe...
  class DETRTracking (line 281) | class DETRTracking(DETRTrackingBase, DETR):
    method __init__ (line 282) | def __init__(self, tracking_kwargs, detr_kwargs):
  class DeformableDETRTracking (line 287) | class DeformableDETRTracking(DETRTrackingBase, DeformableDETR):
    method __init__ (line 288) | def __init__(self, tracking_kwargs, detr_kwargs):

FILE: src/trackformer/models/matcher.py
  class HungarianMatcher (line 13) | class HungarianMatcher(nn.Module):
    method __init__ (line 21) | def __init__(self, cost_class: float = 1, cost_bbox: float = 1, cost_g...
    method forward (line 42) | def forward(self, outputs, targets):
  function build_matcher (line 134) | def build_matcher(args):

FILE: src/trackformer/models/ops/functions/ms_deform_attn_func.py
  class MSDeformAttnFunction (line 14) | class MSDeformAttnFunction(Function):
    method forward (line 16) | def forward(ctx, value, value_spatial_shapes, sampling_locations, atte...
    method backward (line 25) | def backward(ctx, grad_output):
  function ms_deform_attn_core_pytorch (line 34) | def ms_deform_attn_core_pytorch(value, value_spatial_shapes, sampling_lo...
  function ms_deform_attn_core_pytorch_mot (line 56) | def ms_deform_attn_core_pytorch_mot(query, value, value_spatial_shapes, ...

FILE: src/trackformer/models/ops/modules/ms_deform_attn.py
  class MSDeformAttn (line 15) | class MSDeformAttn(nn.Module):
    method __init__ (line 16) | def __init__(self, d_model=256, n_levels=4, n_heads=8, n_points=4, im2...
    method _reset_parameters (line 34) | def _reset_parameters(self):
    method forward (line 49) | def forward(self, query, reference_points, input_flatten, input_spatia...

FILE: src/trackformer/models/ops/setup.py
  function get_extensions (line 17) | def get_extensions():

FILE: src/trackformer/models/ops/src/cpu/ms_deform_attn_cpu.cpp
  function ms_deform_attn_cpu_forward (line 7) | at::Tensor
  function ms_deform_attn_cpu_backward (line 18) | std::vector<at::Tensor>

FILE: src/trackformer/models/ops/src/ms_deform_attn.h
  function im2col_step (line 16) | int im2col_step)

FILE: src/trackformer/models/ops/src/vision.cpp
  function PYBIND11_MODULE (line 4) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: src/trackformer/models/ops/test.py
  function check_forward_equal_with_pytorch (line 23) | def check_forward_equal_with_pytorch():
  function check_backward_equal_with_pytorch (line 38) | def check_backward_equal_with_pytorch():
  function check_gradient_ms_deform_attn (line 98) | def check_gradient_ms_deform_attn(

FILE: src/trackformer/models/ops/test_double_precision.py
  function check_forward_equal_with_pytorch (line 22) | def check_forward_equal_with_pytorch():
  function check_backward_equal_with_pytorch (line 37) | def check_backward_equal_with_pytorch():
  function check_gradient_ms_deform_attn (line 97) | def check_gradient_ms_deform_attn(

FILE: src/trackformer/models/position_encoding.py
  class PositionEmbeddingSine3D (line 12) | class PositionEmbeddingSine3D(nn.Module):
    method __init__ (line 18) | def __init__(self, num_pos_feats=64, num_frames=2, temperature=10000, ...
    method forward (line 31) | def forward(self, tensor_list: NestedTensor):
  class PositionEmbeddingSine (line 84) | class PositionEmbeddingSine(nn.Module):
    method __init__ (line 89) | def __init__(self, num_pos_feats=64, temperature=10000, normalize=Fals...
    method forward (line 100) | def forward(self, tensor_list: NestedTensor):
  class PositionEmbeddingLearned (line 123) | class PositionEmbeddingLearned(nn.Module):
    method __init__ (line 127) | def __init__(self, num_pos_feats=256):
    method reset_parameters (line 133) | def reset_parameters(self):
    method forward (line 137) | def forward(self, tensor_list: NestedTensor):
  function build_position_encoding (line 151) | def build_position_encoding(args):

FILE: src/trackformer/models/tracker.py
  class Tracker (line 16) | class Tracker:
    method __init__ (line 19) | def __init__(self, obj_detector, obj_detector_post, tracker_cfg,
    method num_object_queries (line 68) | def num_object_queries(self):
    method reset (line 71) | def reset(self, hard=True):
    method device (line 83) | def device(self):
    method tracks_to_inactive (line 86) | def tracks_to_inactive(self, tracks):
    method add_tracks (line 93) | def add_tracks(self, pos, scores, hs_embeds, indices, masks=None, atte...
    method public_detections_mask (line 124) | def public_detections_mask(self, new_det_boxes, public_det_boxes):
    method reid (line 167) | def reid(self, new_det_boxes, new_det_scores, new_det_hs_embeds,
    method step (line 266) | def step(self, blob):
    method get_results (line 552) | def get_results(self):
  class Track (line 557) | class Track(object):
    method __init__ (line 560) | def __init__(self, pos, score, track_id, hs_embed, obj_ind,
    method has_positive_area (line 575) | def has_positive_area(self) -> bool:
    method reset_last_pos (line 580) | def reset_last_pos(self) -> None:

FILE: src/trackformer/models/transformer.py
  class Transformer (line 18) | class Transformer(nn.Module):
    method __init__ (line 20) | def __init__(self, d_model=512, nhead=8, num_encoder_layers=6,
    method _reset_parameters (line 45) | def _reset_parameters(self):
    method forward (line 50) | def forward(self, src, mask, query_embed, pos_embed, tgt=None, prev_fr...
  class TransformerEncoder (line 83) | class TransformerEncoder(nn.Module):
    method __init__ (line 85) | def __init__(self, encoder_layer, num_layers, norm=None):
    method forward (line 91) | def forward(self, src,
  class TransformerDecoder (line 107) | class TransformerDecoder(nn.Module):
    method __init__ (line 109) | def __init__(self, decoder_layer, encoder_layer, num_layers,
    method forward (line 122) | def forward(self, tgt, memory,
  class TransformerEncoderLayer (line 166) | class TransformerEncoderLayer(nn.Module):
    method __init__ (line 168) | def __init__(self, d_model, nhead, dim_feedforward=2048, dropout=0.1,
    method with_pos_embed (line 185) | def with_pos_embed(self, tensor, pos: Optional[Tensor]):
    method forward_post (line 188) | def forward_post(self,
    method forward_pre (line 203) | def forward_pre(self, src,
    method forward (line 217) | def forward(self, src,
  class TransformerDecoderLayer (line 226) | class TransformerDecoderLayer(nn.Module):
    method __init__ (line 228) | def __init__(self, d_model, nhead, dim_feedforward=2048, dropout=0.1,
    method with_pos_embed (line 248) | def with_pos_embed(self, tensor, pos: Optional[Tensor]):
    method forward_post (line 251) | def forward_post(self, tgt, memory,
    method forward_pre (line 274) | def forward_pre(self, tgt, memory,
    method forward (line 297) | def forward(self, tgt, memory,
  function _get_clones (line 311) | def _get_clones(module, N):
  function _get_activation_fn (line 315) | def _get_activation_fn(activation):
  function build_transformer (line 326) | def build_transformer(args):

FILE: src/trackformer/util/box_ops.py
  function box_cxcywh_to_xyxy (line 9) | def box_cxcywh_to_xyxy(x):
  function box_xyxy_to_cxcywh (line 16) | def box_xyxy_to_cxcywh(x):
  function box_iou (line 24) | def box_iou(boxes1, boxes2):
  function generalized_box_iou (line 40) | def generalized_box_iou(boxes1, boxes2):
  function masks_to_boxes (line 64) | def masks_to_boxes(masks):

FILE: src/trackformer/util/misc.py
  class SmoothedValue (line 29) | class SmoothedValue(object):
    method __init__ (line 34) | def __init__(self, window_size=20, fmt=None):
    method update (line 42) | def update(self, value, n=1):
    method synchronize_between_processes (line 47) | def synchronize_between_processes(self):
    method median (line 61) | def median(self):
    method avg (line 66) | def avg(self):
    method global_avg (line 71) | def global_avg(self):
    method max (line 75) | def max(self):
    method value (line 79) | def value(self):
    method __str__ (line 82) | def __str__(self):
  function all_gather (line 91) | def all_gather(data):
  function reduce_dict (line 135) | def reduce_dict(input_dict, average=True):
  class MetricLogger (line 162) | class MetricLogger(object):
    method __init__ (line 163) | def __init__(self, print_freq, delimiter="\t", vis=None, debug=False):
    method update (line 170) | def update(self, **kwargs):
    method __getattr__ (line 177) | def __getattr__(self, attr):
    method __str__ (line 185) | def __str__(self):
    method synchronize_between_processes (line 191) | def synchronize_between_processes(self):
    method add_meter (line 195) | def add_meter(self, name, meter):
    method log_every (line 198) | def log_every(self, iterable, epoch=None, header=None):
  function get_sha (line 274) | def get_sha():
  function collate_fn (line 294) | def collate_fn(batch):
  function _max_by_axis (line 300) | def _max_by_axis(the_list):
  function nested_tensor_from_tensor_list (line 309) | def nested_tensor_from_tensor_list(tensor_list: List[Tensor]):
  class NestedTensor (line 329) | class NestedTensor(object):
    method __init__ (line 330) | def __init__(self, tensors, mask: Optional[Tensor] = None):
    method to (line 334) | def to(self, device):
    method decompose (line 345) | def decompose(self):
    method __repr__ (line 348) | def __repr__(self):
    method unmasked_tensor (line 351) | def unmasked_tensor(self, index: int):
  function setup_for_distributed (line 368) | def setup_for_distributed(is_master):
  function is_dist_avail_and_initialized (line 392) | def is_dist_avail_and_initialized():
  function get_world_size (line 400) | def get_world_size():
  function get_rank (line 406) | def get_rank():
  function is_main_process (line 412) | def is_main_process():
  function save_on_master (line 416) | def save_on_master(*args, **kwargs):
  function init_distributed_mode (line 421) | def init_distributed_mode(args):
  function accuracy (line 448) | def accuracy(output, target, topk=(1,)):
  function interpolate (line 466) | def interpolate(input, size=None, scale_factor=None, mode="nearest", ali...
  class DistributedWeightedSampler (line 486) | class DistributedWeightedSampler(torch.utils.data.DistributedSampler):
    method __init__ (line 487) | def __init__(self, dataset, num_replicas=None, rank=None, shuffle=True...
    method __iter__ (line 494) | def __iter__(self):
    method __len__ (line 511) | def __len__(self):
  function inverse_sigmoid (line 515) | def inverse_sigmoid(x, eps=1e-5):
  function dice_loss (line 522) | def dice_loss(inputs, targets, num_boxes):
  function sigmoid_focal_loss (line 540) | def sigmoid_focal_loss(inputs, targets, num_boxes, alpha: float = 0.25, ...
  function nested_dict_to_namespace (line 574) | def nested_dict_to_namespace(dictionary):
  function nested_dict_to_device (line 582) | def nested_dict_to_device(dictionary, device):

FILE: src/trackformer/util/plot_utils.py
  function fig_to_numpy (line 14) | def fig_to_numpy(fig):
  function get_vis_win_names (line 24) | def get_vis_win_names(vis_dict):
  function plot_logs (line 35) | def plot_logs(logs, fields=('class_error', 'loss_bbox_unscaled', 'mAP'),...
  function plot_precision_recall (line 91) | def plot_precision_recall(files, naming_scheme='iter'):

FILE: src/trackformer/util/track_utils.py
  function bbox_overlaps (line 25) | def bbox_overlaps(boxes, query_boxes):
  function rand_cmap (line 54) | def rand_cmap(nlabels, type='bright', first_color_black=True, last_color...
  function plot_sequence (line 126) | def plot_sequence(tracks, data_loader, output_dir, write_images, generat...
  function interpolate_tracks (line 239) | def interpolate_tracks(tracks):
  function bbox_transform_inv (line 274) | def bbox_transform_inv(boxes, deltas):
  function clip_boxes (line 302) | def clip_boxes(boxes, im_shape):
  function get_center (line 321) | def get_center(pos):
  function get_width (line 329) | def get_width(pos):
  function get_height (line 333) | def get_height(pos):
  function make_pos (line 337) | def make_pos(cx, cy, width, height):
  function warp_pos (line 346) | def warp_pos(pos, warp_matrix):
  function get_mot_accum (line 354) | def get_mot_accum(results, seq_loader):
  function evaluate_mot_accums (line 405) | def evaluate_mot_accums(accums, names, generate_overall=True):

FILE: src/trackformer/vis.py
  class BaseVis (line 18) | class BaseVis(object):
    method __init__ (line 20) | def __init__(self, viz_opts, update_mode='append', env=None, win=None,
    method win_exists (line 31) | def win_exists(self):
    method close (line 34) | def close(self):
    method register_event_handler (line 39) | def register_event_handler(self, handler):
  class LineVis (line 43) | class LineVis(BaseVis):
    method plot (line 46) | def plot(self, y_data, x_label):
    method reset (line 74) | def reset(self):
  class ImgVis (line 82) | class ImgVis(BaseVis):
    method plot (line 85) | def plot(self, images):
  function vis_results (line 101) | def vis_results(visualizer, img, result, target, tracking):
  function build_visualizers (line 247) | def build_visualizers(args: dict, train_loss_names: list):

FILE: src/train.py
  function train (line 38) | def train(args: Namespace) -> None:
  function load_config (line 346) | def load_config(_config, _run):