SYMBOL INDEX (1528 symbols across 144 files)

FILE: external/cityscape_panoptic.py
  class CityscapesPanopticDataset (line 24) | class CityscapesPanopticDataset(CocoDataset):
    method load_annotations (line 29) | def load_annotations(self, ann_file):
    method _filter_imgs (line 83) | def _filter_imgs(self, min_size=32):
    method _parse_ann_info (line 111) | def _parse_ann_info(self, img_info, ann_info):
    method _panoptic2json (line 164) | def _panoptic2json(self, results, outfile_prefix):
    method results2json (line 202) | def results2json(self, results, outfile_prefix):
    method results2txt (line 256) | def results2txt(self, results, outfile_prefix):
    method format_results (line 322) | def format_results(self, results, jsonfile_prefix="./test", **kwargs):
    method evaluate (line 350) | def evaluate(self,
    method _evaluate_cityscapes (line 574) | def _evaluate_cityscapes(self, results, txtfile_prefix, logger):

FILE: external/cityscapes_step.py
  class CityscapesSTEP (line 12) | class CityscapesSTEP:
    method __init__ (line 18) | def __init__(
    method pre_pipeline (line 70) | def pre_pipeline(self, results):
    method prepare_test_img (line 78) | def prepare_test_img(self, idx):
    method prepare_val_annotation (line 89) | def prepare_val_annotation(self, idx):
    method prepare_train_img (line 102) | def prepare_train_img(self, idx):
    method __getitem__ (line 120) | def __getitem__(self, idx):
    method _rand_another (line 141) | def _rand_another(self, idx):
    method __len__ (line 146) | def __len__(self):
    method _set_groups (line 149) | def _set_groups(self):
    method evaluate (line 153) | def evaluate(
  function vpq_eval (line 247) | def vpq_eval(element):

FILE: external/cityscapes_vps.py
  class CityscapesVPSDataset (line 24) | class CityscapesVPSDataset(CocoDataset):
    method __init__ (line 25) | def __init__(self,
    method load_ref_annotations (line 56) | def load_ref_annotations(self, ann_file):
    method load_annotations (line 71) | def load_annotations(self, ann_file):
    method _filter_imgs (line 124) | def _filter_imgs(self, min_size=32):
    method prepare_train_img (line 152) | def prepare_train_img(self, idx):
    method check_whether_has_correspondence (line 194) | def check_whether_has_correspondence(self, ref_iid, iid):
    method check_match (line 206) | def check_match(self, ref_ann_info, ann_info):
    method prepare_test_img (line 213) | def prepare_test_img(self, idx):
    method pre_pipeline (line 234) | def pre_pipeline(self, results):
    method pre_test_pipeline (line 248) | def pre_test_pipeline(self, results):
    method _parse_ann_info (line 258) | def _parse_ann_info(self, img_info, ann_info):
    method get_ref_ann_info_by_iid (line 319) | def get_ref_ann_info_by_iid(self, img_id, ref_img_info):
    method _panoptic2json (line 324) | def _panoptic2json(self, results, outfile_prefix):
    method results2json (line 358) | def results2json(self, results, outfile_prefix):
    method results2txt (line 412) | def results2txt(self, results, outfile_prefix):
    method format_results (line 478) | def format_results(self, results, jsonfile_prefix=None, **kwargs):
    method evaluate (line 506) | def evaluate(self,
    method _evaluate_cityscapes (line 730) | def _evaluate_cityscapes(self, results, txtfile_prefix, logger):

FILE: external/coco_panoptic.py
  class CocoPanopticDatasetCustom (line 19) | class CocoPanopticDatasetCustom(CocoDataset):
    method load_annotations (line 21) | def load_annotations(self, ann_file):
    method get_ann_info (line 72) | def get_ann_info(self, idx):
    method get_cat_ids (line 87) | def get_cat_ids(self, idx):
    method _parse_ann_info (line 102) | def _parse_ann_info(self, img_info, ann_info):
    method _panoptic2json (line 161) | def _panoptic2json(self, results, outfile_prefix):
    method results2json (line 188) | def results2json(self, results, outfile_prefix):
    method format_results (line 242) | def format_results(self, results, jsonfile_prefix=None, **kwargs):
    method evaluate (line 270) | def evaluate(self,
  function parse_pq_results (line 484) | def parse_pq_results(pq_res):
  function _print_panoptic_results (line 498) | def _print_panoptic_results(pq_res):

FILE: external/dataset/dvps_pipelines/loading.py
  function bitmasks2bboxes (line 7) | def bitmasks2bboxes(bitmasks):
  class LoadImgDirect (line 21) | class LoadImgDirect:
    method __init__ (line 25) | def __init__(self,
    method __call__ (line 31) | def __call__(self, results):
    method __repr__ (line 54) | def __repr__(self):
  class LoadMultiImagesDirect (line 62) | class LoadMultiImagesDirect(LoadImgDirect):
    method __init__ (line 68) | def __init__(self, *args, **kwargs):
    method __call__ (line 71) | def __call__(self, results):
  class LoadAnnotationsDirect (line 89) | class LoadAnnotationsDirect:
    method __init__ (line 93) | def __init__(self,
    method __call__ (line 110) | def __call__(self, results):
  class LoadMultiAnnotationsDirect (line 225) | class LoadMultiAnnotationsDirect(LoadAnnotationsDirect):
    method __init__ (line 226) | def __init__(self, *args, **kwargs):
    method __call__ (line 229) | def __call__(self, results):

FILE: external/dataset/dvps_pipelines/transforms.py
  class ResizeWithDepth (line 8) | class ResizeWithDepth(Resize):
    method __init__ (line 12) | def __init__(self, *args, **kwargs):
    method _resize_depth (line 16) | def _resize_depth(self, results):
    method __call__ (line 34) | def __call__(self, results):
  class SeqResizeWithDepth (line 41) | class SeqResizeWithDepth(ResizeWithDepth):
    method __init__ (line 50) | def __init__(self, share_params=True, *args, **kwargs):
    method __call__ (line 54) | def __call__(self, results):
  class RandomFlipWithDepth (line 78) | class RandomFlipWithDepth(RandomFlip):
    method __init__ (line 79) | def __init__(self, *args, **kwargs):
    method __call__ (line 82) | def __call__(self, results):
  class SeqFlipWithDepth (line 92) | class SeqFlipWithDepth(RandomFlipWithDepth):
    method __init__ (line 101) | def __init__(self, share_params=True, *args, **kwargs):
    method __call__ (line 105) | def __call__(self, results):
  class SeqRandomCropWithDepth (line 149) | class SeqRandomCropWithDepth(object):
    method __init__ (line 173) | def __init__(self,
    method get_offsets (line 196) | def get_offsets(self, img):
    method random_crop (line 204) | def random_crop(self, results, offsets=None):
    method __call__ (line 272) | def __call__(self, results):
    method check_match (line 305) | def check_match(self, ref_results, results):
  class PadWithDepth (line 314) | class PadWithDepth(Pad):
    method _pad_depth (line 316) | def _pad_depth(self, results):
    method _pad_seg (line 325) | def _pad_seg(self, results):
    method __call__ (line 335) | def __call__(self, results):
  class SeqPadWithDepth (line 352) | class SeqPadWithDepth(PadWithDepth):
    method __init__ (line 358) | def __init__(self, *args, **kwargs):
    method __call__ (line 361) | def __call__(self, results):
  class SeqNormalizeWithDepth (line 381) | class SeqNormalizeWithDepth(Normalize):
    method __init__ (line 387) | def __init__(self, *args, **kwargs):
    method __call__ (line 390) | def __call__(self, results):

FILE: external/dataset/dvps_pipelines/tricks.py
  class SeqAutoAug (line 7) | class SeqAutoAug(AutoAugment):
    method __init__ (line 11) | def __init__(self, policies):
    method __call__ (line 14) | def __call__(self, results):

FILE: external/dataset/forecasting_pipelines/loading.py
  function bitmasks2bboxes (line 8) | def bitmasks2bboxes(bitmasks):
  class LoadMultiImagesFromFile (line 22) | class LoadMultiImagesFromFile:
    method __init__ (line 39) | def __init__(self,
    method __call__ (line 48) | def __call__(self, results):
    method __repr__ (line 75) | def __repr__(self):
  class LoadAnnotationsInstanceMasks (line 84) | class LoadAnnotationsInstanceMasks:
    method __init__ (line 85) | def __init__(self,
    method _load_masks (line 96) | def _load_masks(self, results):
    method _load_semantic_seg (line 131) | def _load_semantic_seg(self, results):
    method __call__ (line 144) | def __call__(self, results):
    method __repr__ (line 162) | def __repr__(self):

FILE: external/dataset/forecasting_pipelines/transforms.py
  class NormalizeMultiple (line 8) | class NormalizeMultiple:
    method __init__ (line 20) | def __init__(self, mean, std, to_rgb=True):
    method __call__ (line 25) | def __call__(self, results):
    method __repr__ (line 51) | def __repr__(self):
  class PadFutureMMDet (line 58) | class PadFutureMMDet:
    method __init__ (line 72) | def __init__(self,
    method _pad_img (line 98) | def _pad_img(self, results):
    method _pad_masks (line 116) | def _pad_masks(self, results):
    method _pad_seg (line 123) | def _pad_seg(self, results):
    method __call__ (line 131) | def __call__(self, results):
    method __repr__ (line 143) | def __repr__(self):
  class KNetInsAdapter (line 153) | class KNetInsAdapter:
    method __init__ (line 158) | def __init__(self, stuff_nums=11):
    method __call__ (line 161) | def __call__(self, results):

FILE: external/dataset/mIoU.py
  function eval_miou (line 4) | def eval_miou(results, targets, num_classes, ignore_index=255):

FILE: external/dataset/pipelines/formatting.py
  class ConcatVideoReferences (line 9) | class ConcatVideoReferences(object):
    method __call__ (line 27) | def __call__(self, results):
  class ConcatVideos (line 91) | class ConcatVideos(object):
    method __call__ (line 109) | def __call__(self, results):
  class MultiImagesToTensor (line 165) | class MultiImagesToTensor(object):
    method __init__ (line 177) | def __init__(self, ref_prefix='ref'):
    method __call__ (line 180) | def __call__(self, results):
    method images_to_tensor (line 208) | def images_to_tensor(self, results):
  class SeqDefaultFormatBundle (line 227) | class SeqDefaultFormatBundle(object):
    method __init__ (line 252) | def __init__(self, ref_prefix='ref'):
    method __call__ (line 255) | def __call__(self, results):
    method default_format_bundle (line 289) | def default_format_bundle(self, results):
    method __repr__ (line 336) | def __repr__(self):
  class VideoCollect (line 341) | class VideoCollect(object):
    method __init__ (line 355) | def __init__(self,
    method __call__ (line 379) | def __call__(self, results):
    method _collect_meta_keys (line 416) | def _collect_meta_keys(self, results):
    method _add_default_meta_keys (line 430) | def _add_default_meta_keys(self, results):
  class ToList (line 457) | class ToList(object):
    method __call__ (line 467) | def __call__(self, results):
  class ReIDFormatBundle (line 475) | class ReIDFormatBundle(object):
    method __init__ (line 486) | def __init__(self, *args, **kwargs):
    method __call__ (line 489) | def __call__(self, results):
    method reid_format_bundle (line 517) | def reid_format_bundle(self, results):
  class ImageToTensorWithRef (line 544) | class ImageToTensorWithRef(object):
    method __init__ (line 546) | def __init__(self, keys):
    method __call__ (line 549) | def __call__(self, results):
    method __repr__ (line 567) | def __repr__(self):
  class LabelConsistentChecker (line 571) | class LabelConsistentChecker:
    method __init__ (line 574) | def __init__(self, num_frames=5):
    method __call__ (line 577) | def __call__(self, results):

FILE: external/dataset/pipelines/loading.py
  class LoadMultiImagesFromFile (line 12) | class LoadMultiImagesFromFile(LoadImageFromFile):
    method __init__ (line 18) | def __init__(self, *args, **kwargs):
    method __call__ (line 21) | def __call__(self, results):
  class SeqLoadAnnotations (line 39) | class SeqLoadAnnotations(LoadAnnotations):
    method __init__ (line 47) | def __init__(self, with_track=False, *args, **kwargs):
    method _load_track (line 51) | def _load_track(self, results):
    method __call__ (line 63) | def __call__(self, results):
  class LoadRefImageFromFile (line 85) | class LoadRefImageFromFile(object):
    method __init__ (line 91) | def __init__(self, sample=True, to_float32=False):
    method __call__ (line 95) | def __call__(self, results):
    method __repr__ (line 123) | def __repr__(self):
  function bitmasks2bboxes (line 128) | def bitmasks2bboxes(bitmasks):
  class LoadAnnotationsInstanceMasks (line 142) | class LoadAnnotationsInstanceMasks:
    method __init__ (line 143) | def __init__(self,
    method _load_masks (line 156) | def _load_masks(self, results):
    method _load_semantic_seg (line 193) | def _load_semantic_seg(self, results):
    method __call__ (line 206) | def __call__(self, results):
    method __repr__ (line 224) | def __repr__(self):

FILE: external/dataset/pipelines/test_time_aug.py
  class MultiScaleFlipAugVideo (line 11) | class MultiScaleFlipAugVideo:
    method __init__ (line 47) | def __init__(self,
    method __call__ (line 78) | def __call__(self, results):
    method __repr__ (line 110) | def __repr__(self):

FILE: external/dataset/pipelines/transforms.py
  class SeqColorAug (line 10) | class SeqColorAug(object):
    method __init__ (line 21) | def __init__(self,
    method __call__ (line 29) | def __call__(self, results):
  class SeqBlurAug (line 56) | class SeqBlurAug(object):
    method __init__ (line 63) | def __init__(self, prob=[0.0, 0.2]):
    method __call__ (line 66) | def __call__(self, results):
  class SeqResize (line 96) | class SeqResize(Resize):
    method __init__ (line 105) | def __init__(self, share_params=True, *args, **kwargs):
    method __call__ (line 109) | def __call__(self, results):
  class SeqNormalize (line 133) | class SeqNormalize(Normalize):
    method __init__ (line 139) | def __init__(self, *args, **kwargs):
    method __call__ (line 142) | def __call__(self, results):
  class SeqRandomFlip (line 161) | class SeqRandomFlip(RandomFlip):
    method __init__ (line 170) | def __init__(self, share_params, *args, **kwargs):
    method __call__ (line 174) | def __call__(self, results):
  class SeqPad (line 218) | class SeqPad(Pad):
    method __init__ (line 224) | def __init__(self, *args, **kwargs):
    method __call__ (line 227) | def __call__(self, results):
  class SeqRandomCrop (line 246) | class SeqRandomCrop(object):
    method __init__ (line 270) | def __init__(self,
    method get_offsets (line 293) | def get_offsets(self, img):
    method random_crop (line 301) | def random_crop(self, results, offsets=None):
    method __call__ (line 364) | def __call__(self, results):
    method check_match (line 391) | def check_match(self, ref_results, results):
  class SeqPhotoMetricDistortion (line 400) | class SeqPhotoMetricDistortion(object):
    method __init__ (line 419) | def __init__(self,
    method get_params (line 431) | def get_params(self):
    method photo_metric_distortion (line 467) | def photo_metric_distortion(self, results, params=None):
    method __call__ (line 524) | def __call__(self, results):
    method __repr__ (line 543) | def __repr__(self):
  class ResizeWithRef (line 555) | class ResizeWithRef(object):
    method __init__ (line 580) | def __init__(self,
    method random_select (line 606) | def random_select(img_scales):
    method random_sample (line 613) | def random_sample(img_scales):
    method random_sample_ratio (line 627) | def random_sample_ratio(img_scale, ratio_range):
    method _random_scale (line 635) | def _random_scale(self, results):
    method _resize_img (line 651) | def _resize_img(self, results):
    method _resize_bboxes (line 668) | def _resize_bboxes(self, results):
    method _resize_masks (line 680) | def _resize_masks(self, results):
    method __call__ (line 703) | def __call__(self, results):
    method __repr__ (line 712) | def __repr__(self):
  class RandomFlipWithRef (line 723) | class RandomFlipWithRef(object):
    method __init__ (line 734) | def __init__(self, flip_ratio=None):
    method bbox_flip (line 739) | def bbox_flip(self, bboxes, img_shape):
    method __call__ (line 753) | def __call__(self, results):
    method __repr__ (line 776) | def __repr__(self):
  class PadWithRef (line 782) | class PadWithRef(object):
    method __init__ (line 794) | def __init__(self, size=None, size_divisor=None, pad_val=0):
    method _pad_img (line 802) | def _pad_img(self, results):
    method _pad_masks (line 815) | def _pad_masks(self, results):
    method __call__ (line 826) | def __call__(self, results):
    method __repr__ (line 831) | def __repr__(self):
  class NormalizeWithRef (line 839) | class NormalizeWithRef(object):
    method __init__ (line 849) | def __init__(self, mean, std, to_rgb=True):
    method __call__ (line 854) | def __call__(self, results):
    method __repr__ (line 864) | def __repr__(self):
  class RandomCropWithRef (line 872) | class RandomCropWithRef(object):
    method __init__ (line 879) | def __init__(self, crop_size):
    method __call__ (line 882) | def __call__(self, results):
    method __repr__ (line 948) | def __repr__(self):
  class PadFutureMMDet (line 954) | class PadFutureMMDet:
    method __init__ (line 968) | def __init__(self,
    method _pad_img (line 994) | def _pad_img(self, results):
    method _pad_masks (line 1012) | def _pad_masks(self, results):
    method _pad_seg (line 1019) | def _pad_seg(self, results):
    method __call__ (line 1027) | def __call__(self, results):
    method __repr__ (line 1039) | def __repr__(self):
  class KNetInsAdapter (line 1049) | class KNetInsAdapter:
    method __init__ (line 1054) | def __init__(self, stuff_nums=11):
    method __call__ (line 1057) | def __call__(self, results):
  class KNetInsAdapterCherryPick (line 1069) | class KNetInsAdapterCherryPick:
    method __init__ (line 1074) | def __init__(self, stuff_nums=11, cherry=(11, 13)):
    method __call__ (line 1078) | def __call__(self, results):

FILE: external/evalhooks.py
  class EvalHook (line 15) | class EvalHook(Hook):
    method __init__ (line 50) | def __init__(self,
    method _init_rule (line 82) | def _init_rule(self, rule, key_indicator):
    method before_run (line 109) | def before_run(self, runner):
    method before_train_epoch (line 116) | def before_train_epoch(self, runner):
    method evaluation_flag (line 124) | def evaluation_flag(self, runner):
    method after_train_epoch (line 143) | def after_train_epoch(self, runner):
    method after_train_iter (line 151) | def after_train_iter(self, runner):
    method save_best_checkpoint (line 159) | def save_best_checkpoint(self, runner, key_score):
    method evaluate (line 174) | def evaluate(self, runner, results):
  class DistEvalHook (line 189) | class DistEvalHook(EvalHook):
    method __init__ (line 223) | def __init__(self,
    method _broadcast_bn_buffer (line 246) | def _broadcast_bn_buffer(self, runner):
    method after_train_epoch (line 260) | def after_train_epoch(self, runner):
    method after_train_iter (line 281) | def after_train_iter(self, runner):

FILE: external/ext/mask.py
  function encode (line 80) | def encode(bimask):
  function decode (line 87) | def decode(rleObjs):
  function area (line 93) | def area(rleObjs):
  function toBbox (line 99) | def toBbox(rleObjs):

FILE: external/ext/ytvos.py
  function _isArrayLike (line 37) | def _isArrayLike(obj):
  class YTVOS (line 41) | class YTVOS:
    method __init__ (line 42) | def __init__(self, annotation_file=None):
    method createIndex (line 61) | def createIndex(self):
    method info (line 92) | def info(self):
    method getAnnIds (line 100) | def getAnnIds(self, vidIds=[], catIds=[], areaRng=[], iscrowd=None):
    method getCatIds (line 128) | def getCatIds(self, catNms=[], supNms=[], catIds=[]):
    method getVidIds (line 150) | def     getVidIds(self, vidIds=[], catIds=[]):
    method loadAnns (line 171) | def loadAnns(self, ids=[]):
    method loadCats (line 182) | def loadCats(self, ids=[]):
    method loadVids (line 193) | def loadVids(self, ids=[]):
    method loadRes (line 205) | def loadRes(self, resFile):
    method annToRLE (line 255) | def annToRLE(self, ann, frameId):
    method annToMask (line 276) | def annToMask(self, ann, frameId):

FILE: external/fcn_mask_head.py
  class InstanceMaskHead (line 14) | class InstanceMaskHead(FCNMaskHead):
    method __init__ (line 16) | def __init__(self, **kwargs):
    method get_seg_masks (line 19) | def get_seg_masks(self, mask_pred, det_bboxes, det_labels, rcnn_test_cfg,

FILE: external/kitti_step_dvps.py
  class SeqObj (line 19) | class SeqObj:
    method __init__ (line 23) | def __init__(self, the_dict: Dict):
    method __hash__ (line 27) | def __hash__(self):
    method __eq__ (line 30) | def __eq__(self, other):
    method __getitem__ (line 33) | def __getitem__(self, attr):
  class KITTISTEPDVPSDataset (line 38) | class KITTISTEPDVPSDataset:
    method __init__ (line 44) | def __init__(self,
    method pre_pipelines (line 124) | def pre_pipelines(self, results):
    method prepare_train_img (line 133) | def prepare_train_img(self, idx):
    method prepare_test_img (line 147) | def prepare_test_img(self, idx):
    method _rand_another (line 155) | def _rand_another(self, idx):
    method __getitem__ (line 161) | def __getitem__(self, idx):
    method __len__ (line 182) | def __len__(self):
    method _set_groups (line 186) | def _set_groups(self):
    method evaluate (line 190) | def evaluate(
  function vpq_eval (line 321) | def vpq_eval(element):

FILE: external/panoptic_fpn.py
  class PanopticFPN (line 6) | class PanopticFPN(TwoStageDetector):
    method __init__ (line 9) | def __init__(self,
    method with_semantic (line 27) | def with_semantic(self):

FILE: external/panoptic_head.py
  class PanopticTestMixin (line 7) | class PanopticTestMixin(object):
    method simple_test_semantic (line 9) | def simple_test_semantic(self, x, img_metas):
    method generate_panoptic (line 20) | def generate_panoptic(self, det_bboxes, det_labels, mask_preds, sem_seg,
  class PanopticHead (line 31) | class PanopticHead(StandardRoIHead, PanopticTestMixin):
    method __init__ (line 34) | def __init__(self, *args, semantic_head, **kwargs):
    method with_semantic (line 39) | def with_semantic(self):
    method init_weights (line 46) | def init_weights(self, pretrained):
    method forward_train (line 57) | def forward_train(self,
    method async_simple_test (line 131) | async def async_simple_test(self,
    method simple_test (line 140) | def simple_test(self,
  function mask2result (line 182) | def mask2result(mask_preds, labels, num_classes):
  function merge_stuff_thing (line 196) | def merge_stuff_thing(det_bboxes,

FILE: external/semantic_seg_head.py
  class SemanticHead (line 10) | class SemanticHead(FusedSemanticHead):
    method __init__ (line 29) | def __init__(self,
    method init_weights (line 54) | def init_weights(self):
    method forward (line 58) | def forward(self, feats):
    method loss (line 64) | def loss(self, mask_pred, labels):
    method get_semantic_seg (line 80) | def get_semantic_seg(self, seg_preds, ori_shape, img_shape_withoutpad):

FILE: external/semkitti_dvps.py
  class SeqObj (line 15) | class SeqObj:
    method __init__ (line 19) | def __init__(self, the_dict: Dict):
    method __hash__ (line 23) | def __hash__(self):
    method __eq__ (line 26) | def __eq__(self, other):
    method __getitem__ (line 29) | def __getitem__(self, attr):
  class KITTIDVPSDataset (line 34) | class KITTIDVPSDataset:
    method __init__ (line 39) | def __init__(self,
    method pre_pipelines (line 121) | def pre_pipelines(self, results):
    method prepare_train_img (line 130) | def prepare_train_img(self, idx):
    method prepare_test_img (line 144) | def prepare_test_img(self, idx):
    method _rand_another (line 152) | def _rand_another(self, idx):
    method __getitem__ (line 158) | def __getitem__(self, idx):
    method __len__ (line 179) | def __len__(self):
    method _set_groups (line 183) | def _set_groups(self):
    method evaluate (line 187) | def evaluate(
  function vpq_eval (line 299) | def vpq_eval(element):

FILE: external/test.py
  function single_gpu_test (line 13) | def single_gpu_test(model,
  function multi_gpu_test (line 78) | def multi_gpu_test(model, data_loader, tmpdir=None, gpu_collect=False):

FILE: external/train.py
  function train_detector (line 16) | def train_detector(model,

FILE: external/utils.py
  function encode_panoptic (line 7) | def encode_panoptic(panoptic_results):

FILE: external/vipseg_dvps.py
  function vip2hb (line 282) | def vip2hb(pan_map):
  class SeqObj (line 303) | class SeqObj:
    method __init__ (line 307) | def __init__(self, the_dict: Dict):
    method __hash__ (line 311) | def __hash__(self):
    method __eq__ (line 314) | def __eq__(self, other):
    method __getitem__ (line 317) | def __getitem__(self, attr):
  class VIPSegDVPSDataset (line 322) | class VIPSegDVPSDataset:
    method __init__ (line 327) | def __init__(self,
    method pre_pipelines (line 427) | def pre_pipelines(self, results):
    method prepare_train_img (line 438) | def prepare_train_img(self, idx):
    method prepare_test_img (line 452) | def prepare_test_img(self, idx):
    method _rand_another (line 460) | def _rand_another(self, idx):
    method __getitem__ (line 466) | def __getitem__(self, idx):
    method __len__ (line 487) | def __len__(self):
    method _set_groups (line 491) | def _set_groups(self):
    method evaluate (line 495) | def evaluate(

FILE: knet/cross_entropy_loss.py
  function cross_entropy (line 8) | def cross_entropy(pred,
  function _expand_onehot_labels (line 45) | def _expand_onehot_labels(labels, label_weights, label_channels):
  function binary_cross_entropy (line 61) | def binary_cross_entropy(pred,
  function mask_cross_entropy (line 95) | def mask_cross_entropy(pred,
  class CrossEntropyLoss (line 140) | class CrossEntropyLoss(nn.Module):
    method __init__ (line 142) | def __init__(self,
    method forward (line 175) | def forward(self,

FILE: knet/det/dice_loss.py
  function dice_loss (line 9) | def dice_loss(input, target, eps=1e-3, numerator_eps=0):

FILE: knet/det/kernel_head.py
  class ConvKernelHead (line 12) | class ConvKernelHead(nn.Module):
    method __init__ (line 14) | def __init__(self,
    method _init_layers (line 122) | def _init_layers(self):
    method init_weights (line 169) | def init_weights(self):
    method _decode_init_proposals (line 196) | def _decode_init_proposals(self, img, img_metas):
    method forward_train (line 267) | def forward_train(self,
    method loss (line 337) | def loss(self,
    method _get_target_single (line 430) | def _get_target_single(self, pos_inds, neg_inds, pos_mask, neg_mask,
    method get_targets (line 469) | def get_targets(self,
    method simple_test_rpn (line 506) | def simple_test_rpn(self, img, img_metas):
    method forward_dummy (line 510) | def forward_dummy(self, img, img_metas):

FILE: knet/det/kernel_iter_head.py
  class KernelIterHead (line 12) | class KernelIterHead(BaseRoIHead):
    method __init__ (line 14) | def __init__(self,
    method init_bbox_head (line 76) | def init_bbox_head(self, mask_roi_extractor, mask_head):
    method init_assigner_sampler (line 85) | def init_assigner_sampler(self):
    method init_weights (line 97) | def init_weights(self):
    method init_mask_head (line 101) | def init_mask_head(self, mask_roi_extractor, mask_head):
    method _mask_forward (line 118) | def _mask_forward(self, stage, x, object_feats, mask_preds, img_metas):
    method forward_train (line 139) | def forward_train(self,
    method simple_test (line 233) | def simple_test(self,
    method simple_test_mask_preds (line 285) | def simple_test_mask_preds(self,
    method aug_test (line 314) | def aug_test(self, features, proposal_list, img_metas, rescale=False):
    method forward_dummy (line 317) | def forward_dummy(self, x, proposal_boxes, proposal_feats, img_metas):
    method get_panoptic (line 332) | def get_panoptic(self, cls_scores, mask_preds, test_cfg, img_meta):
    method split_thing_stuff (line 372) | def split_thing_stuff(self, mask_preds, det_labels, cls_scores):
    method merge_stuff_thing (line 386) | def merge_stuff_thing(self,
    method merge_stuff_thing_stuff_joint (line 467) | def merge_stuff_thing_stuff_joint(self,

FILE: knet/det/kernel_update_head.py
  class KernelUpdateHead (line 17) | class KernelUpdateHead(nn.Module):
    method __init__ (line 19) | def __init__(self,
    method init_weights (line 151) | def init_weights(self):
    method forward (line 170) | def forward(self,
    method loss (line 280) | def loss(self,
    method _get_target_single (line 351) | def _get_target_single(self, pos_inds, neg_inds, pos_mask, neg_mask,
    method get_targets (line 406) | def get_targets(self,
    method rescale_masks (line 443) | def rescale_masks(self, masks_per_img, img_meta):
    method get_seg_masks (line 460) | def get_seg_masks(self, masks_per_img, labels_per_img, scores_per_img,
    method segm2result (line 469) | def segm2result(self, mask_preds, det_labels, cls_scores):

FILE: knet/det/knet.py
  class KNet (line 10) | class KNet(TwoStageDetector):
    method __init__ (line 12) | def __init__(self,
    method forward_train (line 32) | def forward_train(self,
    method simple_test (line 161) | def simple_test(self, img, img_metas, rescale=False):
    method forward_dummy (line 192) | def forward_dummy(self, img):

FILE: knet/det/mask_hungarian_assigner.py
  class DiceCost (line 15) | class DiceCost(object):
    method __init__ (line 34) | def __init__(self,
    method dice_loss (line 44) | def dice_loss(cls, input, target, eps=1e-3):
    method __call__ (line 56) | def __call__(self, mask_preds, gt_masks):
  class MaskCost (line 78) | class MaskCost(object):
    method __init__ (line 85) | def __init__(self, weight=1., pred_act=False, act_mode='sigmoid'):
    method __call__ (line 90) | def __call__(self, cls_pred, target):
  class MaskHungarianAssigner (line 118) | class MaskHungarianAssigner(BaseAssigner):
    method __init__ (line 146) | def __init__(self,
    method assign (line 161) | def assign(self,

FILE: knet/det/mask_pseudo_sampler.py
  class MaskSamplingResult (line 7) | class MaskSamplingResult(SamplingResult):
    method __init__ (line 26) | def __init__(self, pos_inds, neg_inds, masks, gt_masks, assign_result,
    method masks (line 55) | def masks(self):
    method __nice__ (line 59) | def __nice__(self):
    method info (line 68) | def info(self):
  class MaskSamplingResultWithScore (line 81) | class MaskSamplingResultWithScore(SamplingResult):
    method __init__ (line 100) | def __init__(self, pos_inds, neg_inds, masks, scores, gt_masks, assign...
    method masks (line 133) | def masks(self):
    method __nice__ (line 137) | def __nice__(self):
    method info (line 146) | def info(self):
  class MaskPseudoSampler (line 159) | class MaskPseudoSampler(BaseSampler):
    method __init__ (line 162) | def __init__(self, **kwargs):
    method _sample_pos (line 165) | def _sample_pos(self, **kwargs):
    method _sample_neg (line 169) | def _sample_neg(self, **kwargs):
    method sample (line 173) | def sample(self, assign_result, masks, gt_masks, **kwargs):
  class MaskScorePseudoSampler (line 195) | class MaskScorePseudoSampler(BaseSampler):
    method __init__ (line 198) | def __init__(self, **kwargs):
    method _sample_pos (line 201) | def _sample_pos(self, **kwargs):
    method _sample_neg (line 205) | def _sample_neg(self, **kwargs):
    method sample (line 209) | def sample(self, assign_result, masks, score, gt_masks, **kwargs):

FILE: knet/det/msdeformattn_decoder.py
  class MSDeformAttnPixelDecoder (line 18) | class MSDeformAttnPixelDecoder(BaseModule):
    method __init__ (line 42) | def __init__(self,
    method init_weights (line 139) | def init_weights(self):
    method forward (line 165) | def forward(self, feats):

FILE: knet/det/semantic_fpn_wrapper.py
  class SemanticFPNWrapper (line 17) | class SemanticFPNWrapper(nn.Module):
    method __init__ (line 33) | def __init__(self,
    method init_weights (line 180) | def init_weights(self):
    method generate_coord (line 187) | def generate_coord(self, input_feat):
    method forward (line 198) | def forward(self, inputs):
  class UperNetAlignHead (line 239) | class UperNetAlignHead(BaseModule):
    method __init__ (line 241) | def __init__(self, in_channels=[256, 512, 1024, 2048], out_channels=25...
    method forward (line 287) | def forward(self, conv_out):
  class AlignedModule (line 321) | class AlignedModule(nn.Module):
    method __init__ (line 323) | def __init__(self, inplane, outplane, kernel_size=3):
    method forward (line 329) | def forward(self, x):
    method flow_warp (line 342) | def flow_warp(self, input, flow, size):
  class AlignedModulev2PoolingAtten (line 357) | class AlignedModulev2PoolingAtten(nn.Module):
    method __init__ (line 359) | def __init__(self, inplane, outplane, kernel_size=3):
    method forward (line 369) | def forward(self, x):
    method flow_warp (line 395) | def flow_warp(self, input, flow, size):
  class STDCNet1446 (line 413) | class STDCNet1446(nn.Module):
    method __init__ (line 414) | def __init__(self, base=64, layers=[4, 5, 3], block_num=4, type="cat",...
    method init_weight (line 453) | def init_weight(self, pretrain_model):
    method init_params (line 461) | def init_params(self):
    method _make_layers (line 475) | def _make_layers(self, base, layers, block_num, block, norm_layer):
    method forward (line 493) | def forward(self, x):
  class STDCNet813 (line 506) | class STDCNet813(nn.Module):
    method __init__ (line 507) | def __init__(self, base=64, layers=[2, 2, 2], block_num=4, type="cat",...
    method init_weight (line 546) | def init_weight(self, pretrain_model):
    method init_params (line 554) | def init_params(self):
    method _make_layers (line 568) | def _make_layers(self, base, layers, block_num, block, norm_layer):
    method forward (line 586) | def forward(self, x):
  class AddBottleneck (line 600) | class AddBottleneck(nn.Module):
    method __init__ (line 601) | def __init__(self, in_planes, out_planes, block_num=3, stride=1, norm_...
    method forward (line 633) | def forward(self, x):
  class CatBottleneck (line 650) | class CatBottleneck(nn.Module):
    method __init__ (line 651) | def __init__(self, in_planes, out_planes, block_num=3, stride=1, norm_...
    method forward (line 678) | def forward(self, x):
  class ConvX (line 700) | class ConvX(nn.Module):
    method __init__ (line 701) | def __init__(self, in_planes, out_planes, kernel=3, stride=1, norm_lay...
    method forward (line 707) | def forward(self, x):

FILE: knet/det/utils.py
  function sem2ins_masks (line 8) | def sem2ins_masks(gt_sem_seg,
  function sem2ins_masks_cityscapes (line 34) | def sem2ins_masks_cityscapes(gt_sem_seg,
  function sem2ins_masks_kitti_step (line 63) | def sem2ins_masks_kitti_step(gt_sem_seg,

FILE: knet/kernel_updator.py
  class KernelUpdator (line 8) | class KernelUpdator(nn.Module):
    method __init__ (line 10) | def __init__(self,
    method forward (line 56) | def forward(self, update_feature, input_feature):

FILE: knet/video/dice_loss.py
  function dice_loss (line 8) | def dice_loss(input, target, eps=1e-3, numerator_eps=0):

FILE: knet/video/kernel_head.py
  class VideoConvKernelHead (line 12) | class VideoConvKernelHead(nn.Module):
    method __init__ (line 16) | def __init__(self,
    method _init_layers (line 126) | def _init_layers(self):
    method init_weights (line 172) | def init_weights(self):
    method _decode_init_proposals (line 199) | def _decode_init_proposals(self, img, img_metas,
    method forward_train (line 272) | def forward_train(self,
    method loss (line 345) | def loss(self,
    method _get_target_single (line 436) | def _get_target_single(self, pos_inds, neg_inds, pos_mask, neg_mask,
    method get_targets (line 475) | def get_targets(self,
    method simple_test_rpn (line 512) | def simple_test_rpn(self, img, img_metas,
    method forward_dummy (line 517) | def forward_dummy(self, img, img_metas):

FILE: knet/video/kernel_iter_head.py
  class VideoKernelIterHead (line 11) | class VideoKernelIterHead(BaseRoIHead):
    method __init__ (line 13) | def __init__(self,
    method init_bbox_head (line 76) | def init_bbox_head(self, mask_roi_extractor, mask_head):
    method init_assigner_sampler (line 85) | def init_assigner_sampler(self):
    method init_weights (line 97) | def init_weights(self):
    method init_mask_head (line 101) | def init_mask_head(self, mask_roi_extractor, mask_head):
    method _mask_forward (line 118) | def _mask_forward(self, stage, x, object_feats, mask_preds, img_metas,
    method forward_train (line 150) | def forward_train(self,
    method forward_train_with_previous (line 255) | def forward_train_with_previous(self,
    method simple_test (line 378) | def simple_test(self,
    method simple_test_with_previous (line 435) | def simple_test_with_previous(self,
    method simple_test_mask_preds (line 508) | def simple_test_mask_preds(self,
    method simple_test_mask_preds_plus_previous (line 531) | def simple_test_mask_preds_plus_previous(
    method get_masked_feature (line 566) | def get_masked_feature(self, x, mask_pred):
    method aug_test (line 573) | def aug_test(self, features, proposal_list, img_metas, rescale=False):
    method forward_dummy (line 576) | def forward_dummy(self, x, proposal_boxes, proposal_feats, img_metas):
    method get_panoptic (line 591) | def get_panoptic(self, cls_scores, mask_preds, test_cfg, img_meta, obj...
    method split_thing_stuff (line 642) | def split_thing_stuff(self, mask_preds, det_labels, cls_scores):
    method merge_stuff_thing_thing_first (line 656) | def merge_stuff_thing_thing_first(self,
    method merge_stuff_thing_stuff_first (line 743) | def merge_stuff_thing_stuff_first(self,
    method merge_stuff_thing_stuff_joint (line 832) | def merge_stuff_thing_stuff_joint(self,

FILE: knet/video/kernel_update_head.py
  class VideoKernelUpdateHead (line 18) | class VideoKernelUpdateHead(nn.Module):
    method __init__ (line 20) | def __init__(self,
    method init_weights (line 262) | def init_weights(self):
    method forward (line 281) | def forward(self,
    method loss (line 544) | def loss(self,
    method _get_target_single (line 615) | def _get_target_single(self, pos_inds, neg_inds, pos_mask, neg_mask,
    method get_targets (line 670) | def get_targets(self,
    method rescale_masks (line 708) | def rescale_masks(self, masks_per_img, img_meta):
    method get_seg_masks (line 725) | def get_seg_masks(self, masks_per_img, labels_per_img, scores_per_img,
    method segm2result (line 734) | def segm2result(self, mask_preds, det_labels, cls_scores):

FILE: knet/video/knet.py
  class VideoKNet (line 10) | class VideoKNet(TwoStageDetector):
    method __init__ (line 12) | def __init__(self,
    method forward_train (line 31) | def forward_train(self,
    method simple_test (line 182) | def simple_test(self, img, img_metas, rescale=False):
    method forward_dummy (line 210) | def forward_dummy(self, img):
    method extract_feat (line 230) | def extract_feat(self, img):

FILE: knet/video/knet_quansi_dense.py
  class VideoKNetQuansiTrack (line 15) | class VideoKNetQuansiTrack(BaseDetector):
    method __init__ (line 19) | def __init__(self,
    method init_tracker (line 113) | def init_tracker(self):
    method _freeze_detector (line 116) | def _freeze_detector(self):
    method init_track_assigner_sampler (line 126) | def init_track_assigner_sampler(self):
    method preprocess_gt_masks (line 137) | def preprocess_gt_masks(self, img_metas, gt_masks, gt_labels, gt_seman...
    method forward_train (line 200) | def forward_train(self,
    method simple_test (line 402) | def simple_test(self, img, img_metas, rescale=False, ref_img=None, **k...
    method _track_forward (line 511) | def _track_forward(self, x, mask_pred):
    method forward_dummy (line 528) | def forward_dummy(self, img):
    method extract_feat (line 547) | def extract_feat(self, img):
    method with_rpn (line 555) | def with_rpn(self):
    method with_roi_head (line 560) | def with_roi_head(self):
    method aug_test (line 564) | def aug_test(self, x, proposal_list, img_metas, rescale=False, **kwargs):
    method get_things_id_for_tracking (line 572) | def get_things_id_for_tracking(self, panoptic_seg, seg_infos):
    method pack_things_object (line 586) | def pack_things_object(self, object_feats, ref_object_feats):
    method pack_things_masks (line 592) | def pack_things_masks(self, mask_pred, ref_mask_pred):
    method get_semantic_seg (line 597) | def get_semantic_seg(self, panoptic_seg, segments_info):
    method generate_track_id_maps (line 625) | def generate_track_id_maps(self, ids, masks, panopitc_seg_maps):
  function log_masks_for_inference (line 642) | def log_masks_for_inference(masks_preds, names, output_dirs="work_dirs/v...

FILE: knet/video/knet_quansi_dense_embed_fc.py
  class VideoKNetQuansiEmbedFC (line 18) | class VideoKNetQuansiEmbedFC(BaseDetector):
    method __init__ (line 23) | def __init__(self,
    method init_tracker (line 126) | def init_tracker(self):
    method _freeze_detector (line 129) | def _freeze_detector(self):
    method init_track_assigner_sampler (line 139) | def init_track_assigner_sampler(self):
    method preprocess_gt_masks (line 150) | def preprocess_gt_masks(self, img_metas, gt_masks, gt_labels, gt_seman...
    method forward_train (line 222) | def forward_train(self,
    method simple_test (line 468) | def simple_test(self, img, img_metas, rescale=False, ref_img=None, **k...
    method _track_forward (line 607) | def _track_forward(self, track_feats, x=None, mask_pred=None):
    method forward_dummy (line 625) | def forward_dummy(self, img):
    method extract_feat (line 644) | def extract_feat(self, img):
    method with_rpn (line 652) | def with_rpn(self):
    method with_roi_head (line 657) | def with_roi_head(self):
    method aug_test (line 661) | def aug_test(self, x, proposal_list, img_metas, rescale=False, **kwargs):
    method get_things_id_for_tracking (line 669) | def get_things_id_for_tracking(self, panoptic_seg, seg_infos):
    method pack_things_object (line 683) | def pack_things_object(self, object_feats, ref_object_feats):
    method pack_things_masks (line 690) | def pack_things_masks(self, mask_pred, ref_mask_pred):
    method get_semantic_seg (line 696) | def get_semantic_seg(self, panoptic_seg, segments_info):
    method generate_track_id_maps (line 724) | def generate_track_id_maps(self, ids, masks, panopitc_seg_maps):

FILE: knet/video/knet_quansi_dense_embed_fc_joint_train.py
  class VideoKNetQuansiEmbedFCJointTrain (line 18) | class VideoKNetQuansiEmbedFCJointTrain(BaseDetector):
    method __init__ (line 22) | def __init__(self,
    method init_tracker (line 128) | def init_tracker(self):
    method _freeze_detector (line 131) | def _freeze_detector(self):
    method init_track_assigner_sampler (line 141) | def init_track_assigner_sampler(self):
    method preprocess_gt_masks (line 152) | def preprocess_gt_masks(self, img_metas, gt_masks, gt_labels, gt_seman...
    method forward_train (line 225) | def forward_train(self,
    method simple_test (line 472) | def simple_test(self, img, img_metas, rescale=False, ref_img=None, **k...
    method _track_forward (line 614) | def _track_forward(self, track_feats, x=None, mask_pred=None):
    method forward_dummy (line 625) | def forward_dummy(self, img, img_metas=None):
    method extract_feat (line 648) | def extract_feat(self, img):
    method with_rpn (line 656) | def with_rpn(self):
    method with_roi_head (line 661) | def with_roi_head(self):
    method aug_test (line 665) | def aug_test(self, x, proposal_list, img_metas, rescale=False, **kwargs):
    method get_things_id_for_tracking (line 673) | def get_things_id_for_tracking(self, panoptic_seg, seg_infos):
    method pack_things_object (line 687) | def pack_things_object(self, object_feats, ref_object_feats):
    method pack_things_masks (line 693) | def pack_things_masks(self, mask_pred, ref_mask_pred):
    method get_semantic_seg (line 698) | def get_semantic_seg(self, panoptic_seg, segments_info):
    method generate_track_id_maps (line 724) | def generate_track_id_maps(self, ids, masks, panopitc_seg_maps):
    method add_ref_loss (line 738) | def add_ref_loss(self, loss_dict):
    method add_ref_rpn_loss (line 744) | def add_ref_rpn_loss(self, loss_dict):

FILE: knet/video/knet_quansi_dense_embed_fc_toy_exp.py
  class VideoKNetQuansiEmbedFCToy (line 15) | class VideoKNetQuansiEmbedFCToy(BaseDetector):
    method __init__ (line 19) | def __init__(self,
    method init_tracker (line 127) | def init_tracker(self):
    method _freeze_detector (line 130) | def _freeze_detector(self):
    method init_track_assigner_sampler (line 140) | def init_track_assigner_sampler(self):
    method preprocess_gt_masks (line 151) | def preprocess_gt_masks(self, img_metas, gt_masks, gt_labels, gt_seman...
    method forward_train (line 223) | def forward_train(self,
    method simple_test (line 467) | def simple_test(self, img, img_metas, rescale=False, ref_img=None, **k...
    method _track_forward (line 587) | def _track_forward(self, track_feats, x=None, mask_pred=None):
    method forward_dummy (line 605) | def forward_dummy(self, img):
    method extract_feat (line 624) | def extract_feat(self, img):
    method with_rpn (line 632) | def with_rpn(self):
    method with_roi_head (line 637) | def with_roi_head(self):
    method aug_test (line 641) | def aug_test(self, x, proposal_list, img_metas, rescale=False, **kwargs):
    method get_things_id_for_tracking (line 649) | def get_things_id_for_tracking(self, panoptic_seg, seg_infos):
    method pack_things_object (line 663) | def pack_things_object(self, object_feats, ref_object_feats):
    method pack_things_masks (line 669) | def pack_things_masks(self, mask_pred, ref_mask_pred):
    method get_semantic_seg (line 674) | def get_semantic_seg(self, panoptic_seg, segments_info):
    method generate_track_id_maps (line 702) | def generate_track_id_maps(self, ids, masks, panopitc_seg_maps):

FILE: knet/video/knet_quansi_dense_roi_gt_box.py
  class VideoKNetQuansiTrackROIGTBox (line 16) | class VideoKNetQuansiTrackROIGTBox(BaseDetector):
    method __init__ (line 20) | def __init__(self,
    method init_tracker (line 111) | def init_tracker(self):
    method _freeze_detector (line 114) | def _freeze_detector(self):
    method init_track_assigner_sampler (line 124) | def init_track_assigner_sampler(self):
    method preprocess_gt_masks (line 135) | def preprocess_gt_masks(self, img_metas, gt_masks, gt_labels, gt_seman...
    method forward_train (line 207) | def forward_train(self,
    method simple_test (line 436) | def simple_test(self, img, img_metas, rescale=False, ref_img=None, **k...
    method _track_forward (line 567) | def _track_forward(self, x, mask_pred):
    method forward_dummy (line 580) | def forward_dummy(self, img):
    method extract_feat (line 599) | def extract_feat(self, img):
    method with_rpn (line 607) | def with_rpn(self):
    method with_roi_head (line 612) | def with_roi_head(self):
    method aug_test (line 616) | def aug_test(self, x, proposal_list, img_metas, rescale=False, **kwargs):
    method get_things_id_for_tracking (line 624) | def get_things_id_for_tracking(self, panoptic_seg, seg_infos):
    method pack_things_object (line 639) | def pack_things_object(self, object_feats, ref_object_feats):
    method pack_things_masks (line 645) | def pack_things_masks(self, mask_pred, ref_mask_pred):
    method get_semantic_seg (line 650) | def get_semantic_seg(self, panoptic_seg, segments_info):
    method generate_track_id_maps (line 678) | def generate_track_id_maps(self, ids, masks, panopitc_seg_maps):

FILE: knet/video/knet_quansi_dense_roi_gt_box_joint_train.py
  class VideoKNetQuansiTrackROIGTBoxJointTrain (line 17) | class VideoKNetQuansiTrackROIGTBoxJointTrain(BaseDetector):
    method __init__ (line 21) | def __init__(self,
    method init_tracker (line 112) | def init_tracker(self):
    method _freeze_detector (line 115) | def _freeze_detector(self):
    method init_track_assigner_sampler (line 125) | def init_track_assigner_sampler(self):
    method preprocess_gt_masks (line 136) | def preprocess_gt_masks(self, img_metas, gt_masks, gt_labels, gt_seman...
    method forward_train (line 205) | def forward_train(self,
    method simple_test (line 450) | def simple_test(self, img, img_metas, rescale=False, ref_img=None, **k...
    method _track_forward (line 575) | def _track_forward(self, x, mask_pred):
    method forward_dummy (line 588) | def forward_dummy(self, img):
    method extract_feat (line 607) | def extract_feat(self, img):
    method with_rpn (line 615) | def with_rpn(self):
    method with_roi_head (line 620) | def with_roi_head(self):
    method aug_test (line 624) | def aug_test(self, x, proposal_list, img_metas, rescale=False, **kwargs):
    method get_things_id_for_tracking (line 632) | def get_things_id_for_tracking(self, panoptic_seg, seg_infos):
    method pack_things_object (line 647) | def pack_things_object(self, object_feats, ref_object_feats):
    method pack_things_masks (line 653) | def pack_things_masks(self, mask_pred, ref_mask_pred):
    method get_semantic_seg (line 658) | def get_semantic_seg(self, panoptic_seg, segments_info):
    method generate_track_id_maps (line 686) | def generate_track_id_maps(self, ids, masks, panopitc_seg_maps):
    method add_ref_loss (line 697) | def add_ref_loss(self, loss_dict):
    method add_ref_rpn_loss (line 703) | def add_ref_rpn_loss(self, loss_dict):

FILE: knet/video/knet_track_head.py
  class VideoKNetFuseTrack (line 12) | class VideoKNetFuseTrack(BaseDetector):
    method __init__ (line 16) | def __init__(self,
    method preprocess_gt_masks (line 76) | def preprocess_gt_masks(self, img_metas, gt_masks, gt_labels, gt_seman...
    method forward_train (line 139) | def forward_train(self,
    method simple_test (line 312) | def simple_test(self, img, img_metas, rescale=False, ref_img=None):
    method forward_dummy (line 394) | def forward_dummy(self, img):
    method extract_feat (line 413) | def extract_feat(self, img):
    method with_rpn (line 421) | def with_rpn(self):
    method with_roi_head (line 426) | def with_roi_head(self):
    method aug_test (line 430) | def aug_test(self, x, proposal_list, img_metas, rescale=False, **kwargs):
    method pack_things_object (line 438) | def pack_things_object(self, object_feats, ref_object_feats):
    method add_track_loss (line 444) | def add_track_loss(self, loss_dict):
    method add_ref_rpn_loss (line 450) | def add_ref_rpn_loss(self, loss_dict):
    method pack_stuff_things_result (line 456) | def pack_stuff_things_result(self, panoptic_seg, segments_info):
    method generate_track_id_maps (line 478) | def generate_track_id_maps(self, track_results, panopitc_seg_maps):

FILE: knet/video/knet_track_head_roi_align.py
  class VideoKNetFuseROITrack (line 12) | class VideoKNetFuseROITrack(BaseDetector):
    method __init__ (line 16) | def __init__(self,
    method preprocess_gt_masks (line 76) | def preprocess_gt_masks(self, img_metas, gt_masks, gt_labels, gt_seman...
    method forward_train (line 139) | def forward_train(self,
    method simple_test (line 313) | def simple_test(self, img, img_metas, rescale=False, ref_img=None):
    method forward_dummy (line 395) | def forward_dummy(self, img):
    method extract_feat (line 414) | def extract_feat(self, img):
    method with_rpn (line 422) | def with_rpn(self):
    method with_roi_head (line 427) | def with_roi_head(self):
    method aug_test (line 431) | def aug_test(self, x, proposal_list, img_metas, rescale=False, **kwargs):
    method pack_things_object (line 439) | def pack_things_object(self, object_feats, ref_object_feats):
    method pack_things_masks (line 445) | def pack_things_masks(self, mask_pred, ref_mask_pred):
    method add_track_loss (line 450) | def add_track_loss(self, loss_dict):
    method add_ref_rpn_loss (line 456) | def add_ref_rpn_loss(self, loss_dict):
    method pack_stuff_things_result (line 462) | def pack_stuff_things_result(self, panoptic_seg, segments_info):
    method generate_track_id_maps (line 484) | def generate_track_id_maps(self, track_results, panopitc_seg_maps):

FILE: knet/video/knet_uni_track.py
  class VideoKNetUniTrack (line 13) | class VideoKNetUniTrack(BaseDetector):
    method __init__ (line 14) | def __init__(self,
    method preprocess_gt_masks (line 72) | def preprocess_gt_masks(self, img_metas, gt_masks, gt_labels, gt_seman...
    method forward_train (line 135) | def forward_train(self,
    method simple_test (line 282) | def simple_test(self, img, img_metas, rescale=False, ref_img=None):
    method forward_dummy (line 348) | def forward_dummy(self, img):
    method extract_feat (line 368) | def extract_feat(self, img):
    method with_rpn (line 376) | def with_rpn(self):
    method with_roi_head (line 381) | def with_roi_head(self):
    method aug_test (line 385) | def aug_test(self, x, proposal_list, img_metas, rescale=False, **kwargs):
    method add_track_loss (line 393) | def add_track_loss(self, loss_dict):
    method add_ref_rpn_loss (line 399) | def add_ref_rpn_loss(self, loss_dict):
    method pack_stuff_things_result (line 405) | def pack_stuff_things_result(self, panoptic_seg, segments_info):
    method generate_track_id_maps (line 427) | def generate_track_id_maps(self, track_results, panopitc_seg_maps):
    method get_semantic_seg (line 436) | def get_semantic_seg(self, panoptic_seg, segments_info):

FILE: knet/video/mask_hungarian_assigner.py
  class DiceCost (line 14) | class DiceCost(object):
    method __init__ (line 33) | def __init__(self,
    method dice_loss (line 43) | def dice_loss(cls, input, target, eps=1e-3):
    method __call__ (line 55) | def __call__(self, mask_preds, gt_masks):
  class MaskCost (line 76) | class MaskCost(object):
    method __init__ (line 83) | def __init__(self, weight=1., pred_act=False, act_mode='sigmoid'):
    method __call__ (line 88) | def __call__(self, cls_pred, target):
  class MaskHungarianAssigner (line 116) | class MaskHungarianAssigner(BaseAssigner):
    method __init__ (line 144) | def __init__(self,
    method assign (line 159) | def assign(self,
  class MaskHungarianAssignerWithEmbed (line 274) | class MaskHungarianAssignerWithEmbed(BaseAssigner):
    method __init__ (line 302) | def __init__(self,
    method assign (line 317) | def assign(self,

FILE: knet/video/mask_pseudo_sampler.py
  class MaskSamplingResult (line 7) | class MaskSamplingResult(SamplingResult):
    method __init__ (line 26) | def __init__(self, pos_inds, neg_inds, masks, gt_masks, assign_result,
    method masks (line 50) | def masks(self):
    method __nice__ (line 54) | def __nice__(self):
    method info (line 63) | def info(self):

FILE: knet/video/qdtrack/builder.py
  function build_tracker (line 7) | def build_tracker(cfg):

FILE: knet/video/qdtrack/losses/l2_loss.py
  function l2_loss (line 8) | def l2_loss(pred, target):
  class L2Loss (line 24) | class L2Loss(nn.Module):
    method __init__ (line 33) | def __init__(self,
    method forward (line 48) | def forward(self,
    method update_weight (line 75) | def update_weight(self, pred, target, weight, avg_factor):
    method random_choice (line 113) | def random_choice(gallery, num):

FILE: knet/video/qdtrack/losses/multipos_cross_entropy_loss.py
  function multi_pos_cross_entropy (line 6) | def multi_pos_cross_entropy(pred,
  class MultiPosCrossEntropyLoss (line 44) | class MultiPosCrossEntropyLoss(nn.Module):
    method __init__ (line 46) | def __init__(self, reduction='mean', loss_weight=1.0):
    method forward (line 51) | def forward(self,

FILE: knet/video/qdtrack/track/similarity.py
  function cal_similarity (line 5) | def cal_similarity(key_embeds,

FILE: knet/video/qdtrack/track/transforms.py
  function track2result (line 5) | def track2result(bboxes, labels, ids, num_classes):
  function restore_result (line 24) | def restore_result(result, return_ids=False):

FILE: knet/video/qdtrack/trackers/quasi_dense_embed_tracker.py
  class QuasiDenseEmbedTracker (line 9) | class QuasiDenseEmbedTracker(object):
    method __init__ (line 11) | def __init__(self,
    method empty (line 44) | def empty(self):
    method update_memo (line 47) | def update_memo(self, ids, bboxes, embeds, labels, frame_id):
    method memo (line 105) | def memo(self):
    method match (line 137) | def match(self, bboxes, labels, track_feats, frame_id, asso_tau=-1):

FILE: knet/video/qdtrack/trackers/tao_tracker.py
  class TaoTracker (line 19) | class TaoTracker(object):
    method __init__ (line 21) | def __init__(self,
    method reset (line 49) | def reset(self):
    method valid_ids (line 57) | def valid_ids(self):
    method empty (line 64) | def empty(self):
    method update_memo (line 67) | def update_memo(self, ids, bboxes, labels, embeds, frame_id):
    method memo (line 99) | def memo(self):
    method init_tracklets (line 116) | def init_tracklets(self, ids, obj_scores):
    method match (line 126) | def match(self,
  function random_color (line 330) | def random_color(seed):
  function imshow_tracklets (line 337) | def imshow_tracklets(img,

FILE: knet/video/track_heads.py
  class QueryTrackHead (line 16) | class QueryTrackHead(nn.Module):
    method __init__ (line 24) | def __init__(self,
    method init_weights (line 54) | def init_weights(self):
    method compute_comp_scores (line 59) | def compute_comp_scores(self, match_ll, bbox_scores, bbox_ious, label_...
    method forward (line 77) | def forward(self, x, ref_x, x_n, ref_x_n):
    method loss (line 111) | def loss(self,
    method get_targets (line 141) | def get_targets(self,
    method _get_target_single (line 163) | def _get_target_single(self, pos_inds, neg_inds, pos_mask, neg_mask, p...
  class TrackHeadWithROIAlign (line 182) | class TrackHeadWithROIAlign(nn.Module):
    method __init__ (line 190) | def __init__(self,
    method init_weights (line 231) | def init_weights(self):
    method compute_comp_scores (line 236) | def compute_comp_scores(self, match_ll, bbox_scores, bbox_ious, label_...
    method forward (line 254) | def forward(self, x, ref_x, mask_pred, ref_mask_pred, x_n, ref_x_n):
    method loss (line 312) | def loss(self,
    method get_targets (line 341) | def get_targets(self,
    method _get_target_single (line 363) | def _get_target_single(self, pos_inds, neg_inds, pos_mask, neg_mask, p...
  class QuasiDenseMaskEmbedHead (line 382) | class QuasiDenseMaskEmbedHead(nn.Module):
    method __init__ (line 384) | def __init__(self,
    method _add_conv_fc_branch (line 425) | def _add_conv_fc_branch(self, num_convs, num_fcs, in_channels):
    method init_weights (line 453) | def init_weights(self):
    method forward (line 461) | def forward(self, x):
    method get_track_targets (line 473) | def get_track_targets(self, gt_match_indices, key_sampling_results,
    method match (line 492) | def match(self, key_embeds, ref_embeds, key_sampling_results,
    method loss (line 516) | def loss(self, dists, cos_dists, targets, weights):
    method random_choice (line 535) | def random_choice(gallery, num):
  class QuasiDenseMaskEmbedHeadGTMask (line 553) | class QuasiDenseMaskEmbedHeadGTMask(nn.Module):
    method __init__ (line 555) | def __init__(self,
    method _add_conv_fc_branch (line 596) | def _add_conv_fc_branch(self, num_convs, num_fcs, in_channels):
    method init_weights (line 624) | def init_weights(self):
    method forward (line 632) | def forward(self, x):
    method get_track_targets (line 644) | def get_track_targets(self, gt_match_indices, key_sampling_results,
    method match (line 663) | def match(self, key_embeds, ref_embeds, key_sampling_results,
    method loss (line 686) | def loss(self, dists, cos_dists, targets, weights):
    method random_choice (line 705) | def random_choice(gallery, num):

FILE: knet/video/tracker.py
  class SimpleMaskTracker (line 14) | class SimpleMaskTracker(object):
    method __init__ (line 15) | def __init__(self, score_thresh, max_age=32):
    method reset_all (line 24) | def reset_all(self):
    method init_track (line 30) | def init_track(self, results):
    method step (line 53) | def step(self, output_results, track_results):

FILE: knet/video/util.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: knet_vis/det/kernel_head.py
  class ConvKernelHead (line 12) | class ConvKernelHead(nn.Module):
    method __init__ (line 14) | def __init__(self,
    method _init_layers (line 122) | def _init_layers(self):
    method init_weights (line 173) | def init_weights(self):
    method _decode_init_proposals (line 200) | def _decode_init_proposals(self, img, img_metas):
    method forward_train (line 266) | def forward_train(self,
    method loss (line 336) | def loss(self,
    method _get_target_single (line 427) | def _get_target_single(self, pos_inds, neg_inds, pos_mask, neg_mask,
    method get_targets (line 466) | def get_targets(self,
    method simple_test_rpn (line 504) | def simple_test_rpn(self, img, img_metas):
    method forward_dummy (line 508) | def forward_dummy(self, img, img_metas):

FILE: knet_vis/det/kernel_iter_head.py
  class KernelIterHead (line 13) | class KernelIterHead(BaseRoIHead):
    method __init__ (line 15) | def __init__(self,
    method init_bbox_head (line 76) | def init_bbox_head(self, mask_roi_extractor, mask_head):
    method init_assigner_sampler (line 85) | def init_assigner_sampler(self):
    method init_weights (line 97) | def init_weights(self):
    method init_mask_head (line 101) | def init_mask_head(self, mask_roi_extractor, mask_head):
    method _mask_forward (line 118) | def _mask_forward(self, stage, x, object_feats, mask_preds, img_metas):
    method forward_train (line 139) | def forward_train(self,
    method simple_test (line 231) | def simple_test(self,
    method aug_test (line 285) | def aug_test(self, features, proposal_list, img_metas, rescale=False):
    method forward_dummy (line 288) | def forward_dummy(self, x, proposal_boxes, proposal_feats, img_metas):
    method get_panoptic (line 303) | def get_panoptic(self, cls_scores, mask_preds, test_cfg, img_meta):
    method merge_stuff_thing (line 322) | def merge_stuff_thing(self,

FILE: knet_vis/det/kernel_update_head.py
  class KernelUpdateHead (line 20) | class KernelUpdateHead(nn.Module):
    method __init__ (line 22) | def __init__(self,
    method init_weights (line 154) | def init_weights(self):
    method forward (line 173) | def forward(self,
    method loss (line 281) | def loss(self,
    method _get_target_single (line 352) | def _get_target_single(self, pos_inds, neg_inds, pos_mask, neg_mask,
    method get_targets (line 407) | def get_targets(self,
    method rescale_masks (line 442) | def rescale_masks(self, masks_per_img, img_meta):
    method get_seg_masks (line 459) | def get_seg_masks(self, masks_per_img, labels_per_img, scores_per_img,
    method segm2result (line 468) | def segm2result(self, mask_preds, det_labels, cls_scores):
    method get_seg_masks_tracking (line 484) | def get_seg_masks_tracking(self, masks_per_img, labels_per_img, scores...

FILE: knet_vis/det/knet.py
  class KNet (line 11) | class KNet(TwoStageDetector):
    method __init__ (line 13) | def __init__(self,
    method forward_train (line 29) | def forward_train(self,
    method simple_test (line 118) | def simple_test(self, img, img_metas, rescale=False):
    method forward_dummy (line 133) | def forward_dummy(self, img):

FILE: knet_vis/det/mask_hungarian_assigner.py
  class DiceCost (line 15) | class DiceCost(object):
    method __init__ (line 34) | def __init__(self,
    method dice_loss (line 44) | def dice_loss(cls, input, target, eps=1e-3):
    method __call__ (line 56) | def __call__(self, mask_preds, gt_masks):
  class MaskCost (line 77) | class MaskCost(object):
    method __init__ (line 84) | def __init__(self, weight=1., pred_act=False, act_mode='sigmoid'):
    method __call__ (line 89) | def __call__(self, cls_pred, target):
  class MaskHungarianAssigner (line 114) | class MaskHungarianAssigner(BaseAssigner):
    method __init__ (line 142) | def __init__(self,
    method assign (line 157) | def assign(self,

FILE: knet_vis/det/mask_pseudo_sampler.py
  class MaskSamplingResult (line 7) | class MaskSamplingResult(SamplingResult):
    method __init__ (line 26) | def __init__(self, pos_inds, neg_inds, masks, gt_masks, assign_result,
    method masks (line 50) | def masks(self):
    method __nice__ (line 54) | def __nice__(self):
    method info (line 63) | def info(self):
  class MaskPseudoSampler (line 77) | class MaskPseudoSampler(BaseSampler):
    method __init__ (line 80) | def __init__(self, **kwargs):
    method _sample_pos (line 83) | def _sample_pos(self, **kwargs):
    method _sample_neg (line 87) | def _sample_neg(self, **kwargs):
    method sample (line 91) | def sample(self, assign_result, masks, gt_masks, **kwargs):

FILE: knet_vis/det/semantic_fpn_wrapper.py
  class SemanticFPNWrapper (line 10) | class SemanticFPNWrapper(nn.Module):
    method __init__ (line 25) | def __init__(self,
    method init_weights (line 172) | def init_weights(self):
    method generate_coord (line 179) | def generate_coord(self, input_feat):
    method forward (line 190) | def forward(self, inputs):

FILE: knet_vis/det/utils.py
  function sem2ins_masks (line 4) | def sem2ins_masks(gt_sem_seg,

FILE: knet_vis/kernel_updator.py
  class KernelUpdator (line 8) | class KernelUpdator(nn.Module):
    method __init__ (line 10) | def __init__(self,
    method forward (line 56) | def forward(self, update_feature, input_feature):

FILE: knet_vis/tracker/kernel_frame_head.py
  class ConvKernelHeadVolume (line 12) | class ConvKernelHeadVolume(nn.Module):
    method __init__ (line 13) | def __init__(self,
    method _init_layers (line 121) | def _init_layers(self):
    method init_weights (line 172) | def init_weights(self):
    method _decode_init_proposals (line 199) | def _decode_init_proposals(self, img, img_metas, ref_img_metas):
    method forward_train (line 267) | def forward_train(self,
    method loss (line 349) | def loss(self,
    method _get_target_single (line 440) | def _get_target_single(self, pos_inds, neg_inds, pos_mask, neg_mask,
    method get_targets (line 479) | def get_targets(self,
    method simple_test_rpn (line 516) | def simple_test_rpn(self, img, img_metas, ref_img_metas):
    method forward_dummy (line 520) | def forward_dummy(self, img, img_metas, ref_img_metas):

FILE: knet_vis/tracker/kernel_frame_iter_head.py
  class KernelFrameIterHeadVideo (line 14) | class KernelFrameIterHeadVideo(BaseRoIHead):
    method __init__ (line 15) | def __init__(self,
    method init_mask_head (line 82) | def init_mask_head(self, bbox_roi_extractor=None, mask_head=None):
    method init_assigner_sampler (line 92) | def init_assigner_sampler(self):
    method init_bbox_head (line 104) | def init_bbox_head(self, mask_roi_extractor, mask_head):
    method _mask_forward (line 113) | def _mask_forward(self, stage, x, object_feats, mask_preds):
    method _query_fusion (line 139) | def _query_fusion(self, obj_feats, num_imgs, num_frames):
    method _mask_init (line 164) | def _mask_init(self, object_feats, x_feats, num_imgs):
    method forward_train (line 181) | def forward_train(self,
    method simple_test (line 313) | def simple_test(self,
    method init_weights (line 377) | def init_weights(self):

FILE: knet_vis/tracker/kernel_head.py
  class ConvKernelHeadVideo (line 12) | class ConvKernelHeadVideo(nn.Module):
    method __init__ (line 13) | def __init__(self,
    method _init_layers (line 121) | def _init_layers(self):
    method init_weights (line 172) | def init_weights(self):
    method _decode_init_proposals (line 199) | def _decode_init_proposals(self, img, img_metas, ref_img_metas):
    method forward_train (line 267) | def forward_train(self,
    method loss (line 336) | def loss(self,
    method _get_target_single (line 427) | def _get_target_single(self, pos_inds, neg_inds, pos_mask, neg_mask,
    method get_targets (line 466) | def get_targets(self,
    method simple_test_rpn (line 503) | def simple_test_rpn(self, img, img_metas, ref_img_metas):
    method forward_dummy (line 507) | def forward_dummy(self, img, img_metas, ref_img_metas):

FILE: knet_vis/tracker/kernel_iter_head.py
  class KernelIterHeadVideo (line 14) | class KernelIterHeadVideo(BaseRoIHead):
    method __init__ (line 15) | def __init__(self,
    method init_bbox_head (line 75) | def init_bbox_head(self, mask_roi_extractor, mask_head):
    method init_assigner_sampler (line 84) | def init_assigner_sampler(self):
    method init_weights (line 96) | def init_weights(self):
    method init_mask_head (line 100) | def init_mask_head(self, mask_roi_extractor, mask_head):
    method _mask_forward (line 117) | def _mask_forward(self, stage, x, object_feats, mask_preds, img_metas=...
    method forward_train (line 138) | def forward_train(self,
    method simple_test (line 243) | def simple_test(self,
    method aug_test (line 315) | def aug_test(self, features, proposal_list, img_metas, rescale=False):
    method forward_dummy (line 318) | def forward_dummy(self, x, proposal_boxes, proposal_feats, img_metas):
    method get_panoptic (line 333) | def get_panoptic(self, cls_scores, mask_preds, test_cfg, img_meta):
    method merge_stuff_thing (line 352) | def merge_stuff_thing(self,

FILE: knet_vis/tracker/kernel_update_head.py
  class KernelUpdateHeadVideo (line 20) | class KernelUpdateHeadVideo(nn.Module):
    method __init__ (line 22) | def __init__(self,
    method init_weights (line 190) | def init_weights(self):
    method forward (line 209) | def forward(self,
    method loss (line 377) | def loss(self,
    method _get_target_single (line 449) | def _get_target_single(self, pos_inds, neg_inds, pos_mask, neg_mask,
    method get_targets (line 504) | def get_targets(self,
    method rescale_masks (line 539) | def rescale_masks(self, masks_per_img, img_meta):
    method get_seg_masks (line 556) | def get_seg_masks(self, masks_per_img, labels_per_img, scores_per_img,
    method segm2result (line 565) | def segm2result(self, mask_preds, det_labels, cls_scores):
    method get_seg_masks_tracking (line 581) | def get_seg_masks_tracking(self, masks_per_img, labels_per_img, scores...

FILE: knet_vis/tracker/mask_hungarian_assigner.py
  class MaskHungarianAssignerVideo (line 17) | class MaskHungarianAssignerVideo(BaseAssigner):
    method __init__ (line 45) | def __init__(self,
    method assign (line 60) | def assign(self,

FILE: knet_vis/tracker/positional_encoding.py
  class PositionEmbeddingSine3D (line 15) | class PositionEmbeddingSine3D(BaseModule):
    method __init__ (line 21) | def __init__(self, num_feats=64, temperature=10000, normalize=False, s...
    method forward (line 32) | def forward(self, x, mask=None):

FILE: knet_vis/tracker/semantic_fpn_wrapper3D.py
  class SemanticFPNWrapper3D (line 10) | class SemanticFPNWrapper3D(nn.Module):
    method __init__ (line 25) | def __init__(self,
    method init_weights (line 172) | def init_weights(self):
    method generate_coord (line 179) | def generate_coord(self, input_feat):
    method forward (line 190) | def forward(self, inputs, num_imgs, num_frames):

FILE: knet_vis/tracker/track.py
  class KNetTrack (line 16) | class KNetTrack(TwoStageDetector):
    method __init__ (line 18) | def __init__(self,
    method gt_transform (line 52) | def gt_transform(self, img_metas, gt_masks, gt_labels, gt_semantic_seg):
    method ref_gt_transform (line 106) | def ref_gt_transform(self, ref_img_metas, ref_gt_masks, ref_gt_labels,...
    method forward_train (line 142) | def forward_train(self,
    method forward_test (line 243) | def forward_test(self, imgs, img_metas, **kwargs):
    method simple_test (line 289) | def simple_test(self, imgs, img_metas, **kwargs):
    method forward_dummy (line 350) | def forward_dummy(self, img):
    method init_weights (line 369) | def init_weights(self):

FILE: mmtrack/datasets/coco_video_dataset.py
  class CocoVideoDataset (line 14) | class CocoVideoDataset(CocoDataset):
    method __init__ (line 28) | def __init__(self,
    method load_annotations (line 51) | def load_annotations(self, ann_file):
    method load_video_anns (line 66) | def load_video_anns(self, ann_file):
    method key_img_sampling (line 101) | def key_img_sampling(self, img_ids, interval=1):
    method ref_img_sampling (line 105) | def ref_img_sampling(self,
    method get_ann_info (line 239) | def get_ann_info(self, img_info):
    method prepare_results (line 253) | def prepare_results(self, img_info):
    method prepare_data (line 266) | def prepare_data(self, idx):
    method prepare_train_img (line 292) | def prepare_train_img(self, idx):
    method prepare_test_img (line 304) | def prepare_test_img(self, idx):
    method _parse_ann_info (line 316) | def _parse_ann_info(self, img_info, ann_info):
    method evaluate (line 385) | def evaluate(self,
    method __repr__ (line 475) | def __repr__(self):

FILE: mmtrack/datasets/parsers/coco_video_parser.py
  class CocoVID (line 9) | class CocoVID(COCO):
    method __init__ (line 18) | def __init__(self, annotation_file=None, load_img_as_vid=False):
    method convert_img_to_vid (line 23) | def convert_img_to_vid(self, dataset):
    method createIndex (line 39) | def createIndex(self, use_ext=False):
    method get_vid_ids (line 91) | def get_vid_ids(self, vidIds=[]):
    method get_img_ids_from_vid (line 108) | def get_img_ids_from_vid(self, vidId):
    method get_ins_ids_from_vid (line 121) | def get_ins_ids_from_vid(self, vidId):
    method get_img_ids_from_ins_id (line 130) | def get_img_ids_from_ins_id(self, insId):
    method load_vids (line 139) | def load_vids(self, ids=[]):

FILE: mmtrack/datasets/youtube_vis_dataset.py
  function results2outs (line 15) | def results2outs(bbox_results=None,
  class YouTubeVISDataset (line 70) | class YouTubeVISDataset(CocoVideoDataset):
    method __init__ (line 92) | def __init__(self, dataset_version, *args, **kwargs):
    method set_dataset_classes (line 97) | def set_dataset_classes(cls, dataset_version):
    method format_results (line 106) | def format_results(self,

FILE: mmtrack/pipelines/formatting.py
  class ConcatVideoReferences (line 9) | class ConcatVideoReferences(object):
    method __call__ (line 27) | def __call__(self, results):
  class ConcatVideos (line 75) | class ConcatVideos(object):
    method __call__ (line 93) | def __call__(self, results):
  class MultiImagesToTensor (line 149) | class MultiImagesToTensor(object):
    method __init__ (line 161) | def __init__(self, ref_prefix='ref'):
    method __call__ (line 164) | def __call__(self, results):
    method images_to_tensor (line 192) | def images_to_tensor(self, results):
  class SeqDefaultFormatBundle (line 211) | class SeqDefaultFormatBundle(object):
    method __init__ (line 236) | def __init__(self, ref_prefix='ref'):
    method __call__ (line 239) | def __call__(self, results):
    method default_format_bundle (line 273) | def default_format_bundle(self, results):
    method __repr__ (line 311) | def __repr__(self):
  class VideoCollect (line 316) | class VideoCollect(object):
    method __init__ (line 330) | def __init__(self,
    method __call__ (line 354) | def __call__(self, results):
    method _collect_meta_keys (line 391) | def _collect_meta_keys(self, results):
    method _add_default_meta_keys (line 405) | def _add_default_meta_keys(self, results):
  class ToList (line 432) | class ToList(object):
    method __call__ (line 442) | def __call__(self, results):
  class ReIDFormatBundle (line 450) | class ReIDFormatBundle(object):
    method __init__ (line 461) | def __init__(self, *args, **kwargs):
    method __call__ (line 464) | def __call__(self, results):
    method reid_format_bundle (line 492) | def reid_format_bundle(self, results):
  class ImageToTensorWithRef (line 519) | class ImageToTensorWithRef(object):
    method __init__ (line 521) | def __init__(self, keys):
    method __call__ (line 524) | def __call__(self, results):
    method __repr__ (line 542) | def __repr__(self):
  class LabelConsistentChecker (line 546) | class LabelConsistentChecker:
    method __init__ (line 549) | def __init__(self, num_frames=5):
    method __call__ (line 552) | def __call__(self, results):
  class MM2CLIP (line 572) | class MM2CLIP:
    method __init__ (line 575) | def __init__(self, num_frames=5):
    method __call__ (line 578) | def __call__(self, results):

FILE: mmtrack/pipelines/loading.py
  class LoadMultiImagesFromFile (line 12) | class LoadMultiImagesFromFile(LoadImageFromFile):
    method __init__ (line 18) | def __init__(self, *args, **kwargs):
    method __call__ (line 21) | def __call__(self, results):
  class SeqLoadAnnotations (line 39) | class SeqLoadAnnotations(LoadAnnotations):
    method __init__ (line 47) | def __init__(self, with_track=False, *args, **kwargs):
    method _load_track (line 51) | def _load_track(self, results):
    method __call__ (line 63) | def __call__(self, results):
  class LoadRefImageFromFile (line 85) | class LoadRefImageFromFile(object):
    method __init__ (line 91) | def __init__(self, sample=True, to_float32=False):
    method __call__ (line 95) | def __call__(self, results):
    method __repr__ (line 123) | def __repr__(self):
  function bitmasks2bboxes (line 128) | def bitmasks2bboxes(bitmasks):
  class LoadAnnotationsInstanceMasks (line 142) | class LoadAnnotationsInstanceMasks:
    method __init__ (line 143) | def __init__(self,
    method _load_masks (line 156) | def _load_masks(self, results):
    method _load_semantic_seg (line 193) | def _load_semantic_seg(self, results):
    method __call__ (line 206) | def __call__(self, results):
    method __repr__ (line 224) | def __repr__(self):

FILE: mmtrack/pipelines/test_time_aug.py
  class MultiScaleFlipAugVideo (line 11) | class MultiScaleFlipAugVideo:
    method __init__ (line 47) | def __init__(self,
    method __call__ (line 78) | def __call__(self, results):
    method __repr__ (line 110) | def __repr__(self):

FILE: mmtrack/pipelines/transforms.py
  class SeqColorAug (line 10) | class SeqColorAug(object):
    method __init__ (line 21) | def __init__(self,
    method __call__ (line 29) | def __call__(self, results):
  class SeqBlurAug (line 56) | class SeqBlurAug(object):
    method __init__ (line 63) | def __init__(self, prob=[0.0, 0.2]):
    method __call__ (line 66) | def __call__(self, results):
  class SeqResize (line 96) | class SeqResize(Resize):
    method __init__ (line 105) | def __init__(self, share_params=True, *args, **kwargs):
    method __call__ (line 109) | def __call__(self, results):
  class SeqNormalize (line 133) | class SeqNormalize(Normalize):
    method __init__ (line 139) | def __init__(self, *args, **kwargs):
    method __call__ (line 142) | def __call__(self, results):
  class SeqRandomFlip (line 161) | class SeqRandomFlip(RandomFlip):
    method __init__ (line 170) | def __init__(self, share_params, *args, **kwargs):
    method __call__ (line 174) | def __call__(self, results):
  class SeqPad (line 218) | class SeqPad(Pad):
    method __init__ (line 224) | def __init__(self, *args, **kwargs):
    method __call__ (line 227) | def __call__(self, results):
  class SeqRandomCrop (line 246) | class SeqRandomCrop(object):
    method __init__ (line 270) | def __init__(self,
    method get_offsets (line 293) | def get_offsets(self, img):
    method random_crop (line 301) | def random_crop(self, results, offsets=None):
    method __call__ (line 364) | def __call__(self, results):
    method check_match (line 391) | def check_match(self, ref_results, results):
  class SeqPhotoMetricDistortion (line 400) | class SeqPhotoMetricDistortion(object):
    method __init__ (line 419) | def __init__(self,
    method get_params (line 431) | def get_params(self):
    method photo_metric_distortion (line 467) | def photo_metric_distortion(self, results, params=None):
    method __call__ (line 524) | def __call__(self, results):
    method __repr__ (line 543) | def __repr__(self):
  class ResizeWithRef (line 555) | class ResizeWithRef(object):
    method __init__ (line 580) | def __init__(self,
    method random_select (line 606) | def random_select(img_scales):
    method random_sample (line 613) | def random_sample(img_scales):
    method random_sample_ratio (line 627) | def random_sample_ratio(img_scale, ratio_range):
    method _random_scale (line 635) | def _random_scale(self, results):
    method _resize_img (line 651) | def _resize_img(self, results):
    method _resize_bboxes (line 668) | def _resize_bboxes(self, results):
    method _resize_masks (line 680) | def _resize_masks(self, results):
    method __call__ (line 703) | def __call__(self, results):
    method __repr__ (line 712) | def __repr__(self):
  class RandomFlipWithRef (line 723) | class RandomFlipWithRef(object):
    method __init__ (line 734) | def __init__(self, flip_ratio=None):
    method bbox_flip (line 739) | def bbox_flip(self, bboxes, img_shape):
    method __call__ (line 753) | def __call__(self, results):
    method __repr__ (line 776) | def __repr__(self):
  class PadWithRef (line 782) | class PadWithRef(object):
    method __init__ (line 794) | def __init__(self, size=None, size_divisor=None, pad_val=0):
    method _pad_img (line 802) | def _pad_img(self, results):
    method _pad_masks (line 815) | def _pad_masks(self, results):
    method __call__ (line 826) | def __call__(self, results):
    method __repr__ (line 831) | def __repr__(self):
  class NormalizeWithRef (line 839) | class NormalizeWithRef(object):
    method __init__ (line 849) | def __init__(self, mean, std, to_rgb=True):
    method __call__ (line 854) | def __call__(self, results):
    method __repr__ (line 864) | def __repr__(self):
  class RandomCropWithRef (line 872) | class RandomCropWithRef(object):
    method __init__ (line 879) | def __init__(self, crop_size):
    method __call__ (line 882) | def __call__(self, results):
    method __repr__ (line 948) | def __repr__(self):
  class PadFutureMMDet (line 954) | class PadFutureMMDet:
    method __init__ (line 968) | def __init__(self,
    method _pad_img (line 994) | def _pad_img(self, results):
    method _pad_masks (line 1012) | def _pad_masks(self, results):
    method _pad_seg (line 1019) | def _pad_seg(self, results):
    method __call__ (line 1027) | def __call__(self, results):
    method __repr__ (line 1039) | def __repr__(self):
  class KNetInsAdapter (line 1049) | class KNetInsAdapter:
    method __init__ (line 1054) | def __init__(self, stuff_nums=11):
    method __call__ (line 1057) | def __call__(self, results):
  class KNetInsAdapterCherryPick (line 1069) | class KNetInsAdapterCherryPick:
    method __init__ (line 1074) | def __init__(self, stuff_nums=11, cherry=(11, 13)):
    method __call__ (line 1078) | def __call__(self, results):

FILE: mmtrack/transform.py
  function outs2results (line 6) | def outs2results(bboxes=None,

FILE: scripts/kitti_step_prepare.py
  function build_panoptic (line 14) | def build_panoptic(seq_id, input_dir, output_dir):
  function build_img (line 29) | def build_img(seq_id, input_dir, output_dir):

FILE: scripts/visualizer.py
  function sha256num (line 30) | def sha256num(num):
  function id2rgb (line 36) | def id2rgb(id_map):
  function cityscapes_cat2rgb (line 52) | def cityscapes_cat2rgb(cat_map):
  function trackmap2rgb (line 62) | def trackmap2rgb(track_map):
  function draw_bbox_on_img (line 72) | def draw_bbox_on_img(vis_img, bboxes):

FILE: swin/DetectRS.py
  class Bottleneck (line 16) | class Bottleneck(_Bottleneck):
    method __init__ (line 34) | def __init__(self,
    method rfp_forward (line 72) | def rfp_forward(self, x, rfp_feat):
  class ResLayer (line 119) | class ResLayer(Sequential):
    method __init__ (line 143) | def __init__(self,
  class DetectoRS_ResNet_Custom (line 209) | class DetectoRS_ResNet_Custom(ResNet):
    method __init__ (line 230) | def __init__(self,
    method init_weights (line 283) | def init_weights(self):
    method make_res_layer (line 310) | def make_res_layer(self, **kwargs):
    method forward (line 314) | def forward(self, x):
    method rfp_forward (line 321) | def rfp_forward(self, x, rfp_feats):

FILE: swin/ckpt_convert.py
  function pvt_convert (line 12) | def pvt_convert(ckpt):
  function swin_converter (line 85) | def swin_converter(ckpt):

FILE: swin/mix_transformer.py
  class Mlp (line 21) | class Mlp(nn.Module):
    method __init__ (line 22) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method _init_weights (line 34) | def _init_weights(self, m):
    method forward (line 49) | def forward(self, x, H, W):
  class Attention (line 59) | class Attention(nn.Module):
    method __init__ (line 60) | def __init__(self, dim, num_heads=8, qkv_bias=False, qk_scale=None, at...
    method _init_weights (line 82) | def _init_weights(self, m):
    method forward (line 97) | def forward(self, x, H, W):
  class Block (line 121) | class Block(nn.Module):
    method __init__ (line 123) | def __init__(self, dim, num_heads, mlp_ratio=4., qkv_bias=False, qk_sc...
    method _init_weights (line 139) | def _init_weights(self, m):
    method forward (line 154) | def forward(self, x, H, W):
  class OverlapPatchEmbed (line 161) | class OverlapPatchEmbed(nn.Module):
    method __init__ (line 165) | def __init__(self, img_size=224, patch_size=7, stride=4, in_chans=3, e...
    method _init_weights (line 180) | def _init_weights(self, m):
    method forward (line 195) | def forward(self, x):
  class MixVisionTransformer (line 204) | class MixVisionTransformer(BaseModule):
    method __init__ (line 205) | def __init__(self, img_size=224, patch_size=16, in_chans=3, num_classe...
    method _init_weights (line 262) | def _init_weights(self, m):
    method reset_drop_path (line 282) | def reset_drop_path(self, drop_path_rate):
    method freeze_patch_emb (line 300) | def freeze_patch_emb(self):
    method no_weight_decay (line 304) | def no_weight_decay(self):
    method get_classifier (line 307) | def get_classifier(self):
    method reset_classifier (line 310) | def reset_classifier(self, num_classes, global_pool=''):
    method forward_features (line 314) | def forward_features(self, x):
    method forward (line 352) | def forward(self, x):
  class DWConv (line 359) | class DWConv(nn.Module):
    method __init__ (line 360) | def __init__(self, dim=768):
    method forward (line 364) | def forward(self, x, H, W):
  class mit_b0 (line 374) | class mit_b0(MixVisionTransformer):
    method __init__ (line 375) | def __init__(self, **kwargs):
  class mit_b1 (line 383) | class mit_b1(MixVisionTransformer):
    method __init__ (line 384) | def __init__(self, **kwargs):
  class mit_b2 (line 392) | class mit_b2(MixVisionTransformer):
    method __init__ (line 393) | def __init__(self, **kwargs):
  class mit_b3 (line 401) | class mit_b3(MixVisionTransformer):
    method __init__ (line 402) | def __init__(self, **kwargs):
  class mit_b4 (line 410) | class mit_b4(MixVisionTransformer):
    method __init__ (line 411) | def __init__(self, **kwargs):
  class mit_b5 (line 419) | class mit_b5(MixVisionTransformer):
    method __init__ (line 420) | def __init__(self, **kwargs):
  class ResNetV1c (line 428) | class ResNetV1c(ResNet):
    method __init__ (line 437) | def __init__(self, **kwargs):

FILE: swin/swin_checkpoint.py
  function _get_mmcv_home (line 29) | def _get_mmcv_home():
  function load_state_dict (line 40) | def load_state_dict(module, state_dict, strict=False, logger=None):
  function load_url_dist (line 107) | def load_url_dist(url, model_dir=None):
  function load_pavimodel_dist (line 121) | def load_pavimodel_dist(model_path, map_location=None):
  function load_fileclient_dist (line 149) | def load_fileclient_dist(filename, backend, map_location):
  function get_torchvision_models (line 170) | def get_torchvision_models():
  function get_external_models (line 182) | def get_external_models():
  function get_mmcls_models (line 196) | def get_mmcls_models():
  function get_deprecated_model_names (line 203) | def get_deprecated_model_names():
  function _process_mmcls_checkpoint (line 212) | def _process_mmcls_checkpoint(checkpoint):
  function _load_checkpoint (line 223) | def _load_checkpoint(filename, map_location=None):
  function load_checkpoint (line 283) | def load_checkpoint(model,
  function weights_to_cpu (line 356) | def weights_to_cpu(state_dict):
  function _save_to_state_dict (line 370) | def _save_to_state_dict(module, destination, prefix, keep_vars):
  function get_state_dict (line 389) | def get_state_dict(module, destination=None, prefix='', keep_vars=False):
  function save_checkpoint (line 430) | def save_checkpoint(model, filename, optimizer=None, meta=None):

FILE: swin/swin_transformer.py
  class Mlp (line 20) | class Mlp(nn.Module):
    method __init__ (line 23) | def __init__(self,
    method forward (line 37) | def forward(self, x):
  function window_partition (line 46) | def window_partition(x, window_size):
  function window_reverse (line 62) | def window_reverse(windows, window_size, H, W):
  class WindowAttention (line 79) | class WindowAttention(nn.Module):
    method __init__ (line 94) | def __init__(self,
    method forward (line 141) | def forward(self, x, mask=None):
  class SwinTransformerBlock (line 183) | class SwinTransformerBlock(nn.Module):
    method __init__ (line 201) | def __init__(self,
    method forward (line 245) | def forward(self, x, mask_matrix):
  class PatchMerging (line 314) | class PatchMerging(nn.Module):
    method __init__ (line 321) | def __init__(self, dim, norm_layer=nn.LayerNorm):
    method forward (line 327) | def forward(self, x, H, W):
  class BasicLayer (line 357) | class BasicLayer(nn.Module):
    method __init__ (line 376) | def __init__(self,
    method forward (line 419) | def forward(self, x, H, W):
  class PatchEmbed (line 466) | class PatchEmbed(nn.Module):
    method __init__ (line 475) | def __init__(self,
    method forward (line 494) | def forward(self, x):
  class SwinTransformerDIY (line 516) | class SwinTransformerDIY(nn.Module):
    method __init__ (line 544) | def __init__(self,
    method _freeze_stages (line 637) | def _freeze_stages(self):
    method init_weights (line 654) | def init_weights(self, pretrained=None):
    method forward (line 682) | def forward(self, x):
    method train (line 716) | def train(self, mode=True):

FILE: swin/swin_transformer_rfp.py
  class WindowMSA (line 20) | class WindowMSA(BaseModule):
    method __init__ (line 38) | def __init__(self,
    method init_weights (line 74) | def init_weights(self):
    method forward (line 77) | def forward(self, x, mask=None):
    method double_step_seq (line 117) | def double_step_seq(step1, len1, step2, len2):
  class ShiftWindowMSA (line 123) | class ShiftWindowMSA(BaseModule):
    method __init__ (line 145) | def __init__(self,
    method forward (line 174) | def forward(self, query, hw_shape):
    method window_reverse (line 250) | def window_reverse(self, windows, H, W):
    method window_partition (line 266) | def window_partition(self, x):
  class SwinBlock (line 282) | class SwinBlock(BaseModule):
    method __init__ (line 307) | def __init__(self,
    method forward (line 352) | def forward(self, x, hw_shape):
  class SwinBlockSequence (line 375) | class SwinBlockSequence(BaseModule):
    method __init__ (line 403) | def __init__(self,
    method forward (line 448) | def forward(self, x, hw_shape):
  class SwinTransformer (line 459) | class SwinTransformer(BaseModule):
    method __init__ (line 514) | def __init__(self,
    method train (line 633) | def train(self, mode=True):
    method _freeze_stages (line 638) | def _freeze_stages(self):
    method init_weights (line 660) | def init_weights(self):
    method forward (line 739) | def forward(self, x):
  class SwinRFPLayer (line 760) | class SwinRFPLayer(BaseModule):
    method __init__ (line 788) | def __init__(self,
    method forward (line 846) | def forward(self, x, hw_shape):
    method rfp_forward (line 856) | def rfp_forward(self, x, hw_shape, rfp_feat):
  class SwinTransformerRFP (line 874) | class SwinTransformerRFP(SwinTransformer):
    method __init__ (line 875) | def __init__(
    method forward (line 972) | def forward(self, x):
    method rfp_forward (line 979) | def rfp_forward(self, x, rfp_feats):

FILE: swin/transformer.py
  function nlc_to_nchw (line 32) | def nlc_to_nchw(x, hw_shape):
  function nchw_to_nlc (line 47) | def nchw_to_nlc(x):
  class AdaptivePadding (line 58) | class AdaptivePadding(nn.Module):
    method __init__ (line 88) | def __init__(self, kernel_size=1, stride=1, dilation=1, padding='corne...
    method get_pad_shape (line 104) | def get_pad_shape(self, input_shape):
    method forward (line 116) | def forward(self, x):
  class PatchEmbed (line 129) | class PatchEmbed(BaseModule):
    method __init__ (line 155) | def __init__(
    method forward (line 229) | def forward(self, x):
  class PatchMerging (line 251) | class PatchMerging(BaseModule):
    method __init__ (line 280) | def __init__(self,
    method forward (line 329) | def forward(self, x, input_size):
  function inverse_sigmoid (line 375) | def inverse_sigmoid(x, eps=1e-5):

FILE: tools/dataset/cityscapes_instance_idmap.py
  function convert_json_to_label (line 9) | def convert_json_to_label(json_file):
  function parse_args (line 14) | def parse_args():
  function main (line 26) | def main():

FILE: tools/dataset/youtubevis2coco.py
  function parse_args (line 11) | def parse_args():
  function convert_vis (line 32) | def convert_vis(ann_dir, save_dir, dataset_version, mode='train'):
  function main (line 143) | def main():

FILE: tools/eval_dstq.py
  function parse_args (line 15) | def parse_args():
  function updater (line 29) | def updater(pred_ins_name,
  function eval_dstq (line 63) | def eval_dstq(result_dir, gt_dir, seq_ids, with_depth=True):

FILE: tools/eval_dstq_step.py
  function parse_args (line 15) | def parse_args():
  function updater (line 29) | def updater(pred_ins_name,
  function eval_dstq (line 63) | def eval_dstq(result_dir, gt_dir, seq_ids, with_depth=True):

FILE: tools/eval_dstq_vipseg.py
  function vip2hb (line 280) | def vip2hb(pan_map):
  function parse_args (line 301) | def parse_args():
  function updater (line 315) | def updater(pred_ins_name,
  function eval_dstq (line 351) | def eval_dstq(result_dir, gt_dir, with_depth=True):

FILE: tools/eval_dvpq_step.py
  function vpq_eval (line 21) | def vpq_eval(element):
  function eval (line 100) | def eval(element):
  function main (line 144) | def main():

FILE: tools/eval_dvpq_vipseg.py
  function vip2hb (line 275) | def vip2hb(pan_map):
  function parse_args (line 296) | def parse_args():
  function vpq_eval (line 310) | def vpq_eval(element):
  function read_to_eval (line 389) | def read_to_eval(element):
  function eval_dvpq (line 412) | def eval_dvpq(result_dir, gt_dir, split='val', k=1, with_depth=True):

FILE: tools/flops_counter.py
  function get_model_complexity_info (line 19) | def get_model_complexity_info(model, input_res,
  function flops_to_string (line 59) | def flops_to_string(flops, units='GMac', precision=2):
  function params_to_string (line 80) | def params_to_string(params_num, units=None, precision=2):
  function accumulate_flops (line 97) | def accumulate_flops(self):
  function print_model_with_flops (line 107) | def print_model_with_flops(model, total_flops, total_params, units='GMac',
  function get_model_parameters_number (line 153) | def get_model_parameters_number(model):
  function add_flops_counting_methods (line 158) | def add_flops_counting_methods(net_main_module):
  function compute_average_flops_cost (line 172) | def compute_average_flops_cost(self):
  function start_flops_count (line 192) | def start_flops_count(self, **kwargs):
  function stop_flops_count (line 228) | def stop_flops_count(self):
  function reset_flops_count (line 239) | def reset_flops_count(self):
  function empty_flops_counter_hook (line 250) | def empty_flops_counter_hook(module, input, output):
  function upsample_flops_counter_hook (line 254) | def upsample_flops_counter_hook(module, input, output):
  function relu_flops_counter_hook (line 263) | def relu_flops_counter_hook(module, input, output):
  function linear_flops_counter_hook (line 268) | def linear_flops_counter_hook(module, input, output):
  function pool_flops_counter_hook (line 276) | def pool_flops_counter_hook(module, input, output):
  function bn_flops_counter_hook (line 281) | def bn_flops_counter_hook(module, input, output):
  function conv_flops_counter_hook (line 290) | def conv_flops_counter_hook(conv_module, input, output):
  function batch_counter_hook (line 321) | def batch_counter_hook(module, input, output):
  function rnn_flops (line 334) | def rnn_flops(flops, rnn_module, w_ih, w_hh, input_size):
  function rnn_flops_counter_hook (line 359) | def rnn_flops_counter_hook(rnn_module, input, output):
  function rnn_cell_flops_counter_hook (line 392) | def rnn_cell_flops_counter_hook(rnn_cell_module, input, output):
  function ffn_hook (line 408) | def ffn_hook(module, input, output):
  function multihead_attention_counter_hook (line 422) | def multihead_attention_counter_hook(multihead_attention_module, input, ...
  function add_batch_counter_variables_or_reset (line 467) | def add_batch_counter_variables_or_reset(module):
  function add_batch_counter_hook_function (line 472) | def add_batch_counter_hook_function(module):
  function remove_batch_counter_hook_function (line 480) | def remove_batch_counter_hook_function(module):
  function add_flops_counter_variable_or_reset (line 486) | def add_flops_counter_variable_or_reset(module):
  function norm_flops_counter_hook (line 498) | def norm_flops_counter_hook(module, input, output):
  function is_supported_instance (line 573) | def is_supported_instance(module):
  function remove_flops_counter_hook_function (line 579) | def remove_flops_counter_hook_function(module):

FILE: tools/get_flops.py
  function parse_args (line 17) | def parse_args():
  function main (line 46) | def main():

FILE: tools/test.py
  function parse_args (line 19) | def parse_args():
  function main (line 101) | def main():

FILE: tools/test_dvps.py
  function single_gpu_test (line 22) | def single_gpu_test(model,
  function parse_args (line 79) | def parse_args():
  function main (line 181) | def main():

FILE: tools/test_step.py
  function single_gpu_test (line 24) | def single_gpu_test(model,
  function parse_args (line 78) | def parse_args():
  function main (line 170) | def main():

FILE: tools/test_vps.py
  function single_gpu_test (line 22) | def single_gpu_test(model,
  function parse_args (line 69) | def parse_args():
  function main (line 171) | def main():

FILE: tools/train.py
  function parse_args (line 23) | def parse_args():
  function main (line 94) | def main():

FILE: tools/utils/DSTQ.py
  class DSTQuality (line 9) | class DSTQuality(STQuality):
    method __init__ (line 10) | def __init__(
    method update_state (line 38) | def update_state(
    method result (line 78) | def result(self):
    method reset_states (line 145) | def reset_states(self):

FILE: tools/utils/STQ.py
  function _update_dict_stats (line 31) | def _update_dict_stats(stat_dict: MutableMapping[int, np.ndarray],
  class STQuality (line 42) | class STQuality(object):
    method __init__ (line 62) | def __init__(self, num_classes: int, things_list: Sequence[int],
    method get_semantic (line 102) | def get_semantic(self, y: np.ndarray) -> np.ndarray:
    method update_state (line 106) | def update_state(self, y_true: np.ndarray, y_pred: np.ndarray, sequenc...
    method result (line 190) | def result(self) -> Mapping[Text, Any]:
    method reset_states (line 285) | def reset_states(self):

FILE: tools/utils/cityscapesvps_eval.py
  class CityscapesVps (line 14) | class CityscapesVps(Dataset):
    method __init__ (line 16) | def __init__(self):
    method _save_image_single_core (line 24) | def _save_image_single_core(self, proc_id, images_set, names_set, colo...
    method inference_panoptic_video (line 40) | def inference_panoptic_video(self, pred_pans_2ch, output_dir,
    method converter_2ch_track_core (line 111) | def converter_2ch_track_core(self, proc_id, pan_2ch_set, color_generat...

FILE: tools/visualization.py
  function single_gpu_test (line 22) | def single_gpu_test(model,
  function parse_args (line 44) | def parse_args():
  function main (line 126) | def main():

FILE: tools_vis/apis/test.py
  function single_gpu_test (line 18) | def single_gpu_test(model,
  function multi_gpu_test (line 48) | def multi_gpu_test(model, data_loader, tmpdir=None, gpu_collect=False):
  function collect_results_cpu (line 99) | def collect_results_cpu(result_part, size, tmpdir=None):
  function collect_results_gpu (line 142) | def collect_results_gpu(result_part, size):

FILE: tools_vis/test.py
  function parse_args (line 23) | def parse_args():
  function main (line 114) | def main():

FILE: tools_vis/test_whole_video.py
  function parse_args (line 23) | def parse_args():
  function main (line 114) | def main():

FILE: unitrack/basetrack.py
  class TrackState (line 10) | class TrackState(object):
  class BaseTrack (line 17) | class BaseTrack(object):
    method end_frame (line 36) | def end_frame(self):
    method next_id (line 40) | def next_id():
    method activate (line 44) | def activate(self, *args):
    method predict (line 47) | def predict(self):
    method update (line 50) | def update(self, *args, **kwargs):
    method mark_lost (line 53) | def mark_lost(self):
    method mark_removed (line 56) | def mark_removed(self):
  class STrack (line 60) | class STrack(BaseTrack):
    method __init__ (line 63) | def __init__(self, tlwh, score, temp_feat, buffer_size=30,
    method update_features (line 85) | def update_features(self, feat):
    method predict (line 95) | def predict(self):
    method multi_predict (line 102) | def multi_predict(stracks):
    method activate (line 115) | def activate(self, kalman_filter, frame_id):
    method re_activate (line 129) | def re_activate(self, new_track, frame_id, new_id=False, update_featur...
    method update (line 148) | def update(self, new_track, frame_id, update_feature=True):
    method tlwh (line 182) | def tlwh(self):
    method tlbr (line 194) | def tlbr(self):
    method to_xyah (line 203) | def to_xyah(self):
    method __repr__ (line 207) | def __repr__(self):
  function joint_stracks (line 211) | def joint_stracks(tlista, tlistb):
  function sub_stracks (line 225) | def sub_stracks(tlista, tlistb):
  function remove_duplicate_stracks (line 236) | def remove_duplicate_stracks(stracksa, stracksb, ioudist=0.15):

FILE: unitrack/box.py
  class BoxAssociationTracker (line 16) | class BoxAssociationTracker(AssociationTracker):
    method __init__ (line 17) | def __init__(self, opt):
    method extract_emb (line 20) | def extract_emb(self, img, obs):
    method prepare_obs (line 29) | def prepare_obs(self, img, img0, obs, embs=None):

FILE: unitrack/core/association/matching.py
  function merge_matches (line 12) | def merge_matches(m1, m2, shape):
  function linear_assignment (line 29) | def linear_assignment(cost_matrix, thresh):
  function ious (line 43) | def ious(atlbrs, btlbrs):
  function iou_distance (line 63) | def iou_distance(atracks, btracks):
  function embedding_distance (line 83) | def embedding_distance(tracks, detections, metric='cosine'):
  function fuse_motion (line 100) | def fuse_motion(kf, cost_matrix, tracks, detections, only_position=False...
  function center_emb_distance (line 115) | def center_emb_distance(tracks, detections, metric='cosine'):
  function recons_distance (line 134) | def recons_distance(tracks, detections, tmp=100):
  function get_track_feat (line 174) | def get_track_feat(tracks, feat_flag='curr'):
  function reconsdot_distance (line 194) | def reconsdot_distance(tracks, detections, tmp=100):
  function category_gate (line 241) | def category_gate(cost_matrix, tracks, detections):

FILE: unitrack/core/motion/kalman_filter.py
  class KalmanFilter (line 23) | class KalmanFilter(object):
    method __init__ (line 40) | def __init__(self):
    method initiate (line 55) | def initiate(self, measurement):
    method predict (line 88) | def predict(self, mean, covariance):
    method project (line 125) | def project(self, mean, covariance):
    method multi_predict (line 154) | def multi_predict(self, mean, covariance):
    method update (line 196) | def update(self, mean, covariance, measurement):
    method gating_distance (line 230) | def gating_distance(self, mean, covariance, measurements,

FILE: unitrack/core/propagation/__init__.py
  function propagate (line 16) | def propagate(temp_feats, obs, img, model, format='box'):

FILE: unitrack/core/propagation/propagate_box.py
  function propagate_box (line 12) | def propagate_box(temp_feats, box, img, model):

FILE: unitrack/core/propagation/propagate_mask.py
  function propagate_mask (line 12) | def propagate_mask(temp_feats, mask, img, model):

FILE: unitrack/core/propagation/propagate_pose.py
  function propagate_pose (line 12) | def propagate_pose(temp_feats, pose, img, model):

FILE: unitrack/mask.py
  class MaskAssociationTracker (line 18) | class MaskAssociationTracker(AssociationTracker):
    method __init__ (line 19) | def __init__(self, opt):
    method extract_emb (line 22) | def extract_emb(self, img, obs):
    method prepare_obs (line 48) | def prepare_obs(self, img, img0, obs, embs=None):

FILE: unitrack/mask_with_train_embs.py
  class AssociationTrackerWithTrainedEmbed (line 19) | class AssociationTrackerWithTrainedEmbed(object):
    method __init__ (line 20) | def __init__(self, opt):
    method extract_emb (line 40) | def extract_emb(self, img, obs):
    method prepare_obs (line 43) | def prepare_obs(self, img, img0, obs, embs=None):
    method update (line 46) | def update(self, img, img0, obs, embs=None):
    method reset_all (line 153) | def reset_all(self, ):
  class MaskAssociationTracker (line 160) | class MaskAssociationTracker(AssociationTrackerWithTrainedEmbed):
    method __init__ (line 161) | def __init__(self, opt):
    method extract_emb (line 164) | def extract_emb(self, img, obs, embs):
    method prepare_obs (line 192) | def prepare_obs(self, img, img0, obs, embs=None):

FILE: unitrack/model/functional.py
  function hard_prop (line 17) | def hard_prop(pred):
  function context_index_bank (line 24) | def context_index_bank(n_context, long_mem, N):
  function mem_efficient_batched_affinity (line 42) | def mem_efficient_batched_affinity(
  function batched_affinity (line 75) | def batched_affinity(query, keys, mask, temperature, topk, long_mem, dev...
  function process_pose (line 103) | def process_pose(pred, lbl_set, topk=3):
  class MaskedAttention (line 127) | class MaskedAttention(nn.Module):
    method __init__ (line 132) | def __init__(self, radius, flat=True):
    method mask (line 139) | def mask(self, H, W):
    method index (line 144) | def index(self, H, W):
    method make (line 149) | def make(self, H, W):
    method flatten (line 164) | def flatten(self, D):
    method make_index (line 167) | def make_index(self, H, W, pad=False):
    method forward (line 175) | def forward(self, x):

FILE: unitrack/model/hrnet.py
  function conv3x3 (line 29) | def conv3x3(in_planes, out_planes, stride=1):
  class BasicBlock (line 35) | class BasicBlock(nn.Module):
    method __init__ (line 38) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 48) | def forward(self, x):
  class Bottleneck (line 67) | class Bottleneck(nn.Module):
    method __init__ (line 70) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 85) | def forward(self, x):
  class HighResolutionModule (line 108) | class HighResolutionModule(nn.Module):
    method __init__ (line 109) | def __init__(self, num_branches, blocks, num_blocks, num_inchannels,
    method _check_branches (line 126) | def _check_branches(self, num_branches, blocks, num_blocks,
    method _make_one_branch (line 146) | def _make_one_branch(self, branch_index, block, num_blocks, num_channels,
    method _make_branches (line 170) | def _make_branches(self, num_branches, block, num_blocks, num_channels):
    method _make_fuse_layers (line 179) | def _make_fuse_layers(self):
    method get_num_inchannels (line 227) | def get_num_inchannels(self):
    method forward (line 230) | def forward(self, x):
  class HighResolutionNet (line 263) | class HighResolutionNet(nn.Module):
    method __init__ (line 265) | def __init__(self, cfg, **kwargs):
    method _make_head (line 320) | def _make_head(self, pre_stage_channels):
    method _make_transition_layer (line 369) | def _make_transition_layer(
    method _make_layer (line 405) | def _make_layer(self, block, inplanes, planes, blocks, stride=1):
    method _make_stage (line 422) | def _make_stage(self, layer_config, num_inchannels,
    method forward (line 452) | def forward(self, x):
    method init_weights (line 500) | def init_weights(self, pretrained='',):
  function get_cls_net (line 601) | def get_cls_net(c, **kwargs):

FILE: unitrack/model/model.py
  class AppearanceModel (line 11) | class AppearanceModel(nn.Module):
    method __init__ (line 12) | def __init__(self, args):
    method forward (line 17) | def forward(self, x):
  function partial_load (line 21) | def partial_load(pretrained_dict, model, skip_keys=[], log=False):
  function load_vince_model (line 40) | def load_vince_model(path):
  function load_uvc_model (line 46) | def load_uvc_model(ckpt_path):
  function load_tc_model (line 57) | def load_tc_model(ckpt_path):
  class From3D (line 74) | class From3D(nn.Module):
    method __init__ (line 76) | def __init__(self, resnet):
    method forward (line 80) | def forward(self, x):
  function make_encoder (line 88) | def make_encoder(args):

FILE: unitrack/model/random_feat_generator.py
  class RandomFeatGenerator (line 15) | class RandomFeatGenerator(nn.Module):
    method __init__ (line 16) | def __init__(self, args):
    method forward (line 21) | def forward(self, x):
    method __str__ (line 36) | def __str__(self):

FILE: unitrack/model/resnet.py
  class ResNet (line 23) | class ResNet(torch_resnet.ResNet):
    method __init__ (line 24) | def __init__(self, *args, **kwargs):
    method modify (line 27) | def modify(self, remove_layers=[], padding=''):
    method forward (line 50) | def forward(self, x):
  function _resnet (line 64) | def _resnet(arch, block, layers, pretrained, progress, **kwargs):
  function resnet18 (line 72) | def resnet18(pretrained=False, progress=True, **kwargs):
  function resnet50 (line 76) | def resnet50(pretrained=False, progress=True, **kwargs) -> ResNet:
  function resnet101 (line 80) | def resnet101(pretrained=False, progress=True, **kwargs):
  function resnet152 (line 84) | def resnet152(pretrained=False, progress=True, **kwargs):
  function resnext50_32x4d (line 96) | def resnext50_32x4d(pretrained=False, progress=True, **kwargs):
  function resnext101_32x8d (line 110) | def resnext101_32x8d(pretrained=False, progress=True, **kwargs):
  function wide_resnet50_2 (line 124) | def wide_resnet50_2(pretrained=False, progress=True, **kwargs):
  function wide_resnet101_2 (line 142) | def wide_resnet101_2(pretrained=False, progress=True, **kwargs):

FILE: unitrack/multitracker.py
  class AssociationTracker (line 25) | class AssociationTracker(object):
    method __init__ (line 26) | def __init__(self, opt):
    method extract_emb (line 46) | def extract_emb(self, img, obs):
    method prepare_obs (line 49) | def prepare_obs(self, img, img0, obs, embs=None):
    method update (line 52) | def update(self, img, img0, obs, embs=None):
    method reset_all (line 159) | def reset_all(self, ):

FILE: unitrack/utils/__init__.py
  function to_numpy (line 21) | def to_numpy(tensor):
  function to_torch (line 29) | def to_torch(ndarray):
  function im_to_numpy (line 37) | def im_to_numpy(img):
  function im_to_torch (line 42) | def im_to_torch(img):

FILE: unitrack/utils/box.py
  function xyxy2xywh (line 13) | def xyxy2xywh(x):
  function xywh2xyxy (line 23) | def xywh2xyxy(x):
  function tlwh2xyxy (line 33) | def tlwh2xyxy(x):
  function tlwh_to_xywh (line 41) | def tlwh_to_xywh(tlwh):
  function tlwh_to_xyah (line 47) | def tlwh_to_xyah(tlwh):
  function tlbr_to_tlwh (line 57) | def tlbr_to_tlwh(tlbr):
  function tlwh_to_tlbr (line 63) | def tlwh_to_tlbr(tlwh):
  function scale_box (line 69) | def scale_box(scale, coords):
  function scale_box_letterbox_size (line 76) | def scale_box_letterbox_size(img_size, coords, img0_shape):
  function scale_box_input_size (line 88) | def scale_box_input_size(img_size, coords, img0_shape):
  function clip_boxes (line 101) | def clip_boxes(boxes, im_shape):
  function clip_box (line 120) | def clip_box(bbox, im_shape):
  function int_box (line 131) | def int_box(box):
  function remove_duplicated_box (line 137) | def remove_duplicated_box(boxes, iou_th=0.5):
  function skltn2box (line 153) | def skltn2box(skltn):

FILE: unitrack/utils/io.py
  function mkdir_if_missing (line 8) | def mkdir_if_missing(d):
  function write_mots_results (line 12) | def write_mots_results(filename, results, data_type='mot'):
  function write_mot_results (line 35) | def write_mot_results(filename, results, data_type='mot'):
  function read_mot_results (line 63) | def read_mot_results(filename, data_type='mot', is_gt=False, is_ignore=F...
  function _read_mot_results (line 90) | def _read_mot_results(filename, is_gt, is_ignore):
  function unzip_objs (line 132) | def unzip_objs(objs):

FILE: unitrack/utils/log.py
  function get_logger (line 4) | def get_logger(name='root'):

FILE: unitrack/utils/mask.py
  function coords2bbox (line 18) | def coords2bbox(coords, extend=2):
  function coords2bbox_all (line 40) | def coords2bbox_all(coords):
  function coords2bboxTensor (line 48) | def coords2bboxTensor(coords, extend=2):
  function mask2box (line 69) | def mask2box(masks):
  function tensor_mask2box (line 80) | def tensor_mask2box(masks):
  function batch_mask2boxlist (line 92) | def batch_mask2boxlist(masks):
  function bboxlist2roi (line 116) | def bboxlist2roi(bbox_list):
  function bbox2roi (line 137) | def bbox2roi(bbox_list):
  function temp_interp_mask (line 158) | def temp_interp_mask(maskseq, T):
  function mask_seq_jac (line 172) | def mask_seq_jac(sa, sb):
  function skltn2mask (line 182) | def skltn2mask(skltn, size):
  function pts2array (line 226) | def pts2array(pts):

FILE: unitrack/utils/meter.py
  class Timer (line 14) | class Timer(object):
    method __init__ (line 16) | def __init__(self):
    method tic (line 25) | def tic(self):
    method toc (line 30) | def toc(self, average=True):
    method clear (line 41) | def clear(self):

FILE: unitrack/utils/visualize.py
  function dump_predictions (line 14) | def dump_predictions(pred, lbl_set, img, prefix):
  function make_gif (line 57) | def make_gif(video, outname='/tmp/test.gif', sz=256):
  function get_color (line 73) | def get_color(idx):
  function plot_tracking (line 78) | def plot_tracking(image, obs, obj_ids, scores=None, frame_id=0, fps=0.):
  function vis_pose (line 109) | def vis_pose(oriImg, points):
  function draw_skeleton (line 149) | def draw_skeleton(aa, kp, color, show_skeleton_labels=False, dataset= "P...