SYMBOL INDEX (1896 symbols across 173 files) FILE: PythonAPI/common/gason.cpp function isspace (line 52) | static inline bool isspace(char c) { function isdelim (line 56) | static inline bool isdelim(char c) { function isdigit (line 60) | static inline bool isdigit(char c) { function isxdigit (line 64) | static inline bool isxdigit(char c) { function char2int (line 68) | static inline int char2int(char c) { function string2double (line 74) | static double string2double(char *s, char **endptr) { function JsonNode (line 120) | static inline JsonNode *insertAfter(JsonNode *tail, JsonNode *node) { function JsonValue (line 128) | static inline JsonValue listToValue(JsonTag tag, JsonNode *tail) { function jsonParse (line 137) | int jsonParse(char *s, char **endptr, JsonValue *value, JsonAllocator &a... FILE: PythonAPI/common/gason.h type JsonTag (line 8) | enum JsonTag { type JsonNode (line 18) | struct JsonNode function JsonNode (line 54) | JsonNode *toNode() const { type JsonNode (line 60) | struct JsonNode { type JsonIterator (line 66) | struct JsonIterator { function JsonIterator (line 86) | inline JsonIterator end(JsonValue) { FILE: PythonAPI/common/maskApi.c function uint (line 11) | uint umin( uint a, uint b ) { return (ab) ? a : b; } function rleInit (line 14) | void rleInit( RLE *R, siz h, siz w, siz m, uint *cnts ) { function rleFree (line 19) | void rleFree( RLE *R ) { function rlesInit (line 23) | void rlesInit( RLE **R, siz n ) { function rlesFree (line 28) | void rlesFree( RLE **R, siz n ) { function rleEncode (line 32) | void rleEncode( RLE *R, const byte *M, siz h, siz w, siz n ) { function rleDecode (line 43) | void rleDecode( const RLE *R, byte *M, siz n ) { function rleMerge (line 49) | void rleMerge( const RLE *R, RLE *M, siz n, int intersect ) { function rleArea 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imgId, catId): method evaluateImg (line 318) | def evaluateImg(self, imgId, catId, aRng, maxDet): method accumulate (line 400) | def accumulate(self, p = None): method summarize (line 507) | def summarize(self): method __str__ (line 580) | def __str__(self): class Params (line 583) | class Params: method setDetParams (line 587) | def setDetParams(self): method setKpParams (line 598) | def setKpParams(self): method __init__ (line 610) | def __init__(self, iouType='segm'): FILE: PythonAPI/pysobatools/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: PythonAPI/pysobatools/soba.py function _isArrayLike (line 66) | def _isArrayLike(obj): class SOBA (line 70) | class SOBA: method __init__ (line 71) | def __init__(self, annotation_file=None): method createIndex (line 92) | def createIndex(self): method info (line 144) | def info(self): method getAssoAnnIds (line 152) | def getAssoAnnIds(self, imgIds=[], catIds=[], areaRng=[], iscrowd=None): method getAnnIds (line 180) | def getAnnIds(self, imgIds=[], catIds=[], areaRng=[], iscrowd=None): method getAssoIds (line 208) | def getAssoIds(self, catNms=[], supNms=[], catIds=[]): method getCatIds (line 230) | def getCatIds(self, catNms=[], supNms=[], catIds=[]): method getImgIds (line 252) | def getImgIds(self, imgIds=[], catIds=[]): method loadAnns (line 273) | def loadAnns(self, ids=[]): method loadAssoAnns (line 284) | def loadAssoAnns(self, ids=[]): method loadCats (line 290) | def loadCats(self, ids=[]): method loadAsso (line 301) | def loadAsso(self, ids=[]): method loadImgs (line 307) | def loadImgs(self, ids=[]): method showAnns (line 318) | def showAnns(self, anns): method loadRes (line 382) | def loadRes(self, resFile): method loadRes_asso (line 443) | def loadRes_asso(self, resFile): method download (line 504) | def download(self, tarDir = None, imgIds = [] ): method loadNumpyAnnotations (line 528) | def loadNumpyAnnotations(self, data): method annToRLE (line 551) | def annToRLE(self, ann): method annToMask (line 572) | def annToMask(self, ann): FILE: PythonAPI/pysobatools/sobaeval.py class SOAPeval (line 10) | class SOAPeval: method __init__ (line 60) | def __init__(self, isdGt=None, isdDt=None, isdRel = None,iouType='segm'): method _prepare (line 87) | def _prepare(self): method _prepare_asso (line 124) | def _prepare_asso(self): method evaluate (line 162) | def evaluate(self): method evaluate_asso (line 204) | def evaluate_asso(self): method computeIoU (line 248) | def computeIoU(self, imgId, catId): method computeOks (line 277) | def computeOks(self, imgId, catId): method evaluateImg (line 320) | def evaluateImg(self, imgId, catId, aRng, maxDet): method accumulate (line 458) | def accumulate(self, p = None): method summarize (line 565) | def summarize(self): method __str__ (line 638) | def __str__(self): class Params (line 641) | class Params: method setDetParams (line 645) | def setDetParams(self): method setKpParams (line 656) | def setKpParams(self): method __init__ (line 668) | def __init__(self, iouType='segm'): FILE: datasets/prepare_panoptic_fpn.py function _process_panoptic_to_semantic (line 18) | def _process_panoptic_to_semantic(input_panoptic, output_semantic, segme... function separate_coco_semantic_from_panoptic (line 29) | def separate_coco_semantic_from_panoptic(panoptic_json, panoptic_root, s... function link_val100 (line 98) | def link_val100(dir_full, dir_100): FILE: demo/demo.py function setup_cfg (line 20) | def setup_cfg(args): function get_parser (line 33) | def get_parser(): FILE: demo/predictor.py class VisualizationDemo (line 15) | class VisualizationDemo(object): method __init__ (line 16) | def __init__(self, cfg, instance_mode=ColorMode.IMAGE, parallel=False): method run_on_image (line 37) | def run_on_image(self, image): method _frame_from_video (line 68) | def _frame_from_video(self, video): method run_on_video (line 76) | def run_on_video(self, video): class AsyncPredictor (line 132) | class AsyncPredictor: class _StopToken (line 139) | class _StopToken: class _PredictWorker (line 142) | class _PredictWorker(mp.Process): method __init__ (line 143) | def __init__(self, cfg, task_queue, result_queue): method run (line 149) | def run(self): method __init__ (line 160) | def __init__(self, cfg, num_gpus: int = 1): method put (line 187) | def put(self, image): method get (line 191) | def get(self): method __len__ (line 207) | def __len__(self): method __call__ (line 210) | def __call__(self, image): method shutdown (line 214) | def shutdown(self): method default_buffer_size (line 219) | def default_buffer_size(self): FILE: detectron2/checkpoint/c2_model_loading.py function convert_basic_c2_names (line 12) | def convert_basic_c2_names(original_keys): function convert_c2_detectron_names (line 68) | def convert_c2_detectron_names(weights): function align_and_update_state_dicts (line 211) | def align_and_update_state_dicts(model_state_dict, ckpt_state_dict, c2_c... FILE: detectron2/checkpoint/catalog.py class ModelCatalog (line 6) | class ModelCatalog(object): method get (line 55) | def get(name): method _get_c2_imagenet_pretrained (line 63) | def _get_c2_imagenet_pretrained(name): method _get_c2_detectron_baseline (line 71) | def _get_c2_detectron_baseline(name): class ModelCatalogHandler (line 92) | class ModelCatalogHandler(PathHandler): method _get_supported_prefixes (line 99) | def _get_supported_prefixes(self): method _get_local_path (line 102) | def _get_local_path(self, path): method _open (line 108) | def _open(self, path, mode="r", **kwargs): class Detectron2Handler (line 112) | class Detectron2Handler(PathHandler): method _get_supported_prefixes (line 120) | def _get_supported_prefixes(self): method _get_local_path (line 123) | def _get_local_path(self, path): method _open (line 127) | def _open(self, path, mode="r", **kwargs): FILE: detectron2/checkpoint/detection_checkpoint.py class DetectionCheckpointer (line 11) | class DetectionCheckpointer(Checkpointer): method __init__ (line 17) | def __init__(self, model, save_dir="", *, save_to_disk=None, **checkpo... method _load_file (line 26) | def _load_file(self, filename): method _load_model (line 47) | def _load_model(self, checkpoint): FILE: detectron2/checkpoint/model_zoo.py class ModelCatalog (line 6) | class ModelCatalog(object): method get (line 55) | def get(name): method _get_c2_imagenet_pretrained (line 63) | def _get_c2_imagenet_pretrained(name): method _get_c2_detectron_baseline (line 71) | def _get_c2_detectron_baseline(name): class ModelCatalogHandler (line 92) | class ModelCatalogHandler(PathHandler): method _get_supported_prefixes (line 99) | def _get_supported_prefixes(self): method _get_local_path (line 102) | def _get_local_path(self, path): method _open (line 108) | def _open(self, path, mode="r"): class Detectron2Handler (line 112) | class Detectron2Handler(PathHandler): method _get_supported_prefixes (line 120) | def _get_supported_prefixes(self): method _get_local_path (line 123) | def _get_local_path(self, path): method _open (line 127) | def _open(self, path, mode="r"): FILE: detectron2/config/compat.py function upgrade_config (line 33) | def upgrade_config(cfg: CN, to_version: Optional[int] = None) -> CN: function downgrade_config (line 55) | def downgrade_config(cfg: CN, to_version: int) -> CN: function guess_version (line 82) | def guess_version(cfg: CN, filename: str) -> int: function _rename (line 116) | def _rename(cfg: CN, old: str, new: str) -> None: class _RenameConverter (line 146) | class _RenameConverter: method upgrade (line 154) | def upgrade(cls, cfg: CN) -> None: method downgrade (line 159) | def downgrade(cls, cfg: CN) -> None: class ConverterV1 (line 164) | class ConverterV1(_RenameConverter): class ConverterV2 (line 168) | class ConverterV2(_RenameConverter): method upgrade (line 204) | def upgrade(cls, cfg: CN) -> None: method downgrade (line 222) | def downgrade(cls, cfg: CN) -> None: FILE: detectron2/config/config.py class CfgNode (line 8) | class CfgNode(_CfgNode): method merge_from_file (line 22) | def merge_from_file(self, cfg_filename: str, allow_unsafe: bool = True... function get_cfg (line 68) | def get_cfg() -> CfgNode: function set_global_cfg (line 80) | def set_global_cfg(cfg: CfgNode) -> None: FILE: detectron2/data/build.py function filter_images_with_only_crowd_annotations (line 37) | def filter_images_with_only_crowd_annotations(dataset_dicts): function filter_images_with_few_keypoints (line 68) | def filter_images_with_few_keypoints(dataset_dicts, min_keypoints_per_im... function load_proposals_into_dataset (line 102) | def load_proposals_into_dataset(dataset_dicts, proposal_file): function _quantize (line 151) | def _quantize(x, bin_edges): function print_instances_class_histogram (line 158) | def print_instances_class_histogram(dataset_dicts, class_names): function build_batch_data_sampler (line 203) | def build_batch_data_sampler( function get_detection_dataset_dicts (line 242) | def get_detection_dataset_dicts( function build_detection_train_loader (line 287) | def build_detection_train_loader(cfg, mapper=None): function build_detection_test_loader (line 366) | def build_detection_test_loader(cfg, dataset_name, mapper=None): function trivial_batch_collator (line 412) | def trivial_batch_collator(batch): function worker_init_reset_seed (line 419) | def worker_init_reset_seed(worker_id): FILE: detectron2/data/catalog.py class DatasetCatalog (line 12) | class DatasetCatalog(object): method register (line 31) | def register(name, func): method get (line 40) | def get(name): method list (line 61) | def list() -> List[str]: method clear (line 71) | def clear(): class Metadata (line 78) | class Metadata(types.SimpleNamespace): method __getattr__ (line 104) | def __getattr__(self, key): method __setattr__ (line 119) | def __setattr__(self, key, val): method as_dict (line 138) | def as_dict(self): method set (line 145) | def set(self, **kwargs): method get (line 153) | def get(self, key, default=None): class MetadataCatalog (line 164) | class MetadataCatalog: method get (line 179) | def get(name): FILE: detectron2/data/common.py class MapDataset (line 12) | class MapDataset(data.Dataset): method __init__ (line 24) | def __init__(self, dataset, map_func): method __len__ (line 31) | def __len__(self): method __getitem__ (line 34) | def __getitem__(self, idx): class DatasetFromList (line 58) | class DatasetFromList(data.Dataset): method __init__ (line 63) | def __init__(self, lst: list, copy: bool = True): method __len__ (line 74) | def __len__(self): method __getitem__ (line 77) | def __getitem__(self, idx): FILE: detectron2/data/dataset_mapper.py class DatasetMapper (line 18) | class DatasetMapper: method __init__ (line 32) | def __init__(self, cfg, is_train=True): method __call__ (line 62) | def __call__(self, dataset_dict): FILE: detectron2/data/datasets/builtin.py function register_all_coco (line 102) | def register_all_coco(root="datasets"): function register_all_lvis (line 144) | def register_all_lvis(root="datasets"): function register_all_cityscapes (line 166) | def register_all_cityscapes(root="datasets"): function register_all_pascal_voc (line 193) | def register_all_pascal_voc(root="datasets"): FILE: detectron2/data/datasets/builtin_meta.py function _get_coco_instances_meta (line 191) | def _get_coco_instances_meta(): function _get_coco_panoptic_separated_meta (line 206) | def _get_coco_panoptic_separated_meta(): function _get_builtin_metadata (line 239) | def _get_builtin_metadata(dataset_name): FILE: detectron2/data/datasets/cityscapes.py function load_cityscapes_instances (line 25) | def load_cityscapes_instances(image_dir, gt_dir, from_json=True, to_poly... function load_cityscapes_semantic (line 81) | def load_cityscapes_semantic(image_dir, gt_dir): function cityscapes_files_to_dict (line 117) | def cityscapes_files_to_dict(files, from_json, to_polygons): FILE: detectron2/data/datasets/coco.py function load_coco_json (line 24) | def load_coco_json(json_file, image_root, dataset_name=None): function load_sem_seg (line 255) | def load_sem_seg(gt_root, image_root, gt_ext="png", image_ext="jpg"): FILE: detectron2/data/datasets/lvis.py function register_lvis_instances (line 22) | def register_lvis_instances(name, metadata, json_file, image_root): function load_lvis_json (line 38) | def load_lvis_json(json_file, image_root, dataset_name=None): function get_lvis_instances_meta (line 147) | def get_lvis_instances_meta(dataset_name): function _get_lvis_instances_meta_v0_5 (line 165) | def _get_lvis_instances_meta_v0_5(): FILE: detectron2/data/datasets/pascal_voc.py function load_voc_instances (line 25) | def load_voc_instances(dirname: str, split: str): function register_pascal_voc (line 74) | def register_pascal_voc(name, dirname, split, year): FILE: detectron2/data/datasets/register_coco.py function register_coco_instances (line 14) | def register_coco_instances(name, metadata, json_file, image_root): function register_coco_panoptic_separated (line 41) | def register_coco_panoptic_separated( function merge_to_panoptic (line 102) | def merge_to_panoptic(detection_dicts, sem_seg_dicts): FILE: detectron2/data/datasets/register_soba.py function register_soba_instances (line 14) | def register_soba_instances(name, metadata, json_file, image_root): function register_soba_panoptic_separated (line 41) | def register_soba_panoptic_separated( function merge_to_panoptic (line 102) | def merge_to_panoptic(detection_dicts, sem_seg_dicts): FILE: detectron2/data/datasets/soba.py function load_soba_json (line 24) | def load_soba_json(json_file, image_root, dataset_name=None): function load_sem_seg (line 255) | def load_sem_seg(gt_root, image_root, gt_ext="png", image_ext="jpg"): FILE: detectron2/data/detection_utils.py class SizeMismatchError (line 29) | class SizeMismatchError(ValueError): function read_image (line 35) | def read_image(file_name, format=None): function check_image_size (line 65) | def check_image_size(dataset_dict, image): function transform_proposals (line 78) | def transform_proposals(dataset_dict, image_shape, transforms, min_box_s... function transform_instance_annotations (line 120) | def transform_instance_annotations( function transform_keypoint_annotations (line 187) | def transform_keypoint_annotations(keypoints, transforms, image_size, ke... function annotations_to_instances (line 221) | def annotations_to_instances(annos, image_size, mask_format="polygon"): function annotations_to_instances_rotated (line 292) | def annotations_to_instances_rotated(annos, image_size): function filter_empty_instances (line 321) | def filter_empty_instances(instances, by_box=True, by_mask=True): function create_keypoint_hflip_indices (line 350) | def create_keypoint_hflip_indices(dataset_names): function gen_crop_transform_with_instance (line 373) | def gen_crop_transform_with_instance(crop_size, image_size, instance): function check_metadata_consistency (line 397) | def check_metadata_consistency(key, dataset_names): function build_transform_gen (line 426) | def build_transform_gen(cfg, is_train): FILE: detectron2/data/samplers/distributed_sampler.py class TrainingSampler (line 12) | class TrainingSampler(Sampler): method __init__ (line 24) | def __init__(self, size: int, shuffle: bool = True, seed: Optional[int... method __iter__ (line 43) | def __iter__(self): method _infinite_indices (line 47) | def _infinite_indices(self): class RepeatFactorTrainingSampler (line 57) | class RepeatFactorTrainingSampler(Sampler): method __init__ (line 69) | def __init__(self, dataset_dicts, repeat_thresh, shuffle=True, seed=No... method _get_repeat_factors (line 93) | def _get_repeat_factors(self, dataset_dicts, repeat_thresh): method _get_epoch_indices (line 131) | def _get_epoch_indices(self, generator): method __iter__ (line 154) | def __iter__(self): method _infinite_indices (line 158) | def _infinite_indices(self): class InferenceSampler (line 172) | class InferenceSampler(Sampler): method __init__ (line 180) | def __init__(self, size: int): method __iter__ (line 195) | def __iter__(self): method __len__ (line 198) | def __len__(self): FILE: detectron2/data/samplers/grouped_batch_sampler.py class GroupedBatchSampler (line 6) | class GroupedBatchSampler(BatchSampler): method __init__ (line 22) | def __init__(self, sampler, group_ids, batch_size): method __iter__ (line 39) | def __iter__(self): FILE: detectron2/data/transforms/transform.py class ExtentTransform (line 12) | class ExtentTransform(Transform): method __init__ (line 22) | def __init__(self, src_rect, output_size, interp=Image.LINEAR, fill=0): method apply_image (line 33) | def apply_image(self, img, interp=None): method apply_coords (line 44) | def apply_coords(self, coords): method apply_segmentation (line 58) | def apply_segmentation(self, segmentation): class ResizeTransform (line 63) | class ResizeTransform(Transform): method __init__ (line 68) | def __init__(self, h, w, new_h, new_w, interp): method apply_image (line 79) | def apply_image(self, img, interp=None): method apply_coords (line 87) | def apply_coords(self, coords): method apply_segmentation (line 92) | def apply_segmentation(self, segmentation): function HFlip_rotated_box (line 97) | def HFlip_rotated_box(transform, rotated_boxes): function Resize_rotated_box (line 113) | def Resize_rotated_box(transform, rotated_boxes): FILE: detectron2/data/transforms/transform_gen.py function check_dtype (line 37) | def check_dtype(img): class TransformGen (line 49) | class TransformGen(metaclass=ABCMeta): method _init (line 65) | def _init(self, params=None): method get_transform (line 72) | def get_transform(self, img): method _rand_range (line 75) | def _rand_range(self, low=1.0, high=None, size=None): method __repr__ (line 85) | def __repr__(self): class RandomFlip (line 118) | class RandomFlip(TransformGen): method __init__ (line 125) | def __init__(self, prob=0.5): method get_transform (line 140) | def get_transform(self, img): class Resize (line 149) | class Resize(TransformGen): method __init__ (line 152) | def __init__(self, shape, interp=Image.BILINEAR): method get_transform (line 163) | def get_transform(self, img): class ResizeShortestEdge (line 169) | class ResizeShortestEdge(TransformGen): method __init__ (line 175) | def __init__( method get_transform (line 194) | def get_transform(self, img): class RandomCrop (line 216) | class RandomCrop(TransformGen): method __init__ (line 221) | def __init__(self, crop_type: str, crop_size): method get_transform (line 233) | def get_transform(self, img): method get_crop_size (line 241) | def get_crop_size(self, image_size): class RandomExtent (line 263) | class RandomExtent(TransformGen): method __init__ (line 272) | def __init__(self, scale_range, shift_range): method get_transform (line 285) | def get_transform(self, img): class RandomContrast (line 308) | class RandomContrast(TransformGen): method __init__ (line 320) | def __init__(self, intensity_min, intensity_max): method get_transform (line 329) | def get_transform(self, img): class RandomBrightness (line 334) | class RandomBrightness(TransformGen): method __init__ (line 346) | def __init__(self, intensity_min, intensity_max): method get_transform (line 355) | def get_transform(self, img): class RandomSaturation (line 360) | class RandomSaturation(TransformGen): method __init__ (line 372) | def __init__(self, intensity_min, intensity_max): method get_transform (line 381) | def get_transform(self, img): class RandomLighting (line 388) | class RandomLighting(TransformGen): method __init__ (line 396) | def __init__(self, scale): method get_transform (line 408) | def get_transform(self, img): function apply_transform_gens (line 416) | def apply_transform_gens(transform_gens, img): FILE: detectron2/engine/defaults.py function default_argument_parser (line 48) | def default_argument_parser(): function default_setup (line 83) | def default_setup(cfg, args): class DefaultPredictor (line 132) | class DefaultPredictor: method __init__ (line 142) | def __init__(self, cfg): method __call__ (line 159) | def __call__(self, original_image): class DefaultTrainer (line 180) | class DefaultTrainer(SimpleTrainer): method __init__ (line 209) | def __init__(self, cfg): method resume_or_load (line 242) | def resume_or_load(self, resume=True): method build_hooks (line 260) | def build_hooks(self): method build_writers (line 306) | def build_writers(self): method train (line 322) | def train(self): method build_model (line 335) | def build_model(cls, cfg): method build_optimizer (line 346) | def build_optimizer(cls, cfg, model): method build_lr_scheduler (line 354) | def build_lr_scheduler(cls, cfg, optimizer): method build_train_loader (line 358) | def build_train_loader(cls, cfg): method build_test_loader (line 366) | def build_test_loader(cls, cfg, dataset_name): method build_evaluator (line 374) | def build_evaluator(cls, cfg, dataset_name): method test (line 382) | def test(cls, cfg, model, evaluators=None): FILE: detectron2/engine/hooks.py class CallbackHook (line 39) | class CallbackHook(HookBase): method __init__ (line 44) | def __init__(self, *, before_train=None, after_train=None, before_step... method before_train (line 53) | def before_train(self): method after_train (line 57) | def after_train(self): method before_step (line 65) | def before_step(self): method after_step (line 69) | def after_step(self): class IterationTimer (line 74) | class IterationTimer(HookBase): method __init__ (line 86) | def __init__(self, warmup_iter=3): method before_train (line 95) | def before_train(self): method after_train (line 100) | def after_train(self): method before_step (line 126) | def before_step(self): method after_step (line 130) | def after_step(self): class PeriodicWriter (line 143) | class PeriodicWriter(HookBase): method __init__ (line 150) | def __init__(self, writers, period=20): method after_step (line 159) | def after_step(self): class PeriodicCheckpointer (line 167) | class PeriodicCheckpointer(_PeriodicCheckpointer, HookBase): method before_train (line 178) | def before_train(self): method after_step (line 181) | def after_step(self): class LRScheduler (line 186) | class LRScheduler(HookBase): method __init__ (line 192) | def __init__(self, optimizer, scheduler): method after_step (line 220) | def after_step(self): class AutogradProfiler (line 226) | class AutogradProfiler(HookBase): method __init__ (line 238) | def __init__(self, enable_predicate, output_dir, *, use_cuda=True): method before_step (line 251) | def before_step(self): method after_step (line 258) | def after_step(self): class EvalHook (line 278) | class EvalHook(HookBase): method __init__ (line 285) | def __init__(self, eval_period, eval_function): method after_step (line 300) | def after_step(self): method after_train (line 326) | def after_train(self): class PreciseBN (line 332) | class PreciseBN(HookBase): method __init__ (line 342) | def __init__(self, period, model, data_loader, num_iter): method after_step (line 371) | def after_step(self): method update_stats (line 377) | def update_stats(self): FILE: detectron2/engine/launch.py function _find_free_port (line 12) | def _find_free_port(): function launch (line 24) | def launch(main_func, num_gpus_per_machine, num_machines=1, machine_rank... function _distributed_worker (line 55) | def _distributed_worker( FILE: detectron2/engine/train_loop.py class HookBase (line 16) | class HookBase: method before_train (line 51) | def before_train(self): method after_train (line 57) | def after_train(self): method before_step (line 63) | def before_step(self): method after_step (line 69) | def after_step(self): class TrainerBase (line 76) | class TrainerBase: method __init__ (line 95) | def __init__(self): method register_hooks (line 98) | def register_hooks(self, hooks): method train (line 116) | def train(self, start_iter: int, max_iter: int): method before_train (line 137) | def before_train(self): method after_train (line 141) | def after_train(self): method before_step (line 145) | def before_step(self): method after_step (line 149) | def after_step(self): method run_step (line 155) | def run_step(self): class SimpleTrainer (line 159) | class SimpleTrainer(TrainerBase): method __init__ (line 174) | def __init__(self, model, data_loader, optimizer): method run_step (line 197) | def run_step(self): method _detect_anomaly (line 233) | def _detect_anomaly(self, losses, loss_dict): method _write_metrics (line 241) | def _write_metrics(self, metrics_dict: dict): FILE: detectron2/evaluation/cityscapes_evaluation.py class CityscapesEvaluator (line 16) | class CityscapesEvaluator(DatasetEvaluator): method __init__ (line 25) | def __init__(self, dataset_name): method reset (line 36) | def reset(self): method process (line 48) | def process(self, inputs, outputs): method evaluate (line 72) | def evaluate(self): FILE: detectron2/evaluation/coco_evaluation.py class COCOEvaluator (line 27) | class COCOEvaluator(DatasetEvaluator): method __init__ (line 33) | def __init__(self, dataset_name, cfg, distributed, output_dir=None): method reset (line 61) | def reset(self): method _tasks_from_config (line 65) | def _tasks_from_config(self, cfg): method process (line 77) | def process(self, inputs, outputs): method evaluate (line 130) | def evaluate(self): method _eval_predictions (line 160) | def _eval_predictions(self, tasks): method _eval_box_proposals (line 225) | def _eval_box_proposals(self): method _derive_coco_results (line 284) | def _derive_coco_results(self, coco_eval, iou_type, class_names=None): function instances_to_json (line 348) | def instances_to_json(instances, img_id): function _evaluate_box_proposals (line 408) | def _evaluate_box_proposals(dataset_predictions, coco_api, thresholds=No... function _evaluate_predictions_on_coco (line 517) | def _evaluate_predictions_on_coco(coco_gt, coco_results, iou_type, kpt_o... FILE: detectron2/evaluation/evaluation/cityscapes_evaluation.py class CityscapesEvaluator (line 16) | class CityscapesEvaluator(DatasetEvaluator): method __init__ (line 25) | def __init__(self, dataset_name): method reset (line 36) | def reset(self): method process (line 48) | def process(self, inputs, outputs): method evaluate (line 72) | def evaluate(self): FILE: detectron2/evaluation/evaluation/coco_evaluation.py class COCOEvaluator (line 27) | class COCOEvaluator(DatasetEvaluator): method __init__ (line 33) | def __init__(self, dataset_name, cfg, distributed, output_dir=None): method reset (line 61) | def reset(self): method _tasks_from_config (line 65) | def _tasks_from_config(self, cfg): method process (line 77) | def process(self, inputs, outputs): method evaluate (line 130) | def evaluate(self): method _eval_predictions (line 160) | def _eval_predictions(self, tasks): method _eval_box_proposals (line 225) | def _eval_box_proposals(self): method _derive_coco_results (line 284) | def _derive_coco_results(self, coco_eval, iou_type, class_names=None): function instances_to_json (line 348) | def instances_to_json(instances, img_id): function _evaluate_box_proposals (line 408) | def _evaluate_box_proposals(dataset_predictions, coco_api, thresholds=No... function _evaluate_predictions_on_coco (line 517) | def _evaluate_predictions_on_coco(coco_gt, coco_results, iou_type, kpt_o... FILE: detectron2/evaluation/evaluation/evaluator.py class DatasetEvaluator (line 12) | class DatasetEvaluator: method reset (line 23) | def reset(self): method process (line 30) | def process(self, input, output): method evaluate (line 40) | def evaluate(self): class DatasetEvaluators (line 56) | class DatasetEvaluators(DatasetEvaluator): method __init__ (line 57) | def __init__(self, evaluators): method reset (line 62) | def reset(self): method process (line 66) | def process(self, input, output): method evaluate (line 70) | def evaluate(self): function inference_on_dataset (line 83) | def inference_on_dataset(model, data_loader, evaluator): function inference_context (line 150) | def inference_context(model): FILE: detectron2/evaluation/evaluation/lvis_evaluation.py class LVISEvaluator (line 23) | class LVISEvaluator(DatasetEvaluator): method __init__ (line 29) | def __init__(self, dataset_name, cfg, distributed, output_dir=None): method reset (line 56) | def reset(self): method _tasks_from_config (line 60) | def _tasks_from_config(self, cfg): method process (line 70) | def process(self, inputs, outputs): method evaluate (line 107) | def evaluate(self): method _eval_predictions (line 134) | def _eval_predictions(self, tasks): method _eval_box_proposals (line 167) | def _eval_box_proposals(self): function _evaluate_box_proposals (line 211) | def _evaluate_box_proposals(dataset_predictions, lvis_api, thresholds=No... function _evaluate_predictions_on_lvis (line 318) | def _evaluate_predictions_on_lvis(lvis_gt, lvis_results, iou_type, class... FILE: detectron2/evaluation/evaluation/panoptic_evaluation.py class COCOPanopticEvaluator (line 22) | class COCOPanopticEvaluator(DatasetEvaluator): method __init__ (line 30) | def __init__(self, dataset_name, output_dir): method reset (line 47) | def reset(self): method _convert_category_id (line 50) | def _convert_category_id(self, segment_info): method process (line 65) | def process(self, inputs, outputs): method evaluate (line 86) | def evaluate(self): function _print_panoptic_results (line 140) | def _print_panoptic_results(pq_res): FILE: detectron2/evaluation/evaluation/pascal_voc_evaluation.py class PascalVOCDetectionEvaluator (line 19) | class PascalVOCDetectionEvaluator(DatasetEvaluator): method __init__ (line 29) | def __init__(self, dataset_name): method reset (line 44) | def reset(self): method process (line 47) | def process(self, inputs, outputs): method evaluate (line 63) | def evaluate(self): function parse_rec (line 125) | def parse_rec(filename): function voc_ap (line 147) | def voc_ap(rec, prec, use_07_metric=False): function voc_eval (line 179) | def voc_eval(detpath, annopath, imagesetfile, classname, ovthresh=0.5, u... FILE: detectron2/evaluation/evaluation/sem_seg_evaluation.py class SemSegEvaluator (line 19) | class SemSegEvaluator(DatasetEvaluator): method __init__ (line 24) | def __init__(self, dataset_name, distributed, num_classes, ignore_labe... method reset (line 58) | def reset(self): method process (line 62) | def process(self, inputs, outputs): method evaluate (line 86) | def evaluate(self): method encode_json_sem_seg (line 143) | def encode_json_sem_seg(self, sem_seg, image_id): FILE: detectron2/evaluation/evaluation/testing.py function print_csv_format (line 9) | def print_csv_format(results): function verify_results (line 27) | def verify_results(cfg, results): function flatten_results_dict (line 60) | def flatten_results_dict(results): FILE: detectron2/evaluation/evaluator.py class DatasetEvaluator (line 12) | class DatasetEvaluator: method reset (line 23) | def reset(self): method process (line 30) | def process(self, input, output): method evaluate (line 40) | def evaluate(self): class DatasetEvaluators (line 56) | class DatasetEvaluators(DatasetEvaluator): method __init__ (line 57) | def __init__(self, evaluators): method reset (line 62) | def reset(self): method process (line 66) | def process(self, input, output): method evaluate (line 70) | def evaluate(self): function inference_on_dataset (line 83) | def inference_on_dataset(model, data_loader, evaluator): function inference_context (line 150) | def inference_context(model): FILE: detectron2/evaluation/lvis_evaluation.py class LVISEvaluator (line 23) | class LVISEvaluator(DatasetEvaluator): method __init__ (line 29) | def __init__(self, dataset_name, cfg, distributed, output_dir=None): method reset (line 56) | def reset(self): method _tasks_from_config (line 60) | def _tasks_from_config(self, cfg): method process (line 70) | def process(self, inputs, outputs): method evaluate (line 107) | def evaluate(self): method _eval_predictions (line 134) | def _eval_predictions(self, tasks): method _eval_box_proposals (line 167) | def _eval_box_proposals(self): function _evaluate_box_proposals (line 211) | def _evaluate_box_proposals(dataset_predictions, lvis_api, thresholds=No... function _evaluate_predictions_on_lvis (line 318) | def _evaluate_predictions_on_lvis(lvis_gt, lvis_results, iou_type, class... FILE: detectron2/evaluation/panoptic_evaluation.py class COCOPanopticEvaluator (line 22) | class COCOPanopticEvaluator(DatasetEvaluator): method __init__ (line 30) | def __init__(self, dataset_name, output_dir): method reset (line 47) | def reset(self): method _convert_category_id (line 50) | def _convert_category_id(self, segment_info): method process (line 65) | def process(self, inputs, outputs): method evaluate (line 86) | def evaluate(self): function _print_panoptic_results (line 140) | def _print_panoptic_results(pq_res): FILE: detectron2/evaluation/pascal_voc_evaluation.py class PascalVOCDetectionEvaluator (line 19) | class PascalVOCDetectionEvaluator(DatasetEvaluator): method __init__ (line 29) | def __init__(self, dataset_name): method reset (line 44) | def reset(self): method process (line 47) | def process(self, inputs, outputs): method evaluate (line 63) | def evaluate(self): function parse_rec (line 125) | def parse_rec(filename): function voc_ap (line 147) | def voc_ap(rec, prec, use_07_metric=False): function voc_eval (line 179) | def voc_eval(detpath, annopath, imagesetfile, classname, ovthresh=0.5, u... FILE: detectron2/evaluation/rotated_coco_evaluation.py class RotatedCOCOeval (line 14) | class RotatedCOCOeval(COCOeval): method is_rotated (line 16) | def is_rotated(box_list): method boxlist_to_tensor (line 33) | def boxlist_to_tensor(boxlist, output_box_dim): method compute_iou_dt_gt (line 56) | def compute_iou_dt_gt(self, dt, gt, is_crowd): method computeIoU (line 67) | def computeIoU(self, imgId, catId): class RotatedCOCOEvaluator (line 96) | class RotatedCOCOEvaluator(COCOEvaluator): method process (line 103) | def process(self, inputs, outputs): method instances_to_json (line 123) | def instances_to_json(self, instances, img_id): method _eval_predictions (line 147) | def _eval_predictions(self, tasks): method _evaluate_predictions_on_coco (line 188) | def _evaluate_predictions_on_coco(self, coco_gt, coco_results): FILE: detectron2/evaluation/sem_seg_evaluation.py class SemSegEvaluator (line 19) | class SemSegEvaluator(DatasetEvaluator): method __init__ (line 24) | def __init__(self, dataset_name, distributed, num_classes, ignore_labe... method reset (line 58) | def reset(self): method process (line 62) | def process(self, inputs, outputs): method evaluate (line 86) | def evaluate(self): method encode_json_sem_seg (line 143) | def encode_json_sem_seg(self, sem_seg, image_id): FILE: detectron2/evaluation/soba_evaluation.py class SOBAEvaluator (line 27) | class SOBAEvaluator(DatasetEvaluator): method __init__ (line 33) | def __init__(self, dataset_name, cfg, distributed, output_dir=None): method reset (line 61) | def reset(self): method _tasks_from_config (line 65) | def _tasks_from_config(self, cfg): method process (line 77) | def process(self, inputs, outputs): method evaluate (line 130) | def evaluate(self): method _eval_predictions (line 160) | def _eval_predictions(self, tasks): method _eval_box_proposals (line 225) | def _eval_box_proposals(self): method _derive_soba_results (line 284) | def _derive_soba_results(self, soba_eval, iou_type, class_names=None): function instances_to_json (line 348) | def instances_to_json(instances, img_id): function _evaluate_box_proposals (line 408) | def _evaluate_box_proposals(dataset_predictions, soba_api, thresholds=No... function _evaluate_predictions_on_soba (line 517) | def _evaluate_predictions_on_soba(soba_gt, soba_results, iou_type, kpt_o... FILE: detectron2/evaluation/testing.py function print_csv_format (line 9) | def print_csv_format(results): function verify_results (line 27) | def verify_results(cfg, results): function flatten_results_dict (line 60) | def flatten_results_dict(results): FILE: detectron2/export/api.py function add_export_config (line 17) | def add_export_config(cfg): function export_caffe2_model (line 34) | def export_caffe2_model(cfg, model, inputs): class Caffe2Model (line 58) | class Caffe2Model(nn.Module): method __init__ (line 59) | def __init__(self, predict_net, init_net): method predict_net (line 67) | def predict_net(self): method init_net (line 75) | def init_net(self): method save_protobuf (line 84) | def save_protobuf(self, output_dir): method save_graph (line 102) | def save_graph(self, output_file, inputs=None): method load_protobuf (line 123) | def load_protobuf(dir): method __call__ (line 143) | def __call__(self, inputs): FILE: detectron2/export/c10.py class Boxes4or5 (line 21) | class Boxes4or5(Boxes): method __init__ (line 27) | def __init__(self, tensor): class InstancesList (line 35) | class InstancesList(object): method __init__ (line 45) | def __init__(self, im_info, indices, extra_fields=None): method get_fields (line 55) | def get_fields(self): method has (line 69) | def has(self, name): method set (line 72) | def set(self, name, value): method __setattr__ (line 80) | def __setattr__(self, name, val): method __getattr__ (line 86) | def __getattr__(self, name): method __len__ (line 91) | def __len__(self): method flatten (line 94) | def flatten(self): method to_d2_instances_list (line 104) | def to_d2_instances_list(instances_list): class Caffe2Compatible (line 144) | class Caffe2Compatible(object): method _get_tensor_mode (line 145) | def _get_tensor_mode(self): method _set_tensor_mode (line 148) | def _set_tensor_mode(self, v): class Caffe2RPN (line 157) | class Caffe2RPN(Caffe2Compatible, rpn.RPN): method forward (line 158) | def forward(self, images, features, gt_instances=None): method c2_postprocess (line 248) | def c2_postprocess(im_info, rpn_rois, rpn_roi_probs, tensor_mode): class Caffe2ROIPooler (line 264) | class Caffe2ROIPooler(Caffe2Compatible, poolers.ROIPooler): method c2_preprocess (line 266) | def c2_preprocess(box_lists): method forward (line 276) | def forward(self, x, box_lists): class Caffe2FastRCNNOutputsInference (line 331) | class Caffe2FastRCNNOutputsInference: method __init__ (line 332) | def __init__(self, tensor_mode): method __call__ (line 335) | def __call__(self, fastrcnn_outputs, score_thresh, nms_thresh, topk_pe... class Caffe2MaskRCNNInference (line 449) | class Caffe2MaskRCNNInference: method __call__ (line 450) | def __call__(self, pred_mask_logits, pred_instances): class Caffe2KeypointRCNNInference (line 461) | class Caffe2KeypointRCNNInference: method __init__ (line 462) | def __init__(self, use_heatmap_max_keypoint): method __call__ (line 465) | def __call__(self, pred_keypoint_logits, pred_instances): FILE: detectron2/export/caffe2_export.py function _export_via_onnx (line 33) | def _export_via_onnx(model, inputs): function _op_stats (line 66) | def _op_stats(net_def): function _assign_device_option (line 75) | def _assign_device_option( function export_caffe2_detection_model (line 121) | def export_caffe2_detection_model(model: torch.nn.Module, tensor_inputs:... function run_and_save_graph (line 162) | def run_and_save_graph(predict_net, init_net, tensor_inputs, graph_save_... FILE: detectron2/export/caffe2_inference.py class ProtobufModel (line 16) | class ProtobufModel(torch.nn.Module): method __init__ (line 23) | def __init__(self, predict_net, init_net): method forward (line 40) | def forward(self, inputs_dict): class ProtobufDetectionModel (line 68) | class ProtobufDetectionModel(torch.nn.Module): method __init__ (line 74) | def __init__(self, predict_net, init_net, *, convert_outputs=None): method _infer_output_devices (line 94) | def _infer_output_devices(self, inputs_dict): method _convert_inputs (line 112) | def _convert_inputs(self, batched_inputs): method forward (line 119) | def forward(self, batched_inputs): FILE: detectron2/export/caffe2_modeling.py function assemble_rcnn_outputs_by_name (line 29) | def assemble_rcnn_outputs_by_name(image_sizes, tensor_outputs, force_mas... function _cast_to_f32 (line 94) | def _cast_to_f32(f64): function set_caffe2_compatible_tensor_mode (line 98) | def set_caffe2_compatible_tensor_mode(model, enable=True): function convert_batched_inputs_to_c2_format (line 106) | def convert_batched_inputs_to_c2_format(batched_inputs, size_divisibilit... class Caffe2MetaArch (line 134) | class Caffe2MetaArch(Caffe2Compatible, torch.nn.Module): method __init__ (line 141) | def __init__(self, cfg, torch_model): method get_caffe2_inputs (line 153) | def get_caffe2_inputs(self, batched_inputs): method encode_additional_info (line 177) | def encode_additional_info(self, predict_net, init_net): method forward (line 183) | def forward(self, inputs): method _caffe2_preprocess_image (line 198) | def _caffe2_preprocess_image(self, inputs): method get_outputs_converter (line 215) | def get_outputs_converter(predict_net, init_net): class Caffe2GeneralizedRCNN (line 243) | class Caffe2GeneralizedRCNN(Caffe2MetaArch): method __init__ (line 244) | def __init__(self, cfg, torch_model): method encode_additional_info (line 251) | def encode_additional_info(self, predict_net, init_net): method forward (line 260) | def forward(self, inputs): method get_outputs_converter (line 271) | def get_outputs_converter(predict_net, init_net): class Caffe2PanopticFPN (line 280) | class Caffe2PanopticFPN(Caffe2MetaArch): method __init__ (line 281) | def __init__(self, cfg, torch_model): method forward (line 289) | def forward(self, inputs): method encode_additional_info (line 304) | def encode_additional_info(self, predict_net, init_net): method get_outputs_converter (line 334) | def get_outputs_converter(predict_net, init_net): class Caffe2RetinaNet (line 375) | class Caffe2RetinaNet(Caffe2MetaArch): method __init__ (line 376) | def __init__(self, cfg, torch_model): method forward (line 381) | def forward(self, inputs): method encode_additional_info (line 402) | def encode_additional_info(self, predict_net, init_net): method _encode_anchor_generator_cfg (line 433) | def _encode_anchor_generator_cfg(self, predict_net): method get_outputs_converter (line 443) | def get_outputs_converter(predict_net, init_net): FILE: detectron2/export/patcher.py class GenericMixin (line 22) | class GenericMixin(object): class Caffe2CompatibleConverter (line 26) | class Caffe2CompatibleConverter(object): method __init__ (line 32) | def __init__(self, replaceCls): method create_from (line 35) | def create_from(self, module): function patch (line 57) | def patch(model, target, updater, *args, **kwargs): function patch_generalized_rcnn (line 70) | def patch_generalized_rcnn(model): function mock_fastrcnn_outputs_inference (line 79) | def mock_fastrcnn_outputs_inference(tensor_mode, check=True): function mock_mask_rcnn_inference (line 92) | def mock_mask_rcnn_inference(tensor_mode, patched_module, check=True): function mock_keypoint_rcnn_inference (line 102) | def mock_keypoint_rcnn_inference(tensor_mode, patched_module, use_heatma... class ROIHeadsPatcher (line 112) | class ROIHeadsPatcher: method __init__ (line 113) | def __init__(self, cfg, heads): method mock_roi_heads (line 119) | def mock_roi_heads(self, tensor_mode=True): FILE: detectron2/export/shared.py function to_device (line 25) | def to_device(t, device_str): function BilinearInterpolation (line 48) | def BilinearInterpolation(tensor_in, up_scale): function onnx_compatibale_interpolate (line 82) | def onnx_compatibale_interpolate( function mock_torch_nn_functional_interpolate (line 116) | def mock_torch_nn_functional_interpolate(): class ScopedWS (line 129) | class ScopedWS(object): method __init__ (line 130) | def __init__(self, ws_name, is_reset, is_cleanup=False): method __enter__ (line 136) | def __enter__(self): method __exit__ (line 145) | def __exit__(self, *args): function fetch_any_blob (line 152) | def fetch_any_blob(name): function get_pb_arg (line 167) | def get_pb_arg(pb, arg_name): function get_pb_arg_valf (line 174) | def get_pb_arg_valf(pb, arg_name, default_val): function get_pb_arg_floats (line 179) | def get_pb_arg_floats(pb, arg_name, default_val): function get_pb_arg_ints (line 184) | def get_pb_arg_ints(pb, arg_name, default_val): function get_pb_arg_vali (line 189) | def get_pb_arg_vali(pb, arg_name, default_val): function get_pb_arg_vals (line 194) | def get_pb_arg_vals(pb, arg_name, default_val): function get_pb_arg_valstrings (line 199) | def get_pb_arg_valstrings(pb, arg_name, default_val): function check_set_pb_arg (line 204) | def check_set_pb_arg(pb, arg_name, arg_attr, arg_value, allow_override=F... function _create_const_fill_op_from_numpy (line 222) | def _create_const_fill_op_from_numpy(name, tensor, device_option=None): function _create_const_fill_op_from_c2_int8_tensor (line 243) | def _create_const_fill_op_from_c2_int8_tensor(name, int8_tensor): function create_const_fill_op (line 265) | def create_const_fill_op( function construct_init_net_from_params (line 287) | def construct_init_net_from_params( function get_producer_map (line 311) | def get_producer_map(ssa): function get_consumer_map (line 324) | def get_consumer_map(ssa): function get_params_from_init_net (line 337) | def get_params_from_init_net( function _updater_raise (line 366) | def _updater_raise(op, input_types, output_types): function _generic_status_identifier (line 373) | def _generic_status_identifier( function infer_device_type (line 445) | def infer_device_type( function _modify_blob_names (line 488) | def _modify_blob_names(ops, blob_rename_f): function _rename_blob (line 504) | def _rename_blob(name, blob_sizes, blob_ranges): function save_graph (line 520) | def save_graph(net, file_name, graph_name="net", op_only=True, blob_size... function save_graph_base (line 525) | def save_graph_base(net, file_name, graph_name="net", op_only=True, blob... function group_norm_replace_aten_with_caffe2 (line 560) | def group_norm_replace_aten_with_caffe2(predict_net: caffe2_pb2.NetDef): function alias (line 589) | def alias(x, name, is_backward=False): function fuse_alias_placeholder (line 596) | def fuse_alias_placeholder(predict_net, init_net): class IllegalGraphTransformError (line 624) | class IllegalGraphTransformError(ValueError): function _rename_versioned_blob_in_proto (line 628) | def _rename_versioned_blob_in_proto( function rename_op_input (line 659) | def rename_op_input( function rename_op_output (line 726) | def rename_op_output(predict_net: caffe2_pb2.NetDef, op_id: int, output_... function get_sub_graph_external_input_output (line 747) | def get_sub_graph_external_input_output( class DiGraph (line 779) | class DiGraph: method __init__ (line 782) | def __init__(self): method add_edge (line 786) | def add_edge(self, u, v): method get_all_paths (line 792) | def get_all_paths(self, s, d): method from_ssa (line 813) | def from_ssa(ssa): function _get_dependency_chain (line 822) | def _get_dependency_chain(ssa, versioned_target, versioned_source): function identify_reshape_sub_graph (line 852) | def identify_reshape_sub_graph(predict_net: caffe2_pb2.NetDef,) -> List[... function remove_reshape_for_fc (line 879) | def remove_reshape_for_fc(predict_net, params): function fuse_copy_between_cpu_and_gpu (line 949) | def fuse_copy_between_cpu_and_gpu(predict_net: caffe2_pb2.NetDef): function remove_dead_end_ops (line 1007) | def remove_dead_end_ops(net_def: caffe2_pb2.NetDef): FILE: detectron2/layers/aspp.py class ASPP (line 14) | class ASPP(nn.Module): method __init__ (line 19) | def __init__( method forward (line 129) | def forward(self, x): FILE: detectron2/layers/batch_norm.py class FrozenBatchNorm2d (line 13) | class FrozenBatchNorm2d(nn.Module): method __init__ (line 35) | def __init__(self, num_features, eps=1e-5): method forward (line 44) | def forward(self, x): method _load_from_state_dict (line 67) | def _load_from_state_dict( method __repr__ (line 84) | def __repr__(self): method convert_frozen_batchnorm (line 88) | def convert_frozen_batchnorm(cls, module): function get_norm (line 121) | def get_norm(norm, out_channels): class NaiveSyncBatchNorm (line 152) | class NaiveSyncBatchNorm(BatchNorm2d): method __init__ (line 180) | def __init__(self, *args, stats_mode="", **kwargs): method forward (line 185) | def forward(self, input): class CycleBatchNormList (line 233) | class CycleBatchNormList(nn.ModuleList): method __init__ (line 249) | def __init__(self, length: int, bn_class=nn.BatchNorm2d, **kwargs): method forward (line 265) | def forward(self, x): method extra_repr (line 276) | def extra_repr(self): class LayerNorm (line 280) | class LayerNorm(nn.Module): method __init__ (line 288) | def __init__(self, normalized_shape, eps=1e-6): method forward (line 295) | def forward(self, x): FILE: detectron2/layers/blocks.py class CNNBlockBase (line 16) | class CNNBlockBase(nn.Module): method __init__ (line 29) | def __init__(self, in_channels, out_channels, stride): method freeze (line 43) | def freeze(self): class DepthwiseSeparableConv2d (line 58) | class DepthwiseSeparableConv2d(nn.Module): method __init__ (line 66) | def __init__( method forward (line 110) | def forward(self, x): FILE: detectron2/layers/csrc/ROIAlignRotated/ROIAlignRotated.h function namespace (line 5) | namespace detectron2 { FILE: detectron2/layers/csrc/ROIAlignRotated/ROIAlignRotated_cpu.cpp type detectron2 (line 12) | namespace detectron2 { type PreCalc (line 16) | struct PreCalc { function pre_calc_for_bilinear_interpolate (line 28) | void pre_calc_for_bilinear_interpolate( function bilinear_interpolate_gradient (line 132) | void bilinear_interpolate_gradient( function add (line 195) | inline void add(T* address, const T& val) { function ROIAlignRotatedForward (line 202) | void ROIAlignRotatedForward( function ROIAlignRotatedBackward (line 313) | void ROIAlignRotatedBackward( function ROIAlignRotated_forward_cpu (line 418) | at::Tensor ROIAlignRotated_forward_cpu( function ROIAlignRotated_backward_cpu (line 466) | at::Tensor ROIAlignRotated_backward_cpu( FILE: detectron2/layers/csrc/box_iou_rotated/box_iou_rotated.h function namespace (line 5) | namespace detectron2 { FILE: detectron2/layers/csrc/box_iou_rotated/box_iou_rotated_cpu.cpp type detectron2 (line 5) | namespace detectron2 { function box_iou_rotated_cpu_kernel (line 8) | void box_iou_rotated_cpu_kernel( function box_iou_rotated_cpu (line 23) | at::Tensor box_iou_rotated_cpu( FILE: detectron2/layers/csrc/box_iou_rotated/box_iou_rotated_utils.h function namespace (line 17) | namespace detectron2 { FILE: detectron2/layers/csrc/cocoeval/cocoeval.cpp type detectron2 (line 10) | namespace detectron2 { type COCOeval (line 12) | namespace COCOeval { function SortInstancesByDetectionScore (line 18) | void SortInstancesByDetectionScore( function SortInstancesByIgnore (line 34) | void SortInstancesByIgnore( function MatchDetectionsToGroundTruth (line 61) | void MatchDetectionsToGroundTruth( function EvaluateImages (line 142) | std::vector EvaluateImages( function list_to_vec (line 203) | std::vector list_to_vec(const py::list& l) { function BuildSortedDetectionList (line 223) | int BuildSortedDetectionList( function ComputePrecisionRecallCurve (line 284) | void ComputePrecisionRecallCurve( function Accumulate (line 372) | py::dict Accumulate( FILE: detectron2/layers/csrc/cocoeval/cocoeval.h function namespace (line 12) | namespace detectron2 { FILE: detectron2/layers/csrc/deformable/deform_conv.h function namespace (line 5) | namespace detectron2 { FILE: detectron2/layers/csrc/nms_rotated/nms_rotated.h function namespace (line 5) | namespace detectron2 { FILE: detectron2/layers/csrc/nms_rotated/nms_rotated_cpu.cpp type detectron2 (line 5) | namespace detectron2 { function nms_rotated_cpu_kernel (line 8) | at::Tensor nms_rotated_cpu_kernel( function nms_rotated_cpu (line 62) | at::Tensor nms_rotated_cpu( FILE: detectron2/layers/csrc/vision.cpp type detectron2 (line 10) | namespace detectron2 { function get_cuda_version (line 16) | std::string get_cuda_version() { function has_cuda (line 41) | bool has_cuda() { function get_compiler_version (line 51) | std::string get_compiler_version() { function PYBIND11_MODULE (line 77) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) { function TORCH_LIBRARY (line 111) | TORCH_LIBRARY(detectron2, m) { FILE: detectron2/layers/deform_conv.py class _DeformConv (line 16) | class _DeformConv(Function): method forward (line 18) | def forward( method backward (line 85) | def backward(ctx, grad_output): method _output_size (line 146) | def _output_size(input, weight, padding, dilation, stride): method _cal_im2col_step (line 165) | def _cal_im2col_step(input_size, default_size): class _ModulatedDeformConv (line 187) | class _ModulatedDeformConv(Function): method forward (line 189) | def forward( method backward (line 246) | def backward(ctx, grad_output): method _infer_shape (line 298) | def _infer_shape(ctx, input, weight): class DeformConv (line 316) | class DeformConv(nn.Module): method __init__ (line 317) | def __init__( method forward (line 369) | def forward(self, x, offset): method extra_repr (line 400) | def extra_repr(self): class ModulatedDeformConv (line 413) | class ModulatedDeformConv(nn.Module): method __init__ (line 414) | def __init__( method forward (line 463) | def forward(self, x, offset, mask): method extra_repr (line 492) | def extra_repr(self): FILE: detectron2/layers/losses.py function diou_loss (line 5) | def diou_loss( function ciou_loss (line 66) | def ciou_loss( FILE: detectron2/layers/mask_ops.py function _do_paste_mask (line 17) | def _do_paste_mask(masks, boxes, img_h: int, img_w: int, skip_empty: boo... function paste_masks_in_image (line 74) | def paste_masks_in_image( function paste_mask_in_image_old (line 155) | def paste_mask_in_image_old(mask, box, img_h, img_w, threshold): function pad_masks (line 219) | def pad_masks(masks, padding): function scale_boxes (line 237) | def scale_boxes(boxes, scale): function _paste_masks_tensor_shape (line 264) | def _paste_masks_tensor_shape( FILE: detectron2/layers/nms.py function batched_nms (line 9) | def batched_nms( function nms_rotated (line 25) | def nms_rotated(boxes, scores, iou_threshold): function batched_nms_rotated (line 91) | def batched_nms_rotated(boxes, scores, idxs, iou_threshold): FILE: detectron2/layers/roi_align.py class ROIAlign (line 7) | class ROIAlign(nn.Module): method __init__ (line 8) | def __init__(self, output_size, spatial_scale, sampling_ratio, aligned... method forward (line 49) | def forward(self, input, rois): method __repr__ (line 67) | def __repr__(self): FILE: detectron2/layers/roi_align_rotated.py class _ROIAlignRotated (line 9) | class _ROIAlignRotated(Function): method forward (line 11) | def forward(ctx, input, roi, output_size, spatial_scale, sampling_ratio): method backward (line 24) | def backward(ctx, grad_output): class ROIAlignRotated (line 48) | class ROIAlignRotated(nn.Module): method __init__ (line 49) | def __init__(self, output_size, spatial_scale, sampling_ratio): method forward (line 69) | def forward(self, input, rois): method __repr__ (line 85) | def __repr__(self): FILE: detectron2/layers/rotated_boxes.py function pairwise_iou_rotated (line 6) | def pairwise_iou_rotated(boxes1, boxes2): FILE: detectron2/layers/shape_spec.py class ShapeSpec (line 8) | class ShapeSpec: FILE: detectron2/layers/wrappers.py function shapes_to_tensor (line 17) | def shapes_to_tensor(x: List[int], device: Optional[torch.device] = None... function cat (line 39) | def cat(tensors: List[torch.Tensor], dim: int = 0): function empty_input_loss_func_wrapper (line 49) | def empty_input_loss_func_wrapper(loss_func): class _NewEmptyTensorOp (line 64) | class _NewEmptyTensorOp(torch.autograd.Function): method forward (line 66) | def forward(ctx, x, new_shape): method backward (line 71) | def backward(ctx, grad): class Conv2d (line 76) | class Conv2d(torch.nn.Conv2d): method __init__ (line 81) | def __init__(self, *args, **kwargs): method forward (line 98) | def forward(self, x): function nonzero_tuple (line 129) | def nonzero_tuple(x): function move_device_like (line 143) | def move_device_like(src: torch.Tensor, dst: torch.Tensor) -> torch.Tensor: FILE: detectron2/modeling/anchor_generator.py class BufferList (line 18) | class BufferList(nn.Module): method __init__ (line 23) | def __init__(self, buffers=None): method extend (line 28) | def extend(self, buffers): method __len__ (line 34) | def __len__(self): method __iter__ (line 37) | def __iter__(self): function _create_grid_offsets (line 41) | def _create_grid_offsets(size, stride, device): class DefaultAnchorGenerator (line 54) | class DefaultAnchorGenerator(nn.Module): method __init__ (line 59) | def __init__(self, cfg, input_shape: List[ShapeSpec]): method _calculate_anchors (line 82) | def _calculate_anchors(self, sizes, aspect_ratios): method box_dim (line 100) | def box_dim(self): method num_cell_anchors (line 108) | def num_cell_anchors(self): method grid_anchors (line 121) | def grid_anchors(self, grid_sizes): method generate_cell_anchors (line 131) | def generate_cell_anchors(self, sizes=(32, 64, 128, 256, 512), aspect_... method forward (line 168) | def forward(self, features): class RotatedAnchorGenerator (line 191) | class RotatedAnchorGenerator(nn.Module): method __init__ (line 196) | def __init__(self, cfg, input_shape: List[ShapeSpec]): method _calculate_anchors (line 208) | def _calculate_anchors(self, sizes, aspect_ratios, angles, feature_str... method box_dim (line 250) | def box_dim(self): method num_cell_anchors (line 258) | def num_cell_anchors(self): method grid_anchors (line 272) | def grid_anchors(self, grid_sizes): method generate_cell_anchors (line 283) | def generate_cell_anchors( method forward (line 322) | def forward(self, features): function build_anchor_generator (line 345) | def build_anchor_generator(cfg, input_shape): FILE: detectron2/modeling/backbone/backbone.py class Backbone (line 10) | class Backbone(nn.Module, metaclass=ABCMeta): method __init__ (line 15) | def __init__(self): method forward (line 22) | def forward(self): method size_divisibility (line 32) | def size_divisibility(self): method output_shape (line 42) | def output_shape(self): method out_features (line 58) | def out_features(self): method out_feature_strides (line 63) | def out_feature_strides(self): method out_feature_channels (line 68) | def out_feature_channels(self): FILE: detectron2/modeling/backbone/build.py function build_backbone (line 20) | def build_backbone(cfg, input_shape=None): FILE: detectron2/modeling/backbone/fpn.py class FPN (line 16) | class FPN(Backbone): method __init__ (line 22) | def __init__( method size_divisibility (line 105) | def size_divisibility(self): method forward (line 108) | def forward(self, x): method output_shape (line 145) | def output_shape(self): function _assert_strides_are_log2_contiguous (line 154) | def _assert_strides_are_log2_contiguous(strides): class LastLevelMaxPool (line 164) | class LastLevelMaxPool(nn.Module): method __init__ (line 170) | def __init__(self): method forward (line 175) | def forward(self, x): class LastLevelP6P7 (line 179) | class LastLevelP6P7(nn.Module): method __init__ (line 185) | def __init__(self, in_channels, out_channels): method forward (line 194) | def forward(self, c5): function build_resnet_fpn_backbone (line 201) | def build_resnet_fpn_backbone(cfg, input_shape: ShapeSpec): function build_retinanet_resnet_fpn_backbone (line 224) | def build_retinanet_resnet_fpn_backbone(cfg, input_shape: ShapeSpec): FILE: detectron2/modeling/backbone/resnet.py class ResNetBlockBase (line 31) | class ResNetBlockBase(nn.Module): method __init__ (line 32) | def __init__(self, in_channels, out_channels, stride): method freeze (line 46) | def freeze(self): class BottleneckBlock (line 53) | class BottleneckBlock(ResNetBlockBase): method __init__ (line 54) | def __init__( method forward (line 138) | def forward(self, x): class DeformBottleneckBlock (line 157) | class DeformBottleneckBlock(ResNetBlockBase): method __init__ (line 158) | def __init__( method forward (line 245) | def forward(self, x): function make_stage (line 272) | def make_stage(block_class, num_blocks, first_stride, **kwargs): class BasicStem (line 292) | class BasicStem(nn.Module): method __init__ (line 293) | def __init__(self, in_channels=3, out_channels=64, norm="BN"): method forward (line 312) | def forward(self, x): method out_channels (line 319) | def out_channels(self): method stride (line 323) | def stride(self): class ResNet (line 327) | class ResNet(Backbone): method __init__ (line 328) | def __init__(self, stem, stages, num_classes=None, out_features=None): method forward (line 379) | def forward(self, x): method output_shape (line 395) | def output_shape(self): function build_resnet_backbone (line 405) | def build_resnet_backbone(cfg, input_shape): FILE: detectron2/modeling/box_regression.py class Box2BoxTransform (line 14) | class Box2BoxTransform(object): method __init__ (line 21) | def __init__(self, weights, scale_clamp=_DEFAULT_SCALE_CLAMP): method get_deltas (line 34) | def get_deltas(self, src_boxes, target_boxes): method trans_light (line 68) | def trans_light(self, src_boxes): method apply_deltas (line 74) | def apply_deltas(self, deltas, boxes): class Box2BoxTransformRotated (line 115) | class Box2BoxTransformRotated(object): method __init__ (line 124) | def __init__(self, weights, scale_clamp=_DEFAULT_SCALE_CLAMP): method get_deltas (line 136) | def get_deltas(self, src_boxes, target_boxes): method apply_deltas (line 177) | def apply_deltas(self, deltas, boxes): FILE: detectron2/modeling/matcher.py class Matcher (line 5) | class Matcher(object): method __init__ (line 21) | def __init__(self, thresholds, labels, allow_low_quality_matches=False): method __call__ (line 54) | def __call__(self, match_quality_matrix): method set_low_quality_matches_ (line 95) | def set_low_quality_matches_(self, match_labels, match_quality_matrix): FILE: detectron2/modeling/meta_arch/LISA_meta_arch.py class LISARCNN (line 19) | class LISARCNN(GeneralizedRCNN): method __init__ (line 21) | def __init__(self,cfg): method forward (line 26) | def forward(self, batched_inputs): method inference (line 64) | def inference(self, batched_inputs, detected_instances=None, do_postpr... FILE: detectron2/modeling/meta_arch/build.py function build_model (line 13) | def build_model(cfg): FILE: detectron2/modeling/meta_arch/panoptic_fpn.py class PanopticFPN (line 20) | class PanopticFPN(nn.Module): method __init__ (line 25) | def __init__(self, cfg): method forward (line 50) | def forward(self, batched_inputs): function combine_semantic_and_instance_outputs (line 131) | def combine_semantic_and_instance_outputs( FILE: detectron2/modeling/meta_arch/rcnn.py class GeneralizedRCNN (line 19) | class GeneralizedRCNN(nn.Module): method __init__ (line 27) | def __init__(self, cfg): method forward (line 42) | def forward(self, batched_inputs): method inference (line 95) | def inference(self, batched_inputs, detected_instances=None, do_postpr... method preprocess_image (line 142) | def preprocess_image(self, batched_inputs): class ProposalNetwork (line 153) | class ProposalNetwork(nn.Module): method __init__ (line 154) | def __init__(self, cfg): method forward (line 166) | def forward(self, batched_inputs): FILE: detectron2/modeling/meta_arch/retinanet.py function permute_to_N_HWA_K (line 23) | def permute_to_N_HWA_K(tensor, K): function permute_all_cls_and_box_to_N_HWA_K_and_concat (line 35) | def permute_all_cls_and_box_to_N_HWA_K_and_concat(box_cls, box_delta, nu... class RetinaNet (line 57) | class RetinaNet(nn.Module): method __init__ (line 62) | def __init__(self, cfg): method forward (line 101) | def forward(self, batched_inputs): method losses (line 150) | def losses(self, gt_classes, gt_anchors_deltas, pred_class_logits, pre... method get_ground_truth (line 200) | def get_ground_truth(self, anchors, targets): method inference (line 258) | def inference(self, box_cls, box_delta, anchors, images): method inference_single_image (line 287) | def inference_single_image(self, box_cls, box_delta, anchors, image_si... method preprocess_image (line 349) | def preprocess_image(self, batched_inputs): class RetinaNetHead (line 359) | class RetinaNetHead(nn.Module): method __init__ (line 365) | def __init__(self, cfg, input_shape: List[ShapeSpec]): method forward (line 409) | def forward(self, features): FILE: detectron2/modeling/meta_arch/semantic_seg.py class SemanticSegmentor (line 28) | class SemanticSegmentor(nn.Module): method __init__ (line 33) | def __init__(self, cfg): method forward (line 47) | def forward(self, batched_inputs): function build_sem_seg_head (line 93) | def build_sem_seg_head(cfg, input_shape): class SemSegFPNHead (line 102) | class SemSegFPNHead(nn.Module): method __init__ (line 109) | def __init__(self, cfg, input_shape: Dict[str, ShapeSpec]): method forward (line 153) | def forward(self, features, targets=None): FILE: detectron2/modeling/poolers.py function assign_boxes_to_levels (line 13) | def assign_boxes_to_levels(box_lists, min_level, max_level, canonical_bo... function convert_boxes_to_pooler_format (line 45) | def convert_boxes_to_pooler_format(box_lists): class ROIPooler (line 82) | class ROIPooler(nn.Module): method __init__ (line 88) | def __init__( method forward (line 160) | def forward(self, x, box_lists): FILE: detectron2/modeling/postprocessing.py function decode (line 11) | def decode(segm): function encode (line 15) | def encode(segm): function detector_postprocess (line 19) | def detector_postprocess(results, output_height, output_width, mask_thre... function sem_seg_postprocess (line 67) | def sem_seg_postprocess(result, img_size, output_height, output_width): function takeTwo (line 92) | def takeTwo(elm): function compute_iou (line 104) | def compute_iou(rec1, rec2): function box_combine (line 117) | def box_combine(o, s, box1, box2): function compute_direction (line 133) | def compute_direction(box1,box2): function rect_distance (line 136) | def rect_distance(a, b): function dist (line 163) | def dist(a, b): function matchor (line 167) | def matchor(instance, association): function combine_association (line 246) | def combine_association(instance, association): FILE: detectron2/modeling/proposal_generator/LISA_rpn.py function build_rpn_head (line 25) | def build_rpn_head(cfg, input_shape,shadow_object_part=False): class LISARPNHead (line 34) | class LISARPNHead(StandardRPNHead): method __init__ (line 35) | def __init__(self, cfg, input_shape: List[ShapeSpec], shadow_object_pa... method forward (line 47) | def forward(self, features): function build_proposal_generator (line 73) | def build_proposal_generator(cfg, input_shape, **args): class LISARPN (line 85) | class LISARPN(RPN): method __init__ (line 87) | def __init__(self, cfg, input_shape: Dict[str, ShapeSpec], shadow_obje... method forward (line 93) | def forward(self, images, features, gt_instances=None, pre_proposals=N... FILE: detectron2/modeling/proposal_generator/build.py function build_proposal_generator (line 15) | def build_proposal_generator(cfg, input_shape): FILE: detectron2/modeling/proposal_generator/proposal_utils.py function add_ground_truth_to_proposals (line 8) | def add_ground_truth_to_proposals(gt_boxes, proposals, gt_light =None): function add_ground_truth_to_proposals_single_image (line 35) | def add_ground_truth_to_proposals_single_image(gt_boxes, proposals,gt_li... FILE: detectron2/modeling/proposal_generator/rpn.py function build_rpn_head (line 23) | def build_rpn_head(cfg, input_shape): class StandardRPNHead (line 32) | class StandardRPNHead(nn.Module): method __init__ (line 40) | def __init__(self, cfg, input_shape: List[ShapeSpec]): method forward (line 71) | def forward(self, features): class RPN (line 86) | class RPN(nn.Module): method __init__ (line 91) | def __init__(self, cfg, input_shape: Dict[str, ShapeSpec]): method forward (line 124) | def forward(self, images, features, gt_instances=None): FILE: detectron2/modeling/proposal_generator/rpn_outputs.py function find_top_rpn_proposals (line 51) | def find_top_rpn_proposals( function rpn_losses (line 153) | def rpn_losses( class RPNOutputs (line 192) | class RPNOutputs(object): method __init__ (line 193) | def __init__( method _get_ground_truth (line 249) | def _get_ground_truth(self): method losses (line 291) | def losses(self): method predict_proposals (line 393) | def predict_proposals(self): method predict_objectness_logits (line 426) | def predict_objectness_logits(self): FILE: detectron2/modeling/proposal_generator/rrpn.py class RRPN (line 17) | class RRPN(RPN): method __init__ (line 26) | def __init__(self, cfg, input_shape: Dict[str, ShapeSpec]): method forward (line 30) | def forward(self, images, features, gt_instances=None): FILE: detectron2/modeling/proposal_generator/rrpn_outputs.py function find_top_rrpn_proposals (line 41) | def find_top_rrpn_proposals( class RRPNOutputs (line 143) | class RRPNOutputs(RPNOutputs): method __init__ (line 144) | def __init__( method _get_ground_truth (line 200) | def _get_ground_truth(self): FILE: detectron2/modeling/roi_heads/LISA_rcnn.py class RelationROIHeads (line 24) | class RelationROIHeads(StandardROIHeads): method _init_box_head (line 35) | def _init_box_head(self,cfg): method forward (line 71) | def forward(self,images, features, relation_proposals, proposals, rela... method _forward_relation_box (line 113) | def _forward_relation_box(self, features, relation_proposals): method label_and_sample_proposals (line 140) | def label_and_sample_proposals(self, proposals, targets, isrelation = ... FILE: detectron2/modeling/roi_heads/box_head.py class FastRCNNConvFCHead (line 20) | class FastRCNNConvFCHead(nn.Module): method __init__ (line 26) | def __init__(self, cfg, input_shape: ShapeSpec): method forward (line 73) | def forward(self, x): method output_size (line 84) | def output_size(self): function build_box_head (line 88) | def build_box_head(cfg, input_shape): FILE: detectron2/modeling/roi_heads/cascade_rcnn.py class _ScaleGradient (line 18) | class _ScaleGradient(Function): method forward (line 20) | def forward(ctx, input, scale): method backward (line 25) | def backward(ctx, grad_output): class CascadeROIHeads (line 30) | class CascadeROIHeads(StandardROIHeads): method _init_box_head (line 31) | def _init_box_head(self, cfg): method forward (line 83) | def forward(self, images, features, proposals, targets=None): method _forward_box (line 101) | def _forward_box(self, features, proposals, targets=None): method _match_and_label_boxes (line 144) | def _match_and_label_boxes(self, proposals, stage, targets): method _run_stage (line 193) | def _run_stage(self, features, proposals, stage): method _create_proposals_from_boxes (line 222) | def _create_proposals_from_boxes(self, boxes, image_sizes): FILE: detectron2/modeling/roi_heads/fast_rcnn.py function fast_rcnn_losses (line 41) | def fast_rcnn_losses( function fast_rcnn_inference (line 155) | def fast_rcnn_inference(boxes, scores, image_shapes, score_thresh, nms_t... function fast_rcnn_inference_single_image (line 199) | def fast_rcnn_inference_single_image( class FastRCNNOutputs (line 256) | class FastRCNNOutputs(object): method __init__ (line 261) | def __init__( method _log_accuracy (line 303) | def _log_accuracy(self): method losses (line 326) | def losses(self): method predict_boxes (line 357) | def predict_boxes(self): method predict_light (line 368) | def predict_light(self,light): method predict_probs (line 371) | def predict_probs(self): method inference (line 382) | def inference(self, score_thresh, nms_thresh, topk_per_image): class FastRCNNOutputLayers (line 404) | class FastRCNNOutputLayers(nn.Module): method __init__ (line 411) | def __init__(self, input_size, num_classes, cls_agnostic_bbox_reg, box... method forward (line 436) | def forward(self, x): class LightdirectionOutputLayer (line 443) | class LightdirectionOutputLayer(nn.Module): method __init__ (line 445) | def __init__(self, input_size, box_dim =4): method forward (line 456) | def forward(self,x): FILE: detectron2/modeling/roi_heads/keypoint_head.py function build_keypoint_head (line 21) | def build_keypoint_head(cfg, input_shape): function keypoint_rcnn_loss (line 29) | def keypoint_rcnn_loss(pred_keypoint_logits, instances, normalizer): function keypoint_rcnn_inference (line 92) | def keypoint_rcnn_inference(pred_keypoint_logits, pred_instances): class KRCNNConvDeconvUpsampleHead (line 122) | class KRCNNConvDeconvUpsampleHead(nn.Module): method __init__ (line 128) | def __init__(self, cfg, input_shape: ShapeSpec): method forward (line 167) | def forward(self, x): FILE: detectron2/modeling/roi_heads/mask_head.py function mask_rcnn_loss (line 20) | def mask_rcnn_loss(pred_mask_logits, instances): function mask_rcnn_inference (line 95) | def mask_rcnn_inference(pred_mask_logits, pred_instances): class MaskRCNNConvUpsampleHead (line 137) | class MaskRCNNConvUpsampleHead(nn.Module): method __init__ (line 142) | def __init__(self, cfg, input_shape: ShapeSpec): method forward (line 194) | def forward(self, x): function build_mask_head (line 201) | def build_mask_head(cfg, input_shape): FILE: detectron2/modeling/roi_heads/roi_heads.py function build_roi_heads (line 37) | def build_roi_heads(cfg, input_shape): function select_foreground_proposals (line 45) | def select_foreground_proposals(proposals, bg_label): function select_proposals_with_visible_keypoints (line 75) | def select_proposals_with_visible_keypoints(proposals): class ROIHeads (line 116) | class ROIHeads(torch.nn.Module): method __init__ (line 126) | def __init__(self, cfg, input_shape: Dict[str, ShapeSpec]): method label_and_sample_proposals (line 155) | def label_and_sample_proposals(self, proposals, targets): method forward (line 253) | def forward(self, images, features, proposals, targets=None): class Res5ROIHeads (line 283) | class Res5ROIHeads(ROIHeads): method __init__ (line 290) | def __init__(self, cfg, input_shape): method _build_res5_block (line 322) | def _build_res5_block(self, cfg): method _shared_roi_transform (line 348) | def _shared_roi_transform(self, features, boxes): method forward (line 352) | def forward(self, images, features, proposals, targets=None): method forward_with_given_boxes (line 401) | def forward_with_given_boxes(self, features, instances): class StandardROIHeads (line 427) | class StandardROIHeads(ROIHeads): method __init__ (line 439) | def __init__(self, cfg, input_shape): method _init_box_head (line 445) | def _init_box_head(self, cfg): method _init_mask_head (line 476) | def _init_mask_head(self, cfg): method _init_keypoint_head (line 499) | def _init_keypoint_head(self, cfg): method forward (line 524) | def forward(self, images, features, proposals, targets=None): method forward_with_given_boxes (line 549) | def forward_with_given_boxes(self, features, instances): method _forward_box (line 575) | def _forward_box(self, features, proposals): method _forward_mask (line 610) | def _forward_mask(self, features, instances): method _forward_keypoint (line 641) | def _forward_keypoint(self, features, instances): class RROIHeads (line 690) | class RROIHeads(StandardROIHeads): method __init__ (line 696) | def __init__(self, cfg, input_shape: Dict[str, ShapeSpec]): method _init_box_head (line 702) | def _init_box_head(self, cfg): method label_and_sample_proposals (line 735) | def label_and_sample_proposals(self, proposals, targets): FILE: detectron2/modeling/roi_heads/rotated_fast_rcnn.py function fast_rcnn_inference_rotated (line 46) | def fast_rcnn_inference_rotated( function fast_rcnn_inference_single_image_rotated (line 83) | def fast_rcnn_inference_single_image_rotated( class RotatedFastRCNNOutputs (line 129) | class RotatedFastRCNNOutputs(FastRCNNOutputs): method inference (line 134) | def inference(self, score_thresh, nms_thresh, topk_per_image): class RROIHeads (line 154) | class RROIHeads(StandardROIHeads): method __init__ (line 160) | def __init__(self, cfg, input_shape: Dict[str, ShapeSpec]): method _init_box_head (line 169) | def _init_box_head(self, cfg): method label_and_sample_proposals (line 204) | def label_and_sample_proposals(self, proposals, targets): method _forward_box (line 265) | def _forward_box(self, features, proposals): FILE: detectron2/modeling/sampling.py function subsample_labels (line 7) | def subsample_labels(labels, num_samples, positive_fraction, bg_label): FILE: detectron2/modeling/test_time_augmentation.py class DatasetMapperTTA (line 20) | class DatasetMapperTTA: method __init__ (line 29) | def __init__(self, cfg): method __call__ (line 35) | def __call__(self, dataset_dict): class GeneralizedRCNNWithTTA (line 69) | class GeneralizedRCNNWithTTA(nn.Module): method __init__ (line 75) | def __init__(self, cfg, model, tta_mapper=None, batch_size=3): method _turn_off_roi_head (line 103) | def _turn_off_roi_head(self, attr): method _batch_inference (line 124) | def _batch_inference(self, batched_inputs, detected_instances=None, do... method __call__ (line 150) | def __call__(self, batched_inputs): method _inference_one_image (line 156) | def _inference_one_image(self, input): FILE: detectron2/solver/build.py function build_optimizer (line 10) | def build_optimizer(cfg: CfgNode, model: torch.nn.Module) -> torch.optim... function build_lr_scheduler (line 35) | def build_lr_scheduler( FILE: detectron2/solver/lr_scheduler.py class WarmupMultiStepLR (line 16) | class WarmupMultiStepLR(torch.optim.lr_scheduler._LRScheduler): method __init__ (line 17) | def __init__( method get_lr (line 38) | def get_lr(self) -> List[float]: method _compute_values (line 47) | def _compute_values(self) -> List[float]: class WarmupCosineLR (line 52) | class WarmupCosineLR(torch.optim.lr_scheduler._LRScheduler): method __init__ (line 53) | def __init__( method get_lr (line 68) | def get_lr(self) -> List[float]: method _compute_values (line 85) | def _compute_values(self) -> List[float]: function _get_warmup_factor_at_iter (line 90) | def _get_warmup_factor_at_iter( FILE: detectron2/structures/boxes.py class BoxMode (line 13) | class BoxMode(Enum): method convert (line 32) | def convert(box: _RawBoxType, from_mode: "BoxMode", to_mode: "BoxMode"... class Boxes (line 71) | class Boxes: method __init__ (line 85) | def __init__(self, tensor: torch.Tensor): method clone (line 98) | def clone(self) -> "Boxes": method to (line 107) | def to(self, device: str) -> "Boxes": method area (line 110) | def area(self) -> torch.Tensor: method clip (line 121) | def clip(self, box_size: BoxSizeType) -> None: method nonempty (line 136) | def nonempty(self, threshold: int = 0) -> torch.Tensor: method __getitem__ (line 152) | def __getitem__(self, item: Union[int, slice, torch.BoolTensor]) -> "B... method __len__ (line 172) | def __len__(self) -> int: method __repr__ (line 175) | def __repr__(self) -> str: method inside_box (line 178) | def inside_box(self, box_size: BoxSizeType, boundary_threshold: int = ... method get_centers (line 197) | def get_centers(self) -> torch.Tensor: method cat (line 205) | def cat(boxes_list: List["Boxes"]) -> "Boxes": method device (line 223) | def device(self) -> str: method __iter__ (line 226) | def __iter__(self) -> Iterator[torch.Tensor]: function pairwise_iou (line 235) | def pairwise_iou(boxes1: Boxes, boxes2: Boxes) -> torch.Tensor: function matched_boxlist_iou (line 268) | def matched_boxlist_iou(boxes1: Boxes, boxes2: Boxes) -> torch.Tensor: FILE: detectron2/structures/image_list.py class ImageList (line 8) | class ImageList(object): method __init__ (line 19) | def __init__(self, tensor: torch.Tensor, image_sizes: List[Tuple[int, ... method __len__ (line 28) | def __len__(self) -> int: method __getitem__ (line 31) | def __getitem__(self, idx: Union[int, slice]) -> torch.Tensor: method to (line 41) | def to(self, *args: Any, **kwargs: Any) -> "ImageList": method from_tensors (line 46) | def from_tensors( FILE: detectron2/structures/instances.py class Instances (line 9) | class Instances: method __init__ (line 31) | def __init__(self, image_size: Tuple[int, int], **kwargs: Any): method image_size (line 43) | def image_size(self) -> Tuple[int, int]: method __setattr__ (line 50) | def __setattr__(self, name: str, val: Any) -> None: method __getattr__ (line 56) | def __getattr__(self, name: str) -> Any: method set (line 61) | def set(self, name: str, value: Any) -> None: method has (line 74) | def has(self, name: str) -> bool: method remove (line 81) | def remove(self, name: str) -> None: method get (line 87) | def get(self, name: str) -> Any: method get_fields (line 93) | def get_fields(self) -> Dict[str, Any]: method to (line 103) | def to(self, device: str) -> "Instances": method __getitem__ (line 115) | def __getitem__(self, item: Union[int, slice, torch.BoolTensor]) -> "I... method __len__ (line 129) | def __len__(self) -> int: method cat (line 135) | def cat(instance_lists: List["Instances"]) -> "Instances": method __str__ (line 166) | def __str__(self) -> str: method __repr__ (line 174) | def __repr__(self) -> str: FILE: detectron2/structures/keypoints.py class Keypoints (line 9) | class Keypoints: method __init__ (line 21) | def __init__(self, keypoints: Union[torch.Tensor, np.ndarray, List[Lis... method __len__ (line 33) | def __len__(self) -> int: method to (line 36) | def to(self, *args: Any, **kwargs: Any) -> "Keypoints": method to_heatmap (line 39) | def to_heatmap(self, boxes: torch.Tensor, heatmap_size: int) -> torch.... method __getitem__ (line 53) | def __getitem__(self, item: Union[int, slice, torch.BoolTensor]) -> "K... method __repr__ (line 71) | def __repr__(self) -> str: function _keypoints_to_heatmap (line 78) | def _keypoints_to_heatmap( function heatmaps_to_keypoints (line 138) | def heatmaps_to_keypoints(maps: torch.Tensor, rois: torch.Tensor) -> tor... FILE: detectron2/structures/masks.py function polygon_area (line 16) | def polygon_area(x, y): function polygons_to_bitmask (line 22) | def polygons_to_bitmask(polygons: List[np.ndarray], height: int, width: ... function rasterize_polygons_within_box (line 39) | def rasterize_polygons_within_box( class BitMasks (line 88) | class BitMasks: method __init__ (line 97) | def __init__(self, tensor: Union[torch.Tensor, np.ndarray]): method to (line 111) | def to(self, *args: Any, **kwargs: Any) -> "BitMasks": method device (line 115) | def device(self) -> torch.device: method __getitem__ (line 119) | def __getitem__(self, item: Union[int, slice, torch.BoolTensor]) -> "B... method __iter__ (line 143) | def __iter__(self) -> torch.Tensor: method __repr__ (line 147) | def __repr__(self) -> str: method __len__ (line 152) | def __len__(self) -> int: method nonempty (line 155) | def nonempty(self) -> torch.Tensor: method from_polygon_masks (line 166) | def from_polygon_masks( method from_roi_masks (line 183) | def from_roi_masks(roi_masks: "ROIMasks", height: int, width: int) -> ... method crop_and_resize (line 191) | def crop_and_resize(self, boxes: torch.Tensor, mask_size: int) -> torc... method get_bounding_boxes (line 224) | def get_bounding_boxes(self) -> Boxes: method cat (line 243) | def cat(bitmasks_list: List["BitMasks"]) -> "BitMasks": class PolygonMasks (line 261) | class PolygonMasks: method __init__ (line 269) | def __init__(self, polygons: List[List[Union[torch.Tensor, np.ndarray]... method to (line 313) | def to(self, *args: Any, **kwargs: Any) -> "PolygonMasks": method device (line 317) | def device(self) -> torch.device: method get_bounding_boxes (line 320) | def get_bounding_boxes(self) -> Boxes: method nonempty (line 337) | def nonempty(self) -> torch.Tensor: method __getitem__ (line 348) | def __getitem__(self, item: Union[int, slice, List[int], torch.BoolTen... method __iter__ (line 378) | def __iter__(self) -> Iterator[List[np.ndarray]]: method __repr__ (line 386) | def __repr__(self) -> str: method __len__ (line 391) | def __len__(self) -> int: method crop_and_resize (line 394) | def crop_and_resize(self, boxes: torch.Tensor, mask_size: int) -> torc... method area (line 426) | def area(self): method cat (line 446) | def cat(polymasks_list: List["PolygonMasks"]) -> "PolygonMasks": class ROIMasks (line 466) | class ROIMasks: method __init__ (line 473) | def __init__(self, tensor: torch.Tensor): method to (line 482) | def to(self, device: torch.device) -> "ROIMasks": method device (line 486) | def device(self) -> device: method __len__ (line 489) | def __len__(self): method __getitem__ (line 492) | def __getitem__(self, item) -> "ROIMasks": method __repr__ (line 514) | def __repr__(self) -> str: method to_bitmasks (line 520) | def to_bitmasks(self, boxes: torch.Tensor, height, width, threshold=0.5): FILE: detectron2/structures/rotated_boxes.py class RotatedBoxes (line 11) | class RotatedBoxes(Boxes): method __init__ (line 20) | def __init__(self, tensor: torch.Tensor): method clone (line 221) | def clone(self) -> "RotatedBoxes": method to (line 230) | def to(self, device: str) -> "RotatedBoxes": method area (line 233) | def area(self) -> torch.Tensor: method normalize_angles (line 244) | def normalize_angles(self) -> None: method clip (line 251) | def clip(self, box_size: Boxes.BoxSizeType, clip_angle_threshold: floa... method nonempty (line 301) | def nonempty(self, threshold: int = 0) -> torch.Tensor: method __getitem__ (line 316) | def __getitem__(self, item: Union[int, slice, torch.BoolTensor]) -> "R... method __len__ (line 339) | def __len__(self) -> int: method __repr__ (line 342) | def __repr__(self) -> str: method inside_box (line 345) | def inside_box(self, box_size: Boxes.BoxSizeType, boundary_threshold: ... method get_centers (line 382) | def get_centers(self) -> torch.Tensor: method cat (line 390) | def cat(boxes_list: List["RotatedBoxes"]) -> "RotatedBoxes": # type: ... method device (line 408) | def device(self) -> str: method __iter__ (line 411) | def __iter__(self) -> Iterator[torch.Tensor]: function pairwise_iou (line 418) | def pairwise_iou(boxes1: RotatedBoxes, boxes2: RotatedBoxes) -> None: FILE: detectron2/utils/collect_env.py function collect_torch_env (line 12) | def collect_torch_env(): function get_env_module (line 24) | def get_env_module(): function collect_env_info (line 29) | def collect_env_info(): FILE: detectron2/utils/colormap.py function colormap (line 95) | def colormap(rgb=False, maximum=255): function random_color (line 111) | def random_color(rgb=False, maximum=255): FILE: detectron2/utils/comm.py function get_world_size (line 21) | def get_world_size() -> int: function get_rank (line 29) | def get_rank() -> int: function get_local_rank (line 37) | def get_local_rank() -> int: function get_local_size (line 50) | def get_local_size() -> int: function is_main_process (line 63) | def is_main_process() -> bool: function synchronize (line 67) | def synchronize(): function _get_global_gloo_group (line 83) | def _get_global_gloo_group(): function _serialize_to_tensor (line 94) | def _serialize_to_tensor(data, group): function _pad_to_largest_tensor (line 112) | def _pad_to_largest_tensor(tensor, group): function all_gather (line 139) | def all_gather(data, group=None): function gather (line 177) | def gather(data, dst=0, group=None): function shared_random_seed (line 220) | def shared_random_seed(): function reduce_dict (line 234) | def reduce_dict(input_dict, average=True): FILE: detectron2/utils/develop.py function create_dummy_class (line 8) | def create_dummy_class(klass, dependency, message=""): function create_dummy_func (line 37) | def create_dummy_func(func, dependency, message=""): FILE: detectron2/utils/env.py function seed_all_rng (line 27) | def seed_all_rng(seed=None): function _import_file (line 49) | def _import_file(module_name, file_path, make_importable=False): function _configure_libraries (line 58) | def _configure_libraries(): function setup_environment (line 97) | def setup_environment(): function setup_custom_environment (line 119) | def setup_custom_environment(custom_module): function fixup_module_metadata (line 135) | def fixup_module_metadata(module_name, namespace, keys=None): FILE: detectron2/utils/events.py function get_event_storage (line 15) | def get_event_storage(): class JSONWriter (line 22) | class JSONWriter: method __init__ (line 68) | def __init__(self, json_file, window_size=20): method write (line 78) | def write(self): method __del__ (line 89) | def __del__(self): class TensorboardXWriter (line 94) | class TensorboardXWriter: method __init__ (line 99) | def __init__(self, log_dir: str, window_size: int = 20, **kwargs): method write (line 111) | def write(self): method __del__ (line 116) | def __del__(self): class CommonMetricPrinter (line 121) | class CommonMetricPrinter: method __init__ (line 129) | def __init__(self, max_iter): method write (line 138) | def write(self): class EventStorage (line 186) | class EventStorage: method __init__ (line 193) | def __init__(self, start_iter=0): method put_scalar (line 204) | def put_scalar(self, name, value, smoothing_hint=True): method put_scalars (line 231) | def put_scalars(self, *, smoothing_hint=True, **kwargs): method history (line 242) | def history(self, name): method histories (line 252) | def histories(self): method latest (line 259) | def latest(self): method latest_with_smoothing_hint (line 266) | def latest_with_smoothing_hint(self, window_size=20): method smoothing_hints (line 280) | def smoothing_hints(self): method step (line 288) | def step(self): method iter (line 299) | def iter(self): method iteration (line 303) | def iteration(self): method __enter__ (line 307) | def __enter__(self): method __exit__ (line 311) | def __exit__(self, exc_type, exc_val, exc_tb): method name_scope (line 316) | def name_scope(self, name): FILE: detectron2/utils/logger.py class _ColorfulFormatter (line 12) | class _ColorfulFormatter(logging.Formatter): method __init__ (line 13) | def __init__(self, *args, **kwargs): method formatMessage (line 20) | def formatMessage(self, record): function setup_logger (line 33) | def setup_logger( function _cached_log_stream (line 94) | def _cached_log_stream(filename): function _find_caller (line 105) | def _find_caller(): function log_first_n (line 125) | def log_first_n(lvl, msg, n=1, *, name=None, key="caller"): function log_every_n (line 160) | def log_every_n(lvl, msg, n=1, *, name=None): function create_small_table (line 176) | def create_small_table(small_dict): FILE: detectron2/utils/memory.py function _ignore_torch_cuda_oom (line 12) | def _ignore_torch_cuda_oom(): function retry_if_cuda_oom (line 26) | def retry_if_cuda_oom(func): FILE: detectron2/utils/registry.py class Registry (line 2) | class Registry(object): method __init__ (line 27) | def __init__(self, name): method _do_register (line 36) | def _do_register(self, name, obj): method register (line 42) | def register(self, obj=None): method get (line 60) | def get(self, name): FILE: detectron2/utils/serialize.py class PicklableWrapper (line 5) | class PicklableWrapper(object): method __init__ (line 15) | def __init__(self, obj): method __reduce__ (line 18) | def __reduce__(self): method __call__ (line 22) | def __call__(self, *args, **kwargs): method __getattr__ (line 25) | def __getattr__(self, attr): FILE: detectron2/utils/video_visualizer.py class _DetectedInstance (line 15) | class _DetectedInstance: method __init__ (line 31) | def __init__(self, label, bbox, mask_rle, color, ttl): class VideoVisualizer (line 39) | class VideoVisualizer: method __init__ (line 40) | def __init__(self, metadata, instance_mode=ColorMode.IMAGE): method draw_instance_predictions (line 53) | def draw_instance_predictions(self, frame, predictions): method draw_sem_seg (line 112) | def draw_sem_seg(self, frame, sem_seg, area_threshold=None): method draw_panoptic_seg_predictions (line 124) | def draw_panoptic_seg_predictions( method _assign_colors (line 180) | def _assign_colors(self, instances): FILE: detectron2/utils/visualizer.py class ColorMode (line 30) | class ColorMode(Enum): class GenericMask (line 46) | class GenericMask: method __init__ (line 54) | def __init__(self, mask_or_polygons, height, width): method mask (line 83) | def mask(self): method polygons (line 89) | def polygons(self): method has_holes (line 95) | def has_holes(self): method mask_to_polygons (line 103) | def mask_to_polygons(self, mask): method polygons_to_mask (line 121) | def polygons_to_mask(self, polygons): method area (line 126) | def area(self): method bbox (line 129) | def bbox(self): class _PanopticPrediction (line 138) | class _PanopticPrediction: method __init__ (line 139) | def __init__(self, panoptic_seg, segments_info): method non_empty_mask (line 152) | def non_empty_mask(self): method semantic_masks (line 168) | def semantic_masks(self): method instance_masks (line 176) | def instance_masks(self): function _create_text_labels (line 186) | def _create_text_labels(classes, scores, class_names): class VisImage (line 208) | class VisImage: method __init__ (line 209) | def __init__(self, img, scale=1.0): method _setup_figure (line 220) | def _setup_figure(self, img): method save (line 247) | def save(self, filepath): method get_image (line 255) | def get_image(self): class Visualizer (line 292) | class Visualizer: method __init__ (line 293) | def __init__(self, img_rgb, metadata, scale=1.0, instance_mode=ColorMo... method draw_instance_predictions (line 315) | def draw_instance_predictions(self, predictions,is_ass= False, labels_... method draw_sem_seg (line 370) | def draw_sem_seg(self, sem_seg, area_threshold=None, alpha=0.8): method draw_panoptic_seg_predictions (line 405) | def draw_panoptic_seg_predictions( method draw_dataset_dict (line 465) | def draw_dataset_dict(self, dic): method overlay_instances (line 502) | def overlay_instances( method draw_and_connect_keypoints (line 639) | def draw_and_connect_keypoints(self, keypoints): method draw_text (line 698) | def draw_text( method draw_box (line 736) | def draw_box(self, box_coord, alpha=0.5, edge_color="g", line_style="-"): method draw_circle (line 770) | def draw_circle(self, circle_coord, color, radius=3): method draw_line (line 788) | def draw_line(self, x_data, y_data, color): method draw_binary_mask (line 807) | def draw_binary_mask( method draw_polygon (line 867) | def draw_polygon(self, segment, color, edge_color=None, alpha=0.5): method _jitter (line 903) | def _jitter(self, color): method _create_grayscale_image (line 922) | def _create_grayscale_image(self, mask=None): method _change_color_brightness (line 933) | def _change_color_brightness(self, color, brightness_factor): method _convert_boxes (line 958) | def _convert_boxes(self, boxes): method _convert_masks (line 967) | def _convert_masks(self, masks_or_polygons): method _convert_keypoints (line 990) | def _convert_keypoints(self, keypoints): method get_output (line 996) | def get_output(self): FILE: docs/conf.py function autodoc_skip_member (line 258) | def autodoc_skip_member(app, what, name, obj, skip, options): function url_resolver (line 268) | def url_resolver(url): function setup (line 279) | def setup(app): FILE: projects/LISA/LISA/LISA_meta_arch.py class LISARCNN (line 19) | class LISARCNN(GeneralizedRCNN): method __init__ (line 21) | def __init__(self,cfg): method forward (line 26) | def forward(self, batched_inputs): method inference (line 61) | def inference(self, batched_inputs, detected_instances=None, do_postpr... FILE: projects/LISA/LISA/LISA_rcnn.py class LISAROIHeads (line 24) | class LISAROIHeads(StandardROIHeads): method _init_box_head (line 35) | def _init_box_head(self,cfg): method forward (line 71) | def forward(self,images, features, association_proposals, proposals, a... method _forward_association_box (line 102) | def _forward_association_box(self, features, association_proposals): method label_and_sample_proposals (line 128) | def label_and_sample_proposals(self, proposals, targets, isassociation... FILE: projects/LISA/LISA/LISA_rpn.py function build_rpn_head (line 25) | def build_rpn_head(cfg, input_shape,shadow_object_part=False): class LISARPNHead (line 34) | class LISARPNHead(StandardRPNHead): method __init__ (line 35) | def __init__(self, cfg, input_shape: List[ShapeSpec], shadow_object_pa... method forward (line 47) | def forward(self, features): function build_proposal_generator (line 70) | def build_proposal_generator(cfg, input_shape, **args): class LISARPN (line 82) | class LISARPN(RPN): method __init__ (line 84) | def __init__(self, cfg, input_shape: Dict[str, ShapeSpec], shadow_obje... method forward (line 90) | def forward(self, images, features, gt_instances=None, pre_proposals=N... FILE: projects/LISA/LISA/config.py function add_lisa_config (line 7) | def add_lisa_config(cfg): FILE: projects/LISA/defaults.py function default_argument_parser (line 48) | def default_argument_parser(): function default_setup (line 83) | def default_setup(cfg, args): class DefaultPredictor (line 132) | class DefaultPredictor: method __init__ (line 142) | def __init__(self, cfg): method __call__ (line 159) | def __call__(self, original_image): class DefaultTrainer (line 180) | class DefaultTrainer(SimpleTrainer): method __init__ (line 209) | def __init__(self, cfg): method resume_or_load (line 243) | def resume_or_load(self, resume=True): method build_hooks (line 261) | def build_hooks(self): method build_writers (line 307) | def build_writers(self): method train (line 323) | def train(self): method build_model (line 336) | def build_model(cls, cfg): method build_optimizer (line 347) | def build_optimizer(cls, cfg, model): method build_lr_scheduler (line 355) | def build_lr_scheduler(cls, cfg, optimizer): method build_train_loader (line 359) | def build_train_loader(cls, cfg): method build_test_loader (line 367) | def build_test_loader(cls, cfg, dataset_name): method build_evaluator (line 375) | def build_evaluator(cls, cfg, dataset_name): method test (line 383) | def test(cls, cfg, model, evaluators=None): FILE: projects/LISA/demo.py function setup_cfg (line 22) | def setup_cfg(args): function get_parser (line 35) | def get_parser(): FILE: projects/LISA/predictor.py class VisualizationDemo (line 16) | class VisualizationDemo(object): method __init__ (line 17) | def __init__(self, cfg, instance_mode=ColorMode.IMAGE, parallel=False): method run_on_image (line 36) | def run_on_image(self, image): method _frame_from_video (line 76) | def _frame_from_video(self, video): method run_on_video (line 84) | def run_on_video(self, video): class AsyncPredictor (line 140) | class AsyncPredictor: class _StopToken (line 147) | class _StopToken: class _PredictWorker (line 150) | class _PredictWorker(mp.Process): method __init__ (line 151) | def __init__(self, cfg, task_queue, result_queue): method run (line 157) | def run(self): method __init__ (line 168) | def __init__(self, cfg, num_gpus: int = 1): method put (line 195) | def put(self, image): method get (line 199) | def get(self): method __len__ (line 215) | def __len__(self): method __call__ (line 218) | def __call__(self, image): method shutdown (line 222) | def shutdown(self): method default_buffer_size (line 227) | def default_buffer_size(self): FILE: projects/LISA/train_net.py class Trainer (line 48) | class Trainer(DefaultTrainer): method build_evaluator (line 57) | def build_evaluator(cls, cfg, dataset_name, output_folder=None): method test_with_TTA (line 102) | def test_with_TTA(cls, cfg, model): function setup (line 119) | def setup(args): function main (line 131) | def main(args): FILE: projects/LISA/utils.py function extract_bboxes (line 34) | def extract_bboxes(mask): function compute_iou (line 60) | def compute_iou(box, boxes, box_area, boxes_area): function compute_overlaps (line 81) | def compute_overlaps(boxes1, boxes2): function compute_overlaps_masks (line 100) | def compute_overlaps_masks(masks1, masks2): function non_max_suppression (line 122) | def non_max_suppression(boxes, scores, threshold): function apply_box_deltas (line 159) | def apply_box_deltas(boxes, deltas): function box_refinement (line 209) | def box_refinement(box, gt_box): class Dataset (line 239) | class Dataset(object): method __init__ (line 255) | def __init__(self, class_map=None): method add_class (line 262) | def add_class(self, source, class_id, class_name): method add_image (line 276) | def add_image(self, source, image_id, path, **kwargs): method image_reference (line 285) | def image_reference(self, image_id): method prepare (line 294) | def prepare(self, class_map=None): method map_source_class_id (line 330) | def map_source_class_id(self, source_class_id): method get_source_class_id (line 338) | def get_source_class_id(self, class_id, source): method image_ids (line 345) | def image_ids(self): method source_image_link (line 348) | def source_image_link(self, image_id): method load_image (line 355) | def load_image(self, image_id): method load_mask (line 368) | def load_mask(self, image_id): function resize_image (line 388) | def resize_image(image, min_dim=None, max_dim=None, min_scale=None, mode... function resize_mask (line 495) | def resize_mask(mask, scale, padding, crop=None): function minimize_mask (line 517) | def minimize_mask(bbox, mask, mini_shape): function expand_mask (line 537) | def expand_mask(bbox, mini_mask, image_shape): function mold_mask (line 556) | def mold_mask(mask, config): function unmold_mask (line 560) | def unmold_mask(mask, bbox, image_shape): function generate_anchors (line 583) | def generate_anchors(scales, ratios, shape, feature_stride, anchor_stride): function generate_pyramid_anchors (line 622) | def generate_pyramid_anchors(scales, ratios, feature_shapes, feature_str... function trim_zeros (line 646) | def trim_zeros(x): function compute_matches (line 656) | def compute_matches(gt_boxes, gt_class_ids, gt_masks, function compute_ap (line 715) | def compute_ap(gt_boxes, gt_class_ids, gt_masks, function compute_ap_range (line 754) | def compute_ap_range(gt_box, gt_class_id, gt_mask, function compute_recall (line 778) | def compute_recall(pred_boxes, gt_boxes, iou): function download_trained_weights (line 840) | def download_trained_weights(coco_model_path, verbose=1): function norm_boxes (line 853) | def norm_boxes(boxes, shape): function denorm_boxes (line 870) | def denorm_boxes(boxes, shape): function resize (line 887) | def resize(image, output_shape, order=1, mode='constant', cval=0, clip=T... function __main__ (line 909) | def __main__(): FILE: projects/LISA/visualize_data.py function setup (line 18) | def setup(args): function parse_args (line 27) | def parse_args(in_args=None): function output (line 57) | def output(vis, fname): FILE: projects/LISA/visualize_json_results.py function create_instances (line 24) | def create_instances(ins_predictions, ass_predictions,image_size): function dataset_id_map (line 94) | def dataset_id_map(ds_id): function dataset_ass_id_map (line 96) | def dataset_ass_id_map(ds_id): function dataset_id_map (line 102) | def dataset_id_map(ds_id): FILE: setup.py function get_version (line 17) | def get_version(): function get_extensions (line 40) | def get_extensions(): function get_model_zoo_configs (line 89) | def get_model_zoo_configs() -> List[str]: FILE: tests/test_anchor_generator.py class TestAnchorGenerator (line 13) | class TestAnchorGenerator(unittest.TestCase): method test_default_anchor_generator (line 14) | def test_default_anchor_generator(self): method test_default_anchor_generator_centered (line 45) | def test_default_anchor_generator_centered(self): method test_rrpn_anchor_generator (line 77) | def test_rrpn_anchor_generator(self): FILE: tests/test_box2box_transform.py function random_boxes (line 11) | def random_boxes(mean_box, stdev, N): class TestBox2BoxTransform (line 15) | class TestBox2BoxTransform(unittest.TestCase): method test_reconstruction (line 16) | def test_reconstruction(self): function random_rotated_boxes (line 33) | def random_rotated_boxes(mean_box, std_length, std_angle, N): class TestBox2BoxTransformRotated (line 39) | class TestBox2BoxTransformRotated(unittest.TestCase): method test_reconstruction (line 40) | def test_reconstruction(self): FILE: tests/test_boxes.py class TestBoxMode (line 11) | class TestBoxMode(unittest.TestCase): method _convert_xy_to_wh (line 12) | def _convert_xy_to_wh(self, x): method _convert_xywha_to_xyxy (line 15) | def _convert_xywha_to_xyxy(self, x): method _convert_xywh_to_xywha (line 18) | def _convert_xywh_to_xywha(self, x): method test_box_convert_list (line 21) | def test_box_convert_list(self): method test_box_convert_array (line 31) | def test_box_convert_array(self): method test_box_convert_cpu_tensor (line 39) | def test_box_convert_cpu_tensor(self): method test_box_convert_cuda_tensor (line 49) | def test_box_convert_cuda_tensor(self): method test_box_convert_xywha_to_xyxy_list (line 59) | def test_box_convert_xywha_to_xyxy_list(self): method test_box_convert_xywha_to_xyxy_array (line 69) | def test_box_convert_xywha_to_xyxy_array(self): method test_box_convert_xywha_to_xyxy_tensor (line 84) | def test_box_convert_xywha_to_xyxy_tensor(self): method test_box_convert_xywh_to_xywha_list (line 100) | def test_box_convert_xywh_to_xywha_list(self): method test_box_convert_xywh_to_xywha_array (line 110) | def test_box_convert_xywh_to_xywha_array(self): method test_box_convert_xywh_to_xywha_tensor (line 120) | def test_box_convert_xywh_to_xywha_tensor(self): method test_json_serializable (line 131) | def test_json_serializable(self): method test_json_deserializable (line 138) | def test_json_deserializable(self): class TestBoxIOU (line 147) | class TestBoxIOU(unittest.TestCase): method test_pairwise_iou (line 148) | def test_pairwise_iou(self): FILE: tests/test_checkpoint.py class TestCheckpointer (line 11) | class TestCheckpointer(unittest.TestCase): method setUp (line 12) | def setUp(self): method create_complex_model (line 15) | def create_complex_model(self): method test_complex_model_loaded (line 32) | def test_complex_model_loaded(self): FILE: tests/test_config.py class TestConfigVersioning (line 24) | class TestConfigVersioning(unittest.TestCase): method test_upgrade_downgrade_consistency (line 25) | def test_upgrade_downgrade_consistency(self): method _merge_cfg_str (line 34) | def _merge_cfg_str(self, cfg, merge_str): method test_auto_upgrade (line 44) | def test_auto_upgrade(self): method test_guess_v1 (line 54) | def test_guess_v1(self): FILE: tests/test_data_loader.py class TestTransformAnnotations (line 13) | class TestTransformAnnotations(unittest.TestCase): method test_transform_simple_annotation (line 14) | def test_transform_simple_annotation(self): method test_flip_keypoints (line 30) | def test_flip_keypoints(self): method test_transform_RLE (line 62) | def test_transform_RLE(self): method test_transform_RLE_resize (line 85) | def test_transform_RLE_resize(self): method test_gen_crop (line 107) | def test_gen_crop(self): method test_gen_crop_outside_boxes (line 113) | def test_gen_crop_outside_boxes(self): FILE: tests/test_data_transform.py class TestTransforms (line 16) | class TestTransforms(unittest.TestCase): method setUp (line 17) | def setUp(self): method test_apply_rotated_boxes (line 20) | def test_apply_rotated_boxes(self): method test_apply_rotated_boxes_unequal_scaling_factor (line 38) | def test_apply_rotated_boxes_unequal_scaling_factor(self): method test_print_transform_gen (line 72) | def test_print_transform_gen(self): FILE: tests/test_fast_rcnn.py class FastRCNNTest (line 16) | class FastRCNNTest(unittest.TestCase): method test_fast_rcnn (line 17) | def test_fast_rcnn(self): method test_fast_rcnn_rotated (line 56) | def test_fast_rcnn_rotated(self): FILE: tests/test_mask_ops.py function iou_between_full_image_bit_masks (line 28) | def iou_between_full_image_bit_masks(a, b): function rasterize_polygons_with_grid_sample (line 34) | def rasterize_polygons_with_grid_sample(full_image_bit_mask, box, mask_s... class TestMaskCropPaste (line 59) | class TestMaskCropPaste(unittest.TestCase): method setUp (line 60) | def setUp(self): method test_crop_paste_consistency (line 67) | def test_crop_paste_consistency(self): method process_annotation (line 99) | def process_annotation(self, ann, mask_side_len=28): method test_polygon_area (line 139) | def test_polygon_area(self): function benchmark_paste (line 155) | def benchmark_paste(): FILE: tests/test_model_e2e.py function get_model_zoo (line 14) | def get_model_zoo(config_path): function create_model_input (line 26) | def create_model_input(img, inst=None): function get_empty_instance (line 33) | def get_empty_instance(h, w): function get_regular_bitmask_instances (line 41) | def get_regular_bitmask_instances(h, w): class ModelE2ETest (line 50) | class ModelE2ETest(unittest.TestCase): method setUp (line 51) | def setUp(self): method _test_eval (line 54) | def _test_eval(self, input_sizes): method _test_train (line 59) | def _test_train(self, input_sizes, instances): class MaskRCNNE2ETest (line 72) | class MaskRCNNE2ETest(ModelE2ETest): method test_empty_data (line 75) | def test_empty_data(self): method test_half_empty_data (line 80) | def test_half_empty_data(self): class RetinaNetE2ETest (line 85) | class RetinaNetE2ETest(ModelE2ETest): method test_empty_data (line 88) | def test_empty_data(self): FILE: tests/test_model_zoo.py class TestModelZoo (line 11) | class TestModelZoo(unittest.TestCase): method test_get_returns_model (line 12) | def test_get_returns_model(self): method test_get_invalid_model (line 17) | def test_get_invalid_model(self): method test_get_url (line 20) | def test_get_url(self): FILE: tests/test_nms_rotated.py class TestNMSRotated (line 10) | class TestNMSRotated(unittest.TestCase): method reference_horizontal_nms (line 11) | def reference_horizontal_nms(self, boxes, scores, iou_threshold): method _create_tensors (line 35) | def _create_tensors(self, N): method test_batched_nms_rotated_0_degree_cpu (line 45) | def test_batched_nms_rotated_0_degree_cpu(self): method test_batched_nms_rotated_0_degree_cuda (line 69) | def test_batched_nms_rotated_0_degree_cuda(self): method test_nms_rotated_0_degree_cpu (line 92) | def test_nms_rotated_0_degree_cpu(self): method test_nms_rotated_90_degrees_cpu (line 106) | def test_nms_rotated_90_degrees_cpu(self): method test_nms_rotated_180_degrees_cpu (line 125) | def test_nms_rotated_180_degrees_cpu(self): method test_nms_rotated_0_degree_cuda (line 141) | def test_nms_rotated_0_degree_cuda(self): FILE: tests/test_roi_align.py class ROIAlignTest (line 10) | class ROIAlignTest(unittest.TestCase): method test_forward_output (line 11) | def test_forward_output(self): method test_resize (line 49) | def test_resize(self): method _simple_roialign (line 61) | def _simple_roialign(self, img, box, resolution, aligned=True): method _simple_roialign_with_grad (line 78) | def _simple_roialign_with_grad(self, img, box, resolution, device): method test_empty_box (line 93) | def test_empty_box(self): method test_empty_batch (line 105) | def test_empty_batch(self): FILE: tests/test_roi_align_rotated.py class ROIAlignRotatedTest (line 14) | class ROIAlignRotatedTest(unittest.TestCase): method _box_to_rotated_box (line 15) | def _box_to_rotated_box(self, box, angle): method _rot90 (line 24) | def _rot90(self, img, num): method test_forward_output_0_90_180_270 (line 30) | def test_forward_output_0_90_180_270(self): method test_resize (line 73) | def test_resize(self): method _simple_roi_align_rotated (line 87) | def _simple_roi_align_rotated(self, img, box, resolution): method test_empty_box (line 102) | def test_empty_box(self): method test_roi_align_rotated_gradcheck_cpu (line 107) | def test_roi_align_rotated_gradcheck_cpu(self): method test_roi_align_rotated_gradient_cuda (line 128) | def test_roi_align_rotated_gradient_cuda(self): FILE: tests/test_roi_heads.py class ROIHeadsTest (line 16) | class ROIHeadsTest(unittest.TestCase): method test_roi_heads (line 17) | def test_roi_heads(self): method test_rroi_heads (line 58) | def test_rroi_heads(self): FILE: tests/test_roi_pooler.py class TestROIPooler (line 12) | class TestROIPooler(unittest.TestCase): method _rand_boxes (line 13) | def _rand_boxes(self, num_boxes, x_max, y_max): method _test_roialignv2_roialignrotated_match (line 26) | def _test_roialignv2_roialignrotated_match(self, device): method test_roialignv2_roialignrotated_match_cpu (line 76) | def test_roialignv2_roialignrotated_match_cpu(self): method test_roialignv2_roialignrotated_match_cuda (line 80) | def test_roialignv2_roialignrotated_match_cuda(self): FILE: tests/test_rotated_boxes.py class TestRotatedBoxesLayer (line 17) | class TestRotatedBoxesLayer(unittest.TestCase): method test_iou_0_dim_cpu (line 18) | def test_iou_0_dim_cpu(self): method test_iou_0_dim_cuda (line 32) | def test_iou_0_dim_cuda(self): method test_iou_half_overlap_cpu (line 45) | def test_iou_half_overlap_cpu(self): method test_iou_half_overlap_cuda (line 53) | def test_iou_half_overlap_cuda(self): method test_iou_0_degree_cpu (line 60) | def test_iou_0_degree_cpu(self): method test_iou_0_degree_cuda (line 86) | def test_iou_0_degree_cuda(self): method test_iou_45_degrees_cpu (line 111) | def test_iou_45_degrees_cpu(self): method test_iou_45_degrees_cuda (line 125) | def test_iou_45_degrees_cuda(self): method test_iou_perpendicular_cpu (line 138) | def test_iou_perpendicular_cpu(self): method test_iou_perpendicular_cuda (line 147) | def test_iou_perpendicular_cuda(self): method test_iou_large_close_boxes_cpu (line 155) | def test_iou_large_close_boxes_cpu(self): method test_iou_large_close_boxes_cuda (line 168) | def test_iou_large_close_boxes_cuda(self): method test_iou_precision_cpu (line 180) | def test_iou_precision_cpu(self): method test_iou_precision_cuda (line 189) | def test_iou_precision_cuda(self): method test_iou_many_boxes_cpu (line 197) | def test_iou_many_boxes_cpu(self): method test_iou_many_boxes_cuda (line 221) | def test_iou_many_boxes_cuda(self): method test_iou_too_many_boxes_cuda (line 245) | def test_iou_too_many_boxes_cuda(self): class TestRotatedBoxesStructure (line 253) | class TestRotatedBoxesStructure(unittest.TestCase): method test_clip_area_0_degree (line 254) | def test_clip_area_0_degree(self): method test_clip_area_arbitrary_angle (line 283) | def test_clip_area_arbitrary_angle(self): method test_normalize_angles (line 311) | def test_normalize_angles(self): method test_pairwise_iou_0_degree_cpu (line 342) | def test_pairwise_iou_0_degree_cpu(self): method test_pairwise_iou_0_degree_cuda (line 373) | def test_pairwise_iou_0_degree_cuda(self): method test_pairwise_iou_45_degrees_cpu (line 403) | def test_pairwise_iou_45_degrees_cpu(self): method test_pairwise_iou_45_degrees_cuda (line 419) | def test_pairwise_iou_45_degrees_cuda(self): method test_pairwise_iou_orthogonal_cpu (line 434) | def test_pairwise_iou_orthogonal_cpu(self): method test_pairwise_iou_orthogonal_cuda (line 444) | def test_pairwise_iou_orthogonal_cuda(self): method test_pairwise_iou_large_close_boxes_cpu (line 453) | def test_pairwise_iou_large_close_boxes_cpu(self): method test_pairwise_iou_large_close_boxes_cuda (line 471) | def test_pairwise_iou_large_close_boxes_cuda(self): method test_pairwise_iou_many_boxes_cpu (line 488) | def test_pairwise_iou_many_boxes_cpu(self): method test_pairwise_iou_many_boxes_cuda (line 517) | def test_pairwise_iou_many_boxes_cuda(self): function benchmark_rotated_iou (line 546) | def benchmark_rotated_iou(): FILE: tests/test_rpn.py class RPNTest (line 15) | class RPNTest(unittest.TestCase): method test_rpn (line 16) | def test_rpn(self): method test_rrpn (line 76) | def test_rrpn(self): FILE: tests/test_sampler.py class TestGroupedBatchSampler (line 8) | class TestGroupedBatchSampler(unittest.TestCase): method test_missing_group_id (line 9) | def test_missing_group_id(self): method test_groups (line 17) | def test_groups(self): FILE: tests/test_visualizer.py class TestVisualizer (line 14) | class TestVisualizer(unittest.TestCase): method _random_data (line 15) | def _random_data(self): method metadata (line 34) | def metadata(self): method test_draw_dataset_dict (line 37) | def test_draw_dataset_dict(self): method test_overlay_instances (line 64) | def test_overlay_instances(self): method test_overlay_instances_no_boxes (line 81) | def test_overlay_instances_no_boxes(self): method test_draw_instance_predictions (line 86) | def test_draw_instance_predictions(self): method test_draw_empty_mask_predictions (line 98) | def test_draw_empty_mask_predictions(self): method test_correct_output_shape (line 110) | def test_correct_output_shape(self): method test_overlay_rotated_instances (line 116) | def test_overlay_rotated_instances(self): method test_draw_no_metadata (line 133) | def test_draw_no_metadata(self):