SYMBOL INDEX (624 symbols across 121 files)

FILE: mmdetection/mmdet/apis/env.py
  function init_dist (line 13) | def init_dist(launcher, backend='nccl', **kwargs):
  function _init_dist_pytorch (line 26) | def _init_dist_pytorch(backend, **kwargs):
  function _init_dist_mpi (line 34) | def _init_dist_mpi(backend, **kwargs):
  function _init_dist_slurm (line 38) | def _init_dist_slurm(backend, port=29500, **kwargs):
  function set_random_seed (line 53) | def set_random_seed(seed):
  function get_root_logger (line 60) | def get_root_logger(log_level=logging.INFO):

FILE: mmdetection/mmdet/apis/inference.py
  function init_detector (line 15) | def init_detector(config, checkpoint=None, device='cuda:0'):
  function inference_detector (line 48) | def inference_detector(model, imgs):
  function _prepare_data (line 71) | def _prepare_data(img, img_transform, cfg, device):
  function _inference_single (line 89) | def _inference_single(model, img, img_transform, device):
  function _inference_generator (line 97) | def _inference_generator(model, imgs, img_transform, device):
  function show_result (line 103) | def show_result(img, result, class_names, score_thr=0.3, out_file=None):

FILE: mmdetection/mmdet/apis/train.py
  function parse_losses (line 18) | def parse_losses(losses):
  function batch_processor (line 38) | def batch_processor(model, data, train_mode):
  function train_detector (line 48) | def train_detector(model,
  function build_optimizer (line 64) | def build_optimizer(model, optimizer_cfg):
  function _dist_train (line 134) | def _dist_train(model, dataset, cfg, validate=False):
  function _non_dist_train (line 174) | def _non_dist_train(model, dataset, cfg, validate=False):

FILE: mmdetection/mmdet/core/anchor/anchor_generator.py
  class AnchorGenerator (line 4) | class AnchorGenerator(object):
    method __init__ (line 6) | def __init__(self, base_size, scales, ratios, scale_major=True, ctr=No...
    method num_base_anchors (line 15) | def num_base_anchors(self):
    method gen_base_anchors (line 18) | def gen_base_anchors(self):
    method _meshgrid (line 45) | def _meshgrid(self, x, y, row_major=True):
    method grid_anchors (line 53) | def grid_anchors(self, featmap_size, stride=16, device='cuda'):
    method valid_flags (line 72) | def valid_flags(self, featmap_size, valid_size, device='cuda'):

FILE: mmdetection/mmdet/core/anchor/anchor_target.py
  function anchor_target (line 7) | def anchor_target(anchor_list,
  function images_to_levels (line 79) | def images_to_levels(target, num_level_anchors):
  function anchor_target_single (line 94) | def anchor_target_single(flat_anchors,
  function anchor_inside_flags (line 162) | def anchor_inside_flags(flat_anchors, valid_flags, img_shape,
  function unmap (line 176) | def unmap(data, count, inds, fill=0):

FILE: mmdetection/mmdet/core/bbox/assign_sampling.py
  function build_assigner (line 6) | def build_assigner(cfg, **kwargs):
  function build_sampler (line 17) | def build_sampler(cfg, **kwargs):
  function assign_and_sample (line 28) | def assign_and_sample(bboxes, gt_bboxes, gt_bboxes_ignore, gt_labels, cfg):

FILE: mmdetection/mmdet/core/bbox/assigners/assign_result.py
  class AssignResult (line 4) | class AssignResult(object):
    method __init__ (line 6) | def __init__(self, num_gts, gt_inds, max_overlaps, labels=None):
    method add_gt_ (line 12) | def add_gt_(self, gt_labels):

FILE: mmdetection/mmdet/core/bbox/assigners/base_assigner.py
  class BaseAssigner (line 4) | class BaseAssigner(metaclass=ABCMeta):
    method assign (line 7) | def assign(self, bboxes, gt_bboxes, gt_bboxes_ignore=None, gt_labels=N...

FILE: mmdetection/mmdet/core/bbox/assigners/max_iou_assigner.py
  class MaxIoUAssigner (line 8) | class MaxIoUAssigner(BaseAssigner):
    method __init__ (line 33) | def __init__(self,
    method assign (line 47) | def assign(self, bboxes, gt_bboxes, gt_bboxes_ignore=None, gt_labels=N...
    method assign_wrt_overlaps (line 93) | def assign_wrt_overlaps(self, overlaps, gt_labels=None):

FILE: mmdetection/mmdet/core/bbox/bbox_target.py
  function bbox_target (line 7) | def bbox_target(pos_bboxes_list,
  function bbox_target_single (line 35) | def bbox_target_single(pos_bboxes,
  function expand_target (line 64) | def expand_target(bbox_targets, bbox_weights, labels, num_classes):

FILE: mmdetection/mmdet/core/bbox/geometry.py
  function bbox_overlaps (line 4) | def bbox_overlaps(bboxes1, bboxes2, mode='iou', is_aligned=False):

FILE: mmdetection/mmdet/core/bbox/samplers/base_sampler.py
  class BaseSampler (line 8) | class BaseSampler(metaclass=ABCMeta):
    method __init__ (line 10) | def __init__(self,
    method _sample_pos (line 24) | def _sample_pos(self, assign_result, num_expected, **kwargs):
    method _sample_neg (line 28) | def _sample_neg(self, assign_result, num_expected, **kwargs):
    method sample (line 31) | def sample(self,

FILE: mmdetection/mmdet/core/bbox/samplers/combined_sampler.py
  class CombinedSampler (line 5) | class CombinedSampler(BaseSampler):
    method __init__ (line 7) | def __init__(self, pos_sampler, neg_sampler, **kwargs):
    method _sample_pos (line 12) | def _sample_pos(self, **kwargs):
    method _sample_neg (line 15) | def _sample_neg(self, **kwargs):

FILE: mmdetection/mmdet/core/bbox/samplers/instance_balanced_pos_sampler.py
  class InstanceBalancedPosSampler (line 7) | class InstanceBalancedPosSampler(RandomSampler):
    method _sample_pos (line 9) | def _sample_pos(self, assign_result, num_expected, **kwargs):

FILE: mmdetection/mmdet/core/bbox/samplers/iou_balanced_neg_sampler.py
  class IoUBalancedNegSampler (line 7) | class IoUBalancedNegSampler(RandomSampler):
    method __init__ (line 9) | def __init__(self,
    method _sample_neg (line 22) | def _sample_neg(self, assign_result, num_expected, **kwargs):

FILE: mmdetection/mmdet/core/bbox/samplers/ohem_sampler.py
  class OHEMSampler (line 7) | class OHEMSampler(BaseSampler):
    method __init__ (line 9) | def __init__(self,
    method hard_mining (line 26) | def hard_mining(self, inds, num_expected, bboxes, labels, feats):
    method _sample_pos (line 43) | def _sample_pos(self,
    method _sample_neg (line 59) | def _sample_neg(self,

FILE: mmdetection/mmdet/core/bbox/samplers/pseudo_sampler.py
  class PseudoSampler (line 7) | class PseudoSampler(BaseSampler):
    method __init__ (line 9) | def __init__(self, **kwargs):
    method _sample_pos (line 12) | def _sample_pos(self, **kwargs):
    method _sample_neg (line 15) | def _sample_neg(self, **kwargs):
    method sample (line 18) | def sample(self, assign_result, bboxes, gt_bboxes, **kwargs):

FILE: mmdetection/mmdet/core/bbox/samplers/random_sampler.py
  class RandomSampler (line 7) | class RandomSampler(BaseSampler):
    method __init__ (line 9) | def __init__(self,
    method random_choice (line 19) | def random_choice(gallery, num):
    method _sample_pos (line 35) | def _sample_pos(self, assign_result, num_expected, **kwargs):
    method _sample_neg (line 45) | def _sample_neg(self, assign_result, num_expected, **kwargs):

FILE: mmdetection/mmdet/core/bbox/samplers/sampling_result.py
  class SamplingResult (line 4) | class SamplingResult(object):
    method __init__ (line 6) | def __init__(self, pos_inds, neg_inds, bboxes, gt_bboxes, assign_result,
    method bboxes (line 23) | def bboxes(self):

FILE: mmdetection/mmdet/core/bbox/transforms.py
  function bbox2delta (line 6) | def bbox2delta(proposals, gt, means=[0, 0, 0, 0], stds=[1, 1, 1, 1]):
  function delta2bbox (line 34) | def delta2bbox(rois,
  function bbox_flip (line 71) | def bbox_flip(bboxes, img_shape):
  function bbox_mapping (line 91) | def bbox_mapping(bboxes, img_shape, scale_factor, flip):
  function bbox_mapping_back (line 99) | def bbox_mapping_back(bboxes, img_shape, scale_factor, flip):
  function bbox2roi (line 106) | def bbox2roi(bbox_list):
  function roi2bbox (line 128) | def roi2bbox(rois):
  function bbox2result (line 138) | def bbox2result(bboxes, labels, num_classes):
  function distance2bbox (line 159) | def distance2bbox(points, distance, max_shape=None):

FILE: mmdetection/mmdet/core/evaluation/bbox_overlaps.py
  function bbox_overlaps (line 4) | def bbox_overlaps(bboxes1, bboxes2, mode='iou'):

FILE: mmdetection/mmdet/core/evaluation/class_names.py
  function voc_classes (line 4) | def voc_classes():
  function imagenet_det_classes (line 12) | def imagenet_det_classes():
  function imagenet_vid_classes (line 53) | def imagenet_vid_classes():
  function coco_classes (line 63) | def coco_classes():
  function get_classes (line 89) | def get_classes(dataset):

FILE: mmdetection/mmdet/core/evaluation/coco_utils.py
  function coco_eval (line 9) | def coco_eval(result_file, result_types, coco, max_dets=(100, 300, 1000)):
  function fast_eval_recall (line 41) | def fast_eval_recall(results,
  function xyxy2xywh (line 78) | def xyxy2xywh(bbox):
  function proposal2json (line 88) | def proposal2json(dataset, results):
  function det2json (line 103) | def det2json(dataset, results):
  function segm2json (line 120) | def segm2json(dataset, results):
  function results2json (line 140) | def results2json(dataset, results, out_file):

FILE: mmdetection/mmdet/core/evaluation/eval_hooks.py
  class DistEvalHook (line 18) | class DistEvalHook(Hook):
    method __init__ (line 20) | def __init__(self, dataset, interval=1):
    method after_train_epoch (line 32) | def after_train_epoch(self, runner):
    method evaluate (line 73) | def evaluate(self):
  class DistEvalmAPHook (line 77) | class DistEvalmAPHook(DistEvalHook):
    method evaluate (line 79) | def evaluate(self, runner, results):
  class CocoDistEvalRecallHook (line 118) | class CocoDistEvalRecallHook(DistEvalHook):
    method __init__ (line 120) | def __init__(self,
    method evaluate (line 128) | def evaluate(self, runner, results):
  class CocoDistEvalmAPHook (line 138) | class CocoDistEvalmAPHook(DistEvalHook):
    method evaluate (line 140) | def evaluate(self, runner, results):

FILE: mmdetection/mmdet/core/evaluation/mean_ap.py
  function average_precision (line 9) | def average_precision(recalls, precisions, mode='area'):
  function tpfp_imagenet (line 56) | def tpfp_imagenet(det_bboxes,
  function tpfp_default (line 137) | def tpfp_default(det_bboxes, gt_bboxes, gt_ignore, iou_thr, area_ranges=...
  function get_cls_results (line 202) | def get_cls_results(det_results, gt_bboxes, gt_labels, gt_ignore, class_...
  function eval_map (line 220) | def eval_map(det_results,
  function print_map_summary (line 332) | def print_map_summary(mean_ap, results, dataset=None):

FILE: mmdetection/mmdet/core/evaluation/recall.py
  function _recalls (line 7) | def _recalls(all_ious, proposal_nums, thrs):
  function set_recall_param (line 40) | def set_recall_param(proposal_nums, iou_thrs):
  function eval_recalls (line 62) | def eval_recalls(gts,
  function print_recall_summary (line 105) | def print_recall_summary(recalls,
  function plot_num_recall (line 138) | def plot_num_recall(recalls, proposal_nums):
  function plot_iou_recall (line 163) | def plot_iou_recall(recalls, iou_thrs):

FILE: mmdetection/mmdet/core/loss/losses.py
  function weighted_nll_loss (line 9) | def weighted_nll_loss(pred, label, weight, avg_factor=None):
  function weighted_cross_entropy (line 16) | def weighted_cross_entropy(pred, label, weight, avg_factor=None, reduce=...
  function weighted_binary_cross_entropy (line 26) | def weighted_binary_cross_entropy(pred, label, weight, avg_factor=None):
  function py_sigmoid_focal_loss (line 36) | def py_sigmoid_focal_loss(pred,
  function weighted_sigmoid_focal_loss (line 59) | def weighted_sigmoid_focal_loss(pred,
  function mask_cross_entropy (line 73) | def mask_cross_entropy(pred, target, label):
  function smooth_l1_loss (line 81) | def smooth_l1_loss(pred, target, beta=1.0, reduction='mean'):
  function weighted_smoothl1 (line 97) | def weighted_smoothl1(pred, target, weight, beta=1.0, avg_factor=None):
  function accuracy (line 104) | def accuracy(pred, target, topk=1):
  function _expand_binary_labels (line 123) | def _expand_binary_labels(labels, label_weights, label_channels):
  function iou_loss (line 133) | def iou_loss(pred_bboxes, target_bboxes, reduction='mean'):

FILE: mmdetection/mmdet/core/mask/mask_target.py
  function mask_target (line 6) | def mask_target(pos_proposals_list, pos_assigned_gt_inds_list, gt_masks_...
  function mask_target_single (line 15) | def mask_target_single(pos_proposals, pos_assigned_gt_inds, gt_masks, cfg):

FILE: mmdetection/mmdet/core/mask/utils.py
  function split_combined_polys (line 4) | def split_combined_polys(polys, poly_lens, polys_per_mask):

FILE: mmdetection/mmdet/core/post_processing/bbox_nms.py
  function multiclass_nms (line 6) | def multiclass_nms(multi_bboxes,

FILE: mmdetection/mmdet/core/post_processing/merge_augs.py
  function merge_aug_proposals (line 9) | def merge_aug_proposals(aug_proposals, img_metas, rpn_test_cfg):
  function merge_aug_bboxes (line 41) | def merge_aug_bboxes(aug_bboxes, aug_scores, img_metas, rcnn_test_cfg):
  function merge_aug_scores (line 68) | def merge_aug_scores(aug_scores):
  function merge_aug_masks (line 76) | def merge_aug_masks(aug_masks, img_metas, rcnn_test_cfg, weights=None):

FILE: mmdetection/mmdet/core/utils/dist_utils.py
  function _allreduce_coalesced (line 9) | def _allreduce_coalesced(tensors, world_size, bucket_size_mb=-1):
  function allreduce_grads (line 31) | def allreduce_grads(model, coalesce=True, bucket_size_mb=-1):
  class DistOptimizerHook (line 44) | class DistOptimizerHook(OptimizerHook):
    method __init__ (line 46) | def __init__(self, grad_clip=None, coalesce=True, bucket_size_mb=-1):
    method after_train_iter (line 51) | def after_train_iter(self, runner):

FILE: mmdetection/mmdet/core/utils/misc.py
  function tensor2imgs (line 8) | def tensor2imgs(tensor, mean=(0, 0, 0), std=(1, 1, 1), to_rgb=True):
  function multi_apply (line 21) | def multi_apply(func, *args, **kwargs):
  function unmap (line 27) | def unmap(data, count, inds, fill=0):

FILE: mmdetection/mmdet/datasets/coco.py
  class CocoDataset (line 7) | class CocoDataset(CustomDataset):
    method load_annotations (line 24) | def load_annotations(self, ann_file):
    method get_ann_info (line 39) | def get_ann_info(self, idx):
    method _filter_imgs (line 45) | def _filter_imgs(self, min_size=32):
    method _parse_ann_info (line 56) | def _parse_ann_info(self, ann_info, with_mask=True):

FILE: mmdetection/mmdet/datasets/concat_dataset.py
  class ConcatDataset (line 5) | class ConcatDataset(_ConcatDataset):
    method __init__ (line 15) | def __init__(self, datasets):

FILE: mmdetection/mmdet/datasets/custom.py
  class CustomDataset (line 15) | class CustomDataset(Dataset):
    method __init__ (line 39) | def __init__(self,
    method __len__ (line 130) | def __len__(self):
    method load_annotations (line 133) | def load_annotations(self, ann_file):
    method load_proposals (line 136) | def load_proposals(self, proposal_file):
    method get_ann_info (line 139) | def get_ann_info(self, idx):
    method _filter_imgs (line 142) | def _filter_imgs(self, min_size=32):
    method _set_group_flag (line 150) | def _set_group_flag(self):
    method _rand_another (line 162) | def _rand_another(self, idx):
    method __getitem__ (line 166) | def __getitem__(self, idx):
    method prepare_train_img (line 176) | def prepare_train_img(self, idx):
    method prepare_test_img (line 269) | def prepare_test_img(self, idx):

FILE: mmdetection/mmdet/datasets/extra_aug.py
  class ExtraAugmentation (line 8) | class ExtraAugmentation(object):
    method __init__ (line 10) | def __init__(self, **kwargs):
    method transform_from_dict (line 13) | def transform_from_dict(self, **kwargs):
    method __call__ (line 21) | def __call__(self, img):

FILE: mmdetection/mmdet/datasets/loader/build_loader.py
  function build_dataloader (line 15) | def build_dataloader(dataset,

FILE: mmdetection/mmdet/datasets/loader/sampler.py
  class DistributedSampler (line 12) | class DistributedSampler(_DistributedSampler):
    method __init__ (line 14) | def __init__(self, dataset, num_replicas=None, rank=None, shuffle=True):
    method __iter__ (line 18) | def __iter__(self):
  class GroupSampler (line 38) | class GroupSampler(Sampler):
    method __init__ (line 40) | def __init__(self, dataset, samples_per_gpu=1):
    method __iter__ (line 51) | def __iter__(self):
    method __len__ (line 74) | def __len__(self):
  class DistributedGroupSampler (line 78) | class DistributedGroupSampler(Sampler):
    method __init__ (line 93) | def __init__(self,
    method __iter__ (line 119) | def __iter__(self):
    method __len__ (line 155) | def __len__(self):
    method set_epoch (line 158) | def set_epoch(self, epoch):

FILE: mmdetection/mmdet/datasets/repeat_dataset.py
  class RepeatDataset (line 4) | class RepeatDataset(object):
    method __init__ (line 6) | def __init__(self, dataset, times):
    method __getitem__ (line 15) | def __getitem__(self, idx):
    method __len__ (line 18) | def __len__(self):

FILE: mmdetection/mmdet/datasets/transforms.py
  class ImageTransform (line 16) | class ImageTransform(object):
    method __init__ (line 26) | def __init__(self,
    method __call__ (line 36) | def __call__(self, img, scale, flip=False, keep_ratio=True):
  function bbox_flip (line 57) | def bbox_flip(bboxes, img_shape):
  class BboxTransform (line 72) | class BboxTransform(object):
    method __init__ (line 80) | def __init__(self, max_num_gts=None):
    method __call__ (line 83) | def __call__(self, bboxes, img_shape, scale_factor, flip=False):
  class MaskTransform (line 98) | class MaskTransform(object):
    method __call__ (line 106) | def __call__(self, masks, pad_shape, scale_factor, flip=False):
  class SegMapTransform (line 120) | class SegMapTransform(object):
    method __init__ (line 128) | def __init__(self, size_divisor=None):
    method __call__ (line 131) | def __call__(self, img, scale, flip=False, keep_ratio=True):
  class Numpy2Tensor (line 143) | class Numpy2Tensor(object):
    method __init__ (line 145) | def __init__(self):
    method __call__ (line 148) | def __call__(self, *args):
  class RandomCropNearBBox (line 155) | class RandomCropNearBBox(A.DualTransform):
    method __init__ (line 166) | def __init__(self, max_part_shift=0.3, always_apply=False, p=1.0):
    method apply (line 170) | def apply(self, img, x_min=0, x_max=0, y_min=0, y_max=0, **params):
    method get_params_dependent_on_targets (line 173) | def get_params_dependent_on_targets(self, params):
    method apply_to_bbox (line 190) | def apply_to_bbox(self, bbox, x_min=0, x_max=0, y_min=0, y_max=0, **pa...
    method targets_as_params (line 203) | def targets_as_params(self):
    method get_transform_init_args_names (line 206) | def get_transform_init_args_names(self):

FILE: mmdetection/mmdet/datasets/utils.py
  function to_tensor (line 15) | def to_tensor(data):
  function random_scale (line 36) | def random_scale(img_scales, mode='range'):
  function show_ann (line 70) | def show_ann(coco, img, ann_info):
  function get_dataset (line 77) | def get_dataset(data_cfg):
  function rle_decode (line 119) | def rle_decode(rle, h: int, w: int):

FILE: mmdetection/mmdet/datasets/voc.py
  class VOCDataset (line 4) | class VOCDataset(XMLDataset):
    method __init__ (line 11) | def __init__(self, **kwargs):

FILE: mmdetection/mmdet/datasets/xml_style.py
  class XMLDataset (line 10) | class XMLDataset(CustomDataset):
    method __init__ (line 12) | def __init__(self, **kwargs):
    method load_annotations (line 16) | def load_annotations(self, ann_file):
    method get_ann_info (line 32) | def get_ann_info(self, idx):

FILE: mmdetection/mmdet/models/anchor_heads/anchor_head.py
  class AnchorHead (line 16) | class AnchorHead(nn.Module):
    method __init__ (line 33) | def __init__(self,
    method _init_layers (line 72) | def _init_layers(self):
    method init_weights (line 77) | def init_weights(self):
    method forward_single (line 81) | def forward_single(self, x):
    method forward (line 86) | def forward(self, feats):
    method get_anchors (line 89) | def get_anchors(self, featmap_sizes, img_metas):
    method loss_single (line 128) | def loss_single(self, cls_score, bbox_pred, labels, label_weights,
    method loss (line 168) | def loss(self,
    method get_bboxes (line 213) | def get_bboxes(self, cls_scores, bbox_preds, img_metas, cfg,
    method get_bboxes_single (line 239) | def get_bboxes_single(self,

FILE: mmdetection/mmdet/models/anchor_heads/fcos_head.py
  class FCOSHead (line 15) | class FCOSHead(nn.Module):
    method __init__ (line 17) | def __init__(self,
    method _init_layers (line 41) | def _init_layers(self):
    method init_weights (line 73) | def init_weights(self):
    method forward (line 83) | def forward(self, feats):
    method forward_single (line 86) | def forward_single(self, x, scale):
    method loss (line 101) | def loss(self,
    method get_bboxes (line 173) | def get_bboxes(self,
    method get_bboxes_single (line 205) | def get_bboxes_single(self,
    method get_points (line 254) | def get_points(self, featmap_sizes, dtype, device):
    method get_points_single (line 272) | def get_points_single(self, featmap_size, stride, dtype, device):
    method fcos_target (line 283) | def fcos_target(self, points, gt_bboxes_list, gt_labels_list):
    method fcos_target_single (line 321) | def fcos_target_single(self, gt_bboxes, gt_labels, points, regress_ran...
    method centerness_target (line 364) | def centerness_target(self, pos_bbox_targets):

FILE: mmdetection/mmdet/models/anchor_heads/retina_head.py
  class RetinaHead (line 11) | class RetinaHead(AnchorHead):
    method __init__ (line 13) | def __init__(self,
    method _init_layers (line 38) | def _init_layers(self):
    method init_weights (line 70) | def init_weights(self):
    method forward_single (line 79) | def forward_single(self, x):

FILE: mmdetection/mmdet/models/anchor_heads/rpn_head.py
  class RPNHead (line 13) | class RPNHead(AnchorHead):
    method __init__ (line 15) | def __init__(self, in_channels, **kwargs):
    method _init_layers (line 18) | def _init_layers(self):
    method init_weights (line 25) | def init_weights(self):
    method forward_single (line 30) | def forward_single(self, x):
    method loss (line 37) | def loss(self,
    method get_bboxes_single (line 55) | def get_bboxes_single(self,

FILE: mmdetection/mmdet/models/anchor_heads/ssd_head.py
  class SSDHead (line 14) | class SSDHead(AnchorHead):
    method __init__ (line 16) | def __init__(self,
    method init_weights (line 95) | def init_weights(self):
    method forward (line 100) | def forward(self, feats):
    method loss_single (line 109) | def loss_single(self, cls_score, bbox_pred, labels, label_weights,
    method loss (line 133) | def loss(self,

FILE: mmdetection/mmdet/models/backbones/resnet.py
  class BasicBlock (line 15) | class BasicBlock(nn.Module):
    method __init__ (line 18) | def __init__(self,
    method norm1 (line 61) | def norm1(self):
    method norm2 (line 65) | def norm2(self):
    method forward (line 68) | def forward(self, x):
  class Bottleneck (line 87) | class Bottleneck(nn.Module):
    method __init__ (line 90) | def __init__(self,
    method norm1 (line 191) | def norm1(self):
    method norm2 (line 195) | def norm2(self):
    method norm3 (line 199) | def norm3(self):
    method forward (line 202) | def forward(self, x):
  function make_res_layer (line 244) | def make_res_layer(block,
  class ResNet (line 299) | class ResNet(nn.Module):
    method __init__ (line 331) | def __init__(self,
    method norm1 (line 403) | def norm1(self):
    method _make_stem_layer (line 406) | def _make_stem_layer(self):
    method _freeze_stages (line 420) | def _freeze_stages(self):
    method init_weights (line 433) | def init_weights(self, pretrained=None):
    method forward (line 459) | def forward(self, x):
    method train (line 472) | def train(self, mode=True):

FILE: mmdetection/mmdet/models/backbones/resnext.py
  class Bottleneck (line 12) | class Bottleneck(_Bottleneck):
    method __init__ (line 14) | def __init__(self, *args, groups=1, base_width=4, **kwargs):
  function make_res_layer (line 94) | def make_res_layer(block,
  class ResNeXt (line 155) | class ResNeXt(ResNet):
    method __init__ (line 187) | def __init__(self, groups=1, base_width=4, **kwargs):

FILE: mmdetection/mmdet/models/backbones/ssd_vgg.py
  class SSDVGG (line 13) | class SSDVGG(VGG):
    method __init__ (line 19) | def __init__(self,
    method init_weights (line 55) | def init_weights(self, pretrained=None):
    method forward (line 76) | def forward(self, x):
    method _make_extra_layers (line 92) | def _make_extra_layers(self, outplanes):
  class L2Norm (line 119) | class L2Norm(nn.Module):
    method __init__ (line 121) | def __init__(self, n_dims, scale=20., eps=1e-10):
    method forward (line 128) | def forward(self, x):

FILE: mmdetection/mmdet/models/bbox_heads/bbox_head.py
  class BBoxHead (line 11) | class BBoxHead(nn.Module):
    method __init__ (line 15) | def __init__(self,
    method init_weights (line 49) | def init_weights(self):
    method forward (line 57) | def forward(self, x):
    method get_target (line 65) | def get_target(self, sampling_results, gt_bboxes, gt_labels,
    method loss (line 83) | def loss(self,
    method get_det_bboxes (line 110) | def get_det_bboxes(self,
    method refine_bboxes (line 140) | def refine_bboxes(self, rois, labels, bbox_preds, pos_is_gts, img_metas):
    method regress_by_class (line 180) | def regress_by_class(self, rois, label, bbox_pred, img_meta):

FILE: mmdetection/mmdet/models/bbox_heads/convfc_bbox_head.py
  class ConvFCBBoxHead (line 9) | class ConvFCBBoxHead(BBoxHead):
    method __init__ (line 18) | def __init__(self,
    method _add_conv_fc_branch (line 83) | def _add_conv_fc_branch(self,
    method init_weights (line 124) | def init_weights(self):
    method forward (line 132) | def forward(self, x):
  class SharedFCBBoxHead (line 172) | class SharedFCBBoxHead(ConvFCBBoxHead):
    method __init__ (line 174) | def __init__(self, num_fcs=2, fc_out_channels=1024, *args, **kwargs):

FILE: mmdetection/mmdet/models/builder.py
  function _build_module (line 8) | def _build_module(cfg, registry, default_args):
  function build (line 27) | def build(cfg, registry, default_args=None):
  function build_backbone (line 35) | def build_backbone(cfg):
  function build_neck (line 39) | def build_neck(cfg):
  function build_roi_extractor (line 43) | def build_roi_extractor(cfg):
  function build_shared_head (line 47) | def build_shared_head(cfg):
  function build_head (line 51) | def build_head(cfg):
  function build_detector (line 55) | def build_detector(cfg, train_cfg=None, test_cfg=None):

FILE: mmdetection/mmdet/models/detectors/base.py
  class BaseDetector (line 12) | class BaseDetector(nn.Module):
    method __init__ (line 17) | def __init__(self):
    method with_neck (line 21) | def with_neck(self):
    method with_shared_head (line 25) | def with_shared_head(self):
    method with_bbox (line 29) | def with_bbox(self):
    method with_mask (line 33) | def with_mask(self):
    method extract_feat (line 37) | def extract_feat(self, imgs):
    method extract_feats (line 40) | def extract_feats(self, imgs):
    method forward_train (line 46) | def forward_train(self, imgs, img_metas, **kwargs):
    method simple_test (line 50) | def simple_test(self, img, img_meta, **kwargs):
    method aug_test (line 54) | def aug_test(self, imgs, img_metas, **kwargs):
    method init_weights (line 57) | def init_weights(self, pretrained=None):
    method forward_test (line 62) | def forward_test(self, imgs, img_metas, **kwargs):
    method forward (line 82) | def forward(self, img, img_meta, return_loss=True, **kwargs):
    method show_result (line 88) | def show_result(self,

FILE: mmdetection/mmdet/models/detectors/cascade_rcnn.py
  class CascadeRCNN (line 15) | class CascadeRCNN(BaseDetector, RPNTestMixin):
    method __init__ (line 17) | def __init__(self,
    method with_rpn (line 89) | def with_rpn(self):
    method init_weights (line 92) | def init_weights(self, pretrained=None):
    method extract_feat (line 114) | def extract_feat(self, img):
    method forward_train (line 120) | def forward_train(self,
    method simple_test (line 240) | def simple_test(self, img, img_meta, proposals=None, rescale=False):
    method aug_test (line 364) | def aug_test(self, img, img_meta, proposals=None, rescale=False):
    method show_result (line 367) | def show_result(self, data, result, img_norm_cfg, **kwargs):

FILE: mmdetection/mmdet/models/detectors/ensemble_htc.py
  class EnsembleHTC (line 7) | class EnsembleHTC(BaseDetector):
    method __init__ (line 8) | def __init__(self, models):
    method simple_test (line 12) | def simple_test(self, img, img_meta, **kwargs):
    method forward_train (line 15) | def forward_train(self, imgs, img_metas, **kwargs):
    method extract_feat (line 18) | def extract_feat(self, imgs):
    method aug_test (line 21) | def aug_test(self, imgs, img_metas, **kwargs):

FILE: mmdetection/mmdet/models/detectors/fast_rcnn.py
  class FastRCNN (line 6) | class FastRCNN(TwoStageDetector):
    method __init__ (line 8) | def __init__(self,
    method forward_test (line 31) | def forward_test(self, imgs, img_metas, proposals, **kwargs):

FILE: mmdetection/mmdet/models/detectors/faster_rcnn.py
  class FasterRCNN (line 6) | class FasterRCNN(TwoStageDetector):
    method __init__ (line 8) | def __init__(self,

FILE: mmdetection/mmdet/models/detectors/fcos.py
  class FCOS (line 6) | class FCOS(SingleStageDetector):
    method __init__ (line 8) | def __init__(self,

FILE: mmdetection/mmdet/models/detectors/htc.py
  class HybridTaskCascade (line 14) | class HybridTaskCascade(CascadeRCNN, RPNTestMixin):
    method __init__ (line 16) | def __init__(self,
    method with_semantic (line 38) | def with_semantic(self):
    method _bbox_forward_train (line 44) | def _bbox_forward_train(self,
    method _mask_forward_train (line 74) | def _mask_forward_train(self,
    method _bbox_forward_test (line 115) | def _bbox_forward_test(self, stage, x, rois, semantic_feat=None):
    method _mask_forward_test (line 130) | def _mask_forward_test(self, stage, x, bboxes, semantic_feat=None):
    method forward_train (line 158) | def forward_train(self,
    method simple_test (line 270) | def simple_test(self, img, img_meta, proposals=None, rescale=False):
    method aug_test (line 395) | def aug_test(self, imgs, img_metas, proposals=None, rescale=False):

FILE: mmdetection/mmdet/models/detectors/mask_rcnn.py
  class MaskRCNN (line 6) | class MaskRCNN(TwoStageDetector):
    method __init__ (line 8) | def __init__(self,

FILE: mmdetection/mmdet/models/detectors/retinanet.py
  class RetinaNet (line 6) | class RetinaNet(SingleStageDetector):
    method __init__ (line 8) | def __init__(self,

FILE: mmdetection/mmdet/models/detectors/rpn.py
  class RPN (line 11) | class RPN(BaseDetector, RPNTestMixin):
    method __init__ (line 13) | def __init__(self,
    method init_weights (line 28) | def init_weights(self, pretrained=None):
    method extract_feat (line 35) | def extract_feat(self, img):
    method forward_train (line 41) | def forward_train(self,
    method simple_test (line 57) | def simple_test(self, img, img_meta, rescale=False):
    method aug_test (line 66) | def aug_test(self, imgs, img_metas, rescale=False):
    method show_result (line 79) | def show_result(self, data, result, img_norm_cfg, dataset=None, top_k=...

FILE: mmdetection/mmdet/models/detectors/single_stage.py
  class SingleStageDetector (line 10) | class SingleStageDetector(BaseDetector):
    method __init__ (line 12) | def __init__(self,
    method init_weights (line 28) | def init_weights(self, pretrained=None):
    method extract_feat (line 39) | def extract_feat(self, img):
    method forward_train (line 45) | def forward_train(self,
    method simple_test (line 58) | def simple_test(self, img, img_meta, rescale=False):
    method aug_test (line 69) | def aug_test(self, imgs, img_metas, rescale=False):

FILE: mmdetection/mmdet/models/detectors/test_mixins.py
  class RPNTestMixin (line 5) | class RPNTestMixin(object):
    method simple_test_rpn (line 7) | def simple_test_rpn(self, x, img_meta, rpn_test_cfg):
    method aug_test_rpn (line 13) | def aug_test_rpn(self, feats, img_metas, rpn_test_cfg):
  class BBoxTestMixin (line 28) | class BBoxTestMixin(object):
    method simple_test_bboxes (line 30) | def simple_test_bboxes(self,
    method aug_test_bboxes (line 55) | def aug_test_bboxes(self, feats, img_metas, proposal_list, rcnn_test_c...
  class MaskTestMixin (line 92) | class MaskTestMixin(object):
    method simple_test_mask (line 94) | def simple_test_mask(self,
    method aug_test_mask (line 121) | def aug_test_mask(self, feats, img_metas, det_bboxes, det_labels):

FILE: mmdetection/mmdet/models/detectors/two_stage.py
  class TwoStageDetector (line 12) | class TwoStageDetector(BaseDetector, RPNTestMixin, BBoxTestMixin,
    method __init__ (line 15) | def __init__(self,
    method with_rpn (line 60) | def with_rpn(self):
    method init_weights (line 63) | def init_weights(self, pretrained=None):
    method extract_feat (line 84) | def extract_feat(self, img):
    method forward_train (line 90) | def forward_train(self,
    method simple_test (line 192) | def simple_test(self, img, img_meta, proposals=None, rescale=False):
    method aug_test (line 213) | def aug_test(self, imgs, img_metas, rescale=False):

FILE: mmdetection/mmdet/models/mask_heads/fcn_mask_head.py
  class FCNMaskHead (line 13) | class FCNMaskHead(nn.Module):
    method __init__ (line 15) | def __init__(self,
    method init_weights (line 79) | def init_weights(self):
    method forward (line 87) | def forward(self, x):
    method get_target (line 97) | def get_target(self, sampling_results, gt_masks, rcnn_train_cfg):
    method loss (line 106) | def loss(self, mask_pred, mask_targets, labels):
    method get_seg_masks (line 116) | def get_seg_masks(self, mask_pred, det_bboxes, det_labels, rcnn_test_cfg,

FILE: mmdetection/mmdet/models/mask_heads/fused_semantic_head.py
  class FusedSemanticHead (line 10) | class FusedSemanticHead(nn.Module):
    method __init__ (line 24) | def __init__(self,
    method init_weights (line 79) | def init_weights(self):
    method forward (line 82) | def forward(self, feats):
    method loss (line 101) | def loss(self, mask_pred, labels):

FILE: mmdetection/mmdet/models/mask_heads/htc_mask_head.py
  class HTCMaskHead (line 7) | class HTCMaskHead(FCNMaskHead):
    method __init__ (line 9) | def __init__(self, *args, **kwargs):
    method init_weights (line 18) | def init_weights(self):
    method forward (line 22) | def forward(self, x, res_feat=None, return_logits=True, return_feat=Tr...

FILE: mmdetection/mmdet/models/necks/fpn.py
  class FPN (line 10) | class FPN(nn.Module):
    method __init__ (line 12) | def __init__(self,
    method init_weights (line 92) | def init_weights(self):
    method forward (line 97) | def forward(self, inputs):

FILE: mmdetection/mmdet/models/registry.py
  class Registry (line 4) | class Registry(object):
    method __init__ (line 6) | def __init__(self, name):
    method name (line 11) | def name(self):
    method module_dict (line 15) | def module_dict(self):
    method _register_module (line 18) | def _register_module(self, module_class):
    method register_module (line 33) | def register_module(self, cls):

FILE: mmdetection/mmdet/models/roi_extractors/single_level.py
  class SingleRoIExtractor (line 11) | class SingleRoIExtractor(nn.Module):
    method __init__ (line 24) | def __init__(self,
    method num_inputs (line 36) | def num_inputs(self):
    method init_weights (line 40) | def init_weights(self):
    method build_roi_layers (line 43) | def build_roi_layers(self, layer_cfg, featmap_strides):
    method map_roi_levels (line 52) | def map_roi_levels(self, rois, num_levels):
    method forward (line 73) | def forward(self, feats, rois):

FILE: mmdetection/mmdet/models/shared_heads/res_layer.py
  class ResLayer (line 12) | class ResLayer(nn.Module):
    method __init__ (line 14) | def __init__(self,
    method init_weights (line 46) | def init_weights(self, pretrained=None):
    method forward (line 59) | def forward(self, x):
    method train (line 64) | def train(self, mode=True):

FILE: mmdetection/mmdet/models/utils/conv_module.py
  function build_conv_layer (line 16) | def build_conv_layer(cfg, *args, **kwargs):
  class ConvModule (line 44) | class ConvModule(nn.Module):
    method __init__ (line 67) | def __init__(self,
    method norm (line 139) | def norm(self):
    method init_weights (line 142) | def init_weights(self):
    method forward (line 148) | def forward(self, x, activate=True, norm=True):

FILE: mmdetection/mmdet/models/utils/conv_ws.py
  function conv_ws_2d (line 5) | def conv_ws_2d(input,
  class ConvWS2d (line 21) | class ConvWS2d(nn.Conv2d):
    method __init__ (line 23) | def __init__(self,
    method forward (line 44) | def forward(self, x):

FILE: mmdetection/mmdet/models/utils/norm.py
  function build_norm_layer (line 13) | def build_norm_layer(cfg, num_features, postfix=''):

FILE: mmdetection/mmdet/models/utils/scale.py
  class Scale (line 5) | class Scale(nn.Module):
    method __init__ (line 7) | def __init__(self, scale=1.0):
    method forward (line 11) | def forward(self, x):

FILE: mmdetection/mmdet/models/utils/weight_init.py
  function xavier_init (line 5) | def xavier_init(module, gain=1, bias=0, distribution='normal'):
  function normal_init (line 15) | def normal_init(module, mean=0, std=1, bias=0):
  function uniform_init (line 21) | def uniform_init(module, a=0, b=1, bias=0):
  function kaiming_init (line 27) | def kaiming_init(module,
  function bias_init_with_prob (line 43) | def bias_init_with_prob(prior_prob):

FILE: mmdetection/mmdet/ops/dcn/functions/deform_conv.py
  class DeformConvFunction (line 8) | class DeformConvFunction(Function):
    method forward (line 11) | def forward(ctx,
    method backward (line 55) | def backward(ctx, grad_output):
    method _output_size (line 92) | def _output_size(input, weight, padding, dilation, stride):
  class ModulatedDeformConvFunction (line 108) | class ModulatedDeformConvFunction(Function):
    method forward (line 111) | def forward(ctx,
    method backward (line 146) | def backward(ctx, grad_output):
    method _infer_shape (line 168) | def _infer_shape(ctx, input, weight):

FILE: mmdetection/mmdet/ops/dcn/functions/deform_pool.py
  class DeformRoIPoolingFunction (line 7) | class DeformRoIPoolingFunction(Function):
    method forward (line 10) | def forward(ctx,
    method backward (line 50) | def backward(ctx, grad_output):

FILE: mmdetection/mmdet/ops/dcn/modules/deform_conv.py
  class DeformConv (line 10) | class DeformConv(nn.Module):
    method __init__ (line 12) | def __init__(self,
    method reset_parameters (line 47) | def reset_parameters(self):
    method forward (line 54) | def forward(self, x, offset):
  class DeformConvPack (line 59) | class DeformConvPack(DeformConv):
    method __init__ (line 61) | def __init__(self, *args, **kwargs):
    method init_offset (line 74) | def init_offset(self):
    method forward (line 78) | def forward(self, x):
  class ModulatedDeformConv (line 84) | class ModulatedDeformConv(nn.Module):
    method __init__ (line 86) | def __init__(self,
    method reset_parameters (line 116) | def reset_parameters(self):
    method forward (line 125) | def forward(self, x, offset, mask):
  class ModulatedDeformConvPack (line 131) | class ModulatedDeformConvPack(ModulatedDeformConv):
    method __init__ (line 133) | def __init__(self, *args, **kwargs):
    method init_offset (line 146) | def init_offset(self):
    method forward (line 150) | def forward(self, x):

FILE: mmdetection/mmdet/ops/dcn/modules/deform_pool.py
  class DeformRoIPooling (line 6) | class DeformRoIPooling(nn.Module):
    method __init__ (line 8) | def __init__(self,
    method forward (line 27) | def forward(self, data, rois, offset):
  class DeformRoIPoolingPack (line 36) | class DeformRoIPoolingPack(DeformRoIPooling):
    method __init__ (line 38) | def __init__(self,
    method forward (line 72) | def forward(self, data, rois):
  class ModulatedDeformRoIPoolingPack (line 95) | class ModulatedDeformRoIPoolingPack(DeformRoIPooling):
    method __init__ (line 97) | def __init__(self,
    method forward (line 150) | def forward(self, data, rois):

FILE: mmdetection/mmdet/ops/dcn/src/deform_conv_cuda.cpp
  function shape_check (line 61) | void shape_check(at::Tensor input, at::Tensor offset, at::Tensor *gradOu...
  function deform_conv_forward_cuda (line 151) | int deform_conv_forward_cuda(at::Tensor input, at::Tensor weight,
  function deform_conv_backward_input_cuda (line 260) | int deform_conv_backward_input_cuda(at::Tensor input, at::Tensor offset,
  function deform_conv_backward_parameters_cuda (line 373) | int deform_conv_backward_parameters_cuda(
  function modulated_deform_conv_cuda_forward (line 486) | void modulated_deform_conv_cuda_forward(
  function modulated_deform_conv_cuda_backward (line 566) | void modulated_deform_conv_cuda_backward(
  function PYBIND11_MODULE (line 681) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: mmdetection/mmdet/ops/dcn/src/deform_pool_cuda.cpp
  function deform_psroi_pooling_cuda_forward (line 30) | void deform_psroi_pooling_cuda_forward(
  function deform_psroi_pooling_cuda_backward (line 54) | void deform_psroi_pooling_cuda_backward(
  function PYBIND11_MODULE (line 81) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: mmdetection/mmdet/ops/nms/nms_wrapper.py
  function nms (line 8) | def nms(dets, iou_thr, device_id=None):
  function soft_nms (line 52) | def soft_nms(dets, iou_thr, method='linear', sigma=0.5, min_score=1e-3):

FILE: mmdetection/mmdet/ops/nms/setup.py
  function customize_compiler_for_nvcc (line 23) | def customize_compiler_for_nvcc(self):
  class custom_build_ext (line 60) | class custom_build_ext(build_ext):
    method build_extensions (line 62) | def build_extensions(self):

FILE: mmdetection/mmdet/ops/nms/src/nms_cpu.cpp
  function nms_cpu_kernel (line 5) | at::Tensor nms_cpu_kernel(const at::Tensor& dets, const float threshold) {
  function nms (line 61) | at::Tensor nms(const at::Tensor& dets, const float threshold) {
  function PYBIND11_MODULE (line 69) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: mmdetection/mmdet/ops/nms/src/nms_cuda.cpp
  function nms (line 8) | at::Tensor nms(const at::Tensor& dets, const float threshold) {
  function PYBIND11_MODULE (line 15) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: mmdetection/mmdet/ops/roi_align/functions/roi_align.py
  class RoIAlignFunction (line 6) | class RoIAlignFunction(Function):
    method forward (line 9) | def forward(ctx, features, rois, out_size, spatial_scale, sample_num=0):
    method backward (line 39) | def backward(ctx, grad_output):

FILE: mmdetection/mmdet/ops/roi_align/modules/roi_align.py
  class RoIAlign (line 5) | class RoIAlign(Module):
    method __init__ (line 7) | def __init__(self, out_size, spatial_scale, sample_num=0):
    method forward (line 14) | def forward(self, features, rois):

FILE: mmdetection/mmdet/ops/roi_align/src/roi_align_cuda.cpp
  function roi_align_forward_cuda (line 27) | int roi_align_forward_cuda(at::Tensor features, at::Tensor rois,
  function roi_align_backward_cuda (line 55) | int roi_align_backward_cuda(at::Tensor top_grad, at::Tensor rois,
  function PYBIND11_MODULE (line 82) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: mmdetection/mmdet/ops/roi_pool/functions/roi_pool.py
  class RoIPoolFunction (line 7) | class RoIPoolFunction(Function):
    method forward (line 10) | def forward(ctx, features, rois, out_size, spatial_scale):
    method backward (line 38) | def backward(ctx, grad_output):

FILE: mmdetection/mmdet/ops/roi_pool/modules/roi_pool.py
  class RoIPool (line 5) | class RoIPool(Module):
    method __init__ (line 7) | def __init__(self, out_size, spatial_scale):
    method forward (line 13) | def forward(self, features, rois):

FILE: mmdetection/mmdet/ops/roi_pool/src/roi_pool_cuda.cpp
  function roi_pooling_forward_cuda (line 26) | int roi_pooling_forward_cuda(at::Tensor features, at::Tensor rois,
  function roi_pooling_backward_cuda (line 54) | int roi_pooling_backward_cuda(at::Tensor top_grad, at::Tensor rois,
  function PYBIND11_MODULE (line 83) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: mmdetection/mmdet/ops/sigmoid_focal_loss/functions/sigmoid_focal_loss.py
  class SigmoidFocalLossFunction (line 8) | class SigmoidFocalLossFunction(Function):
    method forward (line 11) | def forward(ctx, input, target, gamma=2.0, alpha=0.25, reduction='mean'):
    method backward (line 31) | def backward(ctx, d_loss):

FILE: mmdetection/mmdet/ops/sigmoid_focal_loss/modules/sigmoid_focal_loss.py
  class SigmoidFocalLoss (line 6) | class SigmoidFocalLoss(nn.Module):
    method __init__ (line 8) | def __init__(self, gamma, alpha):
    method forward (line 13) | def forward(self, logits, targets):
    method __repr__ (line 18) | def __repr__(self):

FILE: mmdetection/mmdet/ops/sigmoid_focal_loss/src/sigmoid_focal_loss.cpp
  function SigmoidFocalLoss_forward (line 17) | at::Tensor SigmoidFocalLoss_forward(const at::Tensor &logits,
  function SigmoidFocalLoss_backward (line 27) | at::Tensor SigmoidFocalLoss_backward(const at::Tensor &logits,
  function PYBIND11_MODULE (line 38) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: mmdetection/setup.py
  function readme (line 7) | def readme():
  function get_git_hash (line 22) | def get_git_hash():
  function get_hash (line 48) | def get_hash():
  function write_version_py (line 63) | def write_version_py():
  function get_version (line 77) | def get_version():

FILE: mmdetection/tools/analyze_logs.py
  function cal_train_time (line 10) | def cal_train_time(log_dicts, args):
  function plot_curve (line 34) | def plot_curve(log_dicts, args):
  function add_plot_parser (line 94) | def add_plot_parser(subparsers):
  function add_time_parser (line 122) | def add_time_parser(subparsers):
  function parse_args (line 138) | def parse_args():
  function load_json_logs (line 148) | def load_json_logs(json_logs):
  function main (line 165) | def main():

FILE: mmdetection/tools/coco_eval.py
  function main (line 6) | def main():

FILE: mmdetection/tools/convert_datasets/pascal_voc.py
  function parse_xml (line 13) | def parse_xml(args):
  function cvt_annotations (line 67) | def cvt_annotations(devkit_path, years, split, out_file):
  function parse_args (line 94) | def parse_args():
  function main (line 103) | def main():

FILE: mmdetection/tools/publish_model.py
  function parse_args (line 6) | def parse_args():
  function process_checkpoint (line 15) | def process_checkpoint(in_file, out_file):
  function main (line 28) | def main():

FILE: mmdetection/tools/test.py
  function single_gpu_test (line 18) | def single_gpu_test(model, data_loader, show=False):
  function multi_gpu_test (line 37) | def multi_gpu_test(model, data_loader, tmpdir=None):
  function collect_results (line 60) | def collect_results(result_part, size, tmpdir=None):
  function parse_args (line 103) | def parse_args():
  function main (line 128) | def main():

FILE: mmdetection/tools/test_ensemble.py
  function single_gpu_test (line 19) | def single_gpu_test(model, data_loader, show=False):
  function multi_gpu_test (line 38) | def multi_gpu_test(model, data_loader, tmpdir=None):
  function collect_results (line 61) | def collect_results(result_part, size, tmpdir=None):
  function parse_args (line 104) | def parse_args():
  function main (line 128) | def main():

FILE: mmdetection/tools/train.py
  function parse_args (line 14) | def parse_args():
  function main (line 42) | def main():

FILE: mmdetection/tools/upgrade_model_version.py
  function convert (line 8) | def convert(in_file, out_file):
  function main (line 33) | def main():

FILE: mmdetection/tools/voc_eval.py
  function voc_eval (line 10) | def voc_eval(result_file, dataset, iou_thr=0.5):
  function main (line 46) | def main():

FILE: src/create_mmdetection_test.py
  function parse_args (line 12) | def parse_args():
  function convert (line 21) | def convert(group: dict, root) -> dict:
  function main (line 37) | def main():

FILE: src/create_mmdetection_train.py
  function parse_args (line 11) | def parse_args():
  function main (line 21) | def main():

FILE: src/draw.py
  function parse_args (line 17) | def parse_args():
  function get_spaced_colors (line 30) | def get_spaced_colors(n, start_color=(75, 0, 130)):
  function put_text (line 42) | def put_text(img, color, text, i, x_shift=10, y_shift=10):
  function draw_masks (line 50) | def draw_masks(img, masks, colors, classes):
  function get_gt_masks (line 63) | def get_gt_masks(annotation):
  function draw (line 70) | def draw(args, root, output, metric_threshold, colors, classes):
  function main (line 88) | def main():

FILE: src/eda.py
  function parse_args (line 14) | def parse_args():
  function draw_masks (line 21) | def draw_masks(img, masks):
  function main (line 30) | def main():

FILE: src/metric.py
  function precision_at (line 5) | def precision_at(threshold, iou):
  function calc_iou (line 14) | def calc_iou(y_true, y_prediction):
  function calc_score_per_class (line 42) | def calc_score_per_class(y_true, y_prediction):

FILE: src/prune.py
  function parse_args (line 6) | def parse_args():
  function main (line 13) | def main():

FILE: src/rle.py
  function kaggle_rle_encode (line 7) | def kaggle_rle_encode(mask):
  function kaggle_rle_decode (line 15) | def kaggle_rle_decode(rle, h, w):
  function coco_rle_encode (line 25) | def coco_rle_encode(mask):
  function coco_rle_decode (line 35) | def coco_rle_decode(rle, h, w):
  function kaggle2coco (line 39) | def kaggle2coco(kaggle_rle, h, w):
  function main (line 60) | def main():

FILE: src/rm_attribute_classes.py
  function parse_args (line 7) | def parse_args():
  function main (line 14) | def main():

FILE: src/split.py
  function parse_args (line 9) | def parse_args():
  function main (line 20) | def main():

FILE: src/submit.py
  function parse_args (line 14) | def parse_args():
  function decode_and_resize (line 24) | def decode_and_resize(
  function create_mask (line 41) | def create_mask(args):
  function main (line 90) | def main():

FILE: src/utils.py
  function group2mmdetection (line 7) | def group2mmdetection(group: dict) -> dict:
  function create_labeled_mask (line 32) | def create_labeled_mask(mask):
  function check_overlaps (line 36) | def check_overlaps(mask):
  function hard_overlaps_suppression (line 41) | def hard_overlaps_suppression(binary_mask, scores):

FILE: src/visualization.py
  function draw_bounding_box_on_image (line 9) | def draw_bounding_box_on_image(
  function draw_bounding_boxes_on_image_array (line 53) | def draw_bounding_boxes_on_image_array(
  function draw_bounding_boxes_on_image (line 61) | def draw_bounding_boxes_on_image(