SYMBOL INDEX (503 symbols across 36 files)

FILE: backbone.py
  function DCN (line 10) | def DCN(*args, **kwdargs):
  class Bottleneck (line 13) | class Bottleneck(nn.Module):
    method __init__ (line 17) | def __init__(self, inplanes, planes, stride=1, downsample=None, norm_l...
    method forward (line 37) | def forward(self, x):
  class ResNetBackbone (line 60) | class ResNetBackbone(nn.Module):
    method __init__ (line 63) | def __init__(self, layers, dcn_layers=[0, 0, 0, 0], dcn_interval=1, at...
    method _make_layer (line 94) | def _make_layer(self, block, planes, blocks, stride=1, dcn_layers=0, d...
    method forward (line 126) | def forward(self, x):
    method init_backbone (line 141) | def init_backbone(self, path):
    method add_layer (line 156) | def add_layer(self, conv_channels=1024, downsample=2, depth=1, block=B...
  class ResNetBackboneGN (line 163) | class ResNetBackboneGN(ResNetBackbone):
    method __init__ (line 165) | def __init__(self, layers, num_groups=32):
    method init_backbone (line 168) | def init_backbone(self, path):
  function darknetconvlayer (line 222) | def darknetconvlayer(in_channels, out_channels, *args, **kwdargs):
  class DarkNetBlock (line 235) | class DarkNetBlock(nn.Module):
    method __init__ (line 240) | def __init__(self, in_channels, channels):
    method forward (line 246) | def forward(self, x):
  class DarkNetBackbone (line 252) | class DarkNetBackbone(nn.Module):
    method __init__ (line 260) | def __init__(self, layers=[1, 2, 8, 8, 4], block=DarkNetBlock):
    method _make_layer (line 283) | def _make_layer(self, block, channels, num_blocks, stride=2):
    method forward (line 299) | def forward(self, x):
    method add_layer (line 311) | def add_layer(self, conv_channels=1024, stride=2, depth=1, block=DarkN...
    method init_backbone (line 315) | def init_backbone(self, path):
  class VGGBackbone (line 324) | class VGGBackbone(nn.Module):
    method __init__ (line 335) | def __init__(self, cfg, extra_args=[], norm_layers=[]):
    method _make_layer (line 359) | def _make_layer(self, cfg):
    method forward (line 400) | def forward(self, x):
    method transform_key (line 415) | def transform_key(self, k):
    method init_backbone (line 421) | def init_backbone(self, path):
    method add_layer (line 428) | def add_layer(self, conv_channels=128, downsample=2):
  function construct_backbone (line 449) | def construct_backbone(cfg):

FILE: data/coco.py
  function get_label_map (line 13) | def get_label_map():
  class COCOAnnotationTransform (line 19) | class COCOAnnotationTransform(object):
    method __init__ (line 23) | def __init__(self):
    method __call__ (line 26) | def __call__(self, target, width, height):
  class COCODetection (line 52) | class COCODetection(data.Dataset):
    method __init__ (line 64) | def __init__(self, image_path, info_file, transform=None,
    method __getitem__ (line 86) | def __getitem__(self, index):
    method __len__ (line 97) | def __len__(self):
    method pull_item (line 100) | def pull_item(self, index):
    method pull_image (line 178) | def pull_image(self, index):
    method pull_anno (line 193) | def pull_anno(self, index):
    method __repr__ (line 209) | def __repr__(self):
  function enforce_size (line 219) | def enforce_size(img, targets, masks, num_crowds, new_w, new_h):
  function detection_collate (line 260) | def detection_collate(batch):

FILE: data/config.py
  class Config (line 61) | class Config(object):
    method __init__ (line 70) | def __init__(self, config_dict):
    method copy (line 74) | def copy(self, new_config_dict={}):
    method replace (line 87) | def replace(self, new_config_dict):
    method print (line 98) | def print(self):
  function set_cfg (line 812) | def set_cfg(config_name:str):
  function set_dataset (line 823) | def set_dataset(dataset_name:str):

FILE: eval.py
  function str2bool (line 32) | def str2bool(v):
  function parse_args (line 40) | def parse_args(argv=None):
  function prep_display (line 145) | def prep_display(dets_out, img, h, w, undo_transform=True, class_color=F...
  function prep_benchmark (line 274) | def prep_benchmark(dets_out, h, w):
  function prep_coco_cats (line 293) | def prep_coco_cats():
  function get_coco_cat (line 301) | def get_coco_cat(transformed_cat_id):
  function get_transformed_cat (line 305) | def get_transformed_cat(coco_cat_id):
  class Detections (line 310) | class Detections:
    method __init__ (line 312) | def __init__(self):
    method add_bbox (line 316) | def add_bbox(self, image_id:int, category_id:int, bbox:list, score:flo...
    method add_mask (line 330) | def add_mask(self, image_id:int, category_id:int, segmentation:np.ndar...
    method dump (line 342) | def dump(self):
    method dump_web (line 352) | def dump_web(self):
  function _mask_iou (line 386) | def _mask_iou(mask1, mask2, iscrowd=False):
  function _bbox_iou (line 391) | def _bbox_iou(bbox1, bbox2, iscrowd=False):
  function prep_metrics (line 396) | def prep_metrics(ap_data, dets, img, gt, gt_masks, h, w, num_crowd, imag...
  class APDataObject (line 523) | class APDataObject:
    method __init__ (line 529) | def __init__(self):
    method push (line 533) | def push(self, score:float, is_true:bool):
    method add_gt_positives (line 536) | def add_gt_positives(self, num_positives:int):
    method is_empty (line 540) | def is_empty(self) -> bool:
    method get_ap (line 543) | def get_ap(self) -> float:
  function badhash (line 593) | def badhash(x):
  function evalimage (line 605) | def evalimage(net:Yolact, path:str, save_path:str=None):
  function evalimages (line 622) | def evalimages(net:Yolact, input_folder:str, output_folder:str):
  class CustomDataParallel (line 640) | class CustomDataParallel(torch.nn.DataParallel):
    method gather (line 642) | def gather(self, outputs, output_device):
  function evalvideo (line 646) | def evalvideo(net:Yolact, path:str, out_path:str=None):
  function evaluate (line 880) | def evaluate(net:Yolact, dataset, train_mode=False):
  function calc_map (line 1021) | def calc_map(ap_data):
  function print_maps (line 1049) | def print_maps(all_maps):

FILE: external/DCNv2/dcn_v2.py
  class _DCNv2 (line 16) | class _DCNv2(Function):
    method forward (line 18) | def forward(ctx, input, offset, mask, weight, bias,
    method backward (line 37) | def backward(ctx, grad_output):
  class DCNv2 (line 57) | class DCNv2(nn.Module):
    method __init__ (line 59) | def __init__(self, in_channels, out_channels,
    method reset_parameters (line 75) | def reset_parameters(self):
    method forward (line 83) | def forward(self, input, offset, mask):
  class DCN (line 97) | class DCN(DCNv2):
    method __init__ (line 99) | def __init__(self, in_channels, out_channels,
    method init_offset (line 114) | def init_offset(self):
    method forward (line 118) | def forward(self, input):
  class _DCNv2Pooling (line 132) | class _DCNv2Pooling(Function):
    method forward (line 134) | def forward(ctx, input, rois, offset,
    method backward (line 163) | def backward(ctx, grad_output):
  class DCNv2Pooling (line 187) | class DCNv2Pooling(nn.Module):
    method __init__ (line 189) | def __init__(self,
    method forward (line 208) | def forward(self, input, rois, offset):
  class DCNPooling (line 223) | class DCNPooling(DCNv2Pooling):
    method __init__ (line 225) | def __init__(self,
    method forward (line 259) | def forward(self, input, rois):

FILE: external/DCNv2/setup.py
  function get_extensions (line 17) | def get_extensions():

FILE: external/DCNv2/src/cpu/dcn_v2_cpu.cpp
  function dcn_v2_cpu_forward (line 7) | at::Tensor
  function dcn_v2_cpu_backward (line 26) | std::vector<at::Tensor>
  function dcn_v2_psroi_pooling_cpu_forward (line 42) | std::tuple<at::Tensor, at::Tensor>
  function dcn_v2_psroi_pooling_cpu_backward (line 58) | std::tuple<at::Tensor, at::Tensor>

FILE: external/DCNv2/src/vision.cpp
  function PYBIND11_MODULE (line 4) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) {

FILE: external/DCNv2/test.py
  function conv_identify (line 20) | def conv_identify(weight, bias):
  function check_zero_offset (line 32) | def check_zero_offset():
  function check_gradient_dconv (line 69) | def check_gradient_dconv():
  function check_pooling_zero_offset (line 100) | def check_pooling_zero_offset():
  function check_gradient_dpooling (line 134) | def check_gradient_dpooling():
  function example_dconv (line 169) | def example_dconv():
  function example_dpooling (line 183) | def example_dpooling():
  function example_mdpooling (line 226) | def example_mdpooling():

FILE: layers/box_utils.py
  function point_form (line 8) | def point_form(boxes):
  function center_size (line 21) | def center_size(boxes):
  function intersect (line 33) | def intersect(box_a, box_b):
  function jaccard (line 54) | def jaccard(box_a, box_b, iscrowd:bool=False):
  function diou (line 82) | def diou(box_a, box_b, iscrowd:bool=False):
  function distance (line 128) | def distance(box_a, box_b, iscrowd:bool=False):
  function elemwise_box_iou (line 170) | def elemwise_box_iou(box_a, box_b):
  function mask_iou (line 186) | def mask_iou(masks_a, masks_b, iscrowd=False):
  function elemwise_mask_iou (line 203) | def elemwise_mask_iou(masks_a, masks_b):
  function change (line 217) | def change(gt, priors):
  function match (line 247) | def match(pos_thresh, neg_thresh, truths, priors, labels, crowd_boxes, l...
  function encode (line 318) | def encode(matched, priors, use_yolo_regressors:bool=False):
  function decode (line 356) | def decode(loc, priors, use_yolo_regressors:bool=False):
  function log_sum_exp (line 404) | def log_sum_exp(x):
  function sanitize_coordinates (line 416) | def sanitize_coordinates(_x1, _x2, img_size:int, padding:int=0, cast:boo...
  function crop (line 438) | def crop(masks, boxes, padding:int=1):
  function index2d (line 464) | def index2d(src, idx):

FILE: layers/functions/detection.py
  class Detect (line 11) | class Detect(object):
    method __init__ (line 19) | def __init__(self, num_classes, bkg_label, top_k, conf_thresh, nms_thr...
    method __call__ (line 37) | def __call__(self, predictions, net):
    method detect (line 86) | def detect(self, batch_idx, conf_preds, decoded_boxes, mask_data, inst...
    method cc_fast_nms (line 133) | def cc_fast_nms(self, boxes, masks, scores, iou_threshold:float=0.5, t...
    method cc_cluster_nms (line 144) | def cc_cluster_nms(self, boxes, masks, scores, iou_threshold:float=0.5...
    method cc_cluster_diounms (line 162) | def cc_cluster_diounms(self, boxes, masks, scores, iou_threshold:float...
    method cc_cluster_SPM_nms (line 180) | def cc_cluster_SPM_nms(self, boxes, masks, scores, iou_threshold:float...
    method cc_cluster_SPM_dist_nms (line 203) | def cc_cluster_SPM_dist_nms(self, boxes, masks, scores, iou_threshold:...
    method cc_cluster_SPM_dist_weighted_nms (line 229) | def cc_cluster_SPM_dist_weighted_nms(self, boxes, masks, scores, iou_t...
    method fast_nms (line 267) | def fast_nms(self, boxes, masks, scores, iou_threshold:float=0.5, top_...
    method cluster_nms (line 310) | def cluster_nms(self, boxes, masks, scores, iou_threshold:float=0.5, t...
    method cluster_diounms (line 346) | def cluster_diounms(self, boxes, masks, scores, iou_threshold:float=0....
    method cluster_SPM_nms (line 381) | def cluster_SPM_nms(self, boxes, masks, scores, iou_threshold:float=0....
    method cluster_SPM_dist_nms (line 421) | def cluster_SPM_dist_nms(self, boxes, masks, scores, iou_threshold:flo...
    method cluster_SPM_dist_weighted_nms (line 462) | def cluster_SPM_dist_weighted_nms(self, boxes, masks, scores, iou_thre...
    method traditional_nms_yolact (line 519) | def traditional_nms_yolact(self, boxes, masks, scores, iou_threshold=0...
    method traditional_nms_ours (line 567) | def traditional_nms_ours(self, boxes, masks, scores, iou_threshold=0.5...

FILE: layers/interpolate.py
  class InterpolateModule (line 4) | class InterpolateModule(nn.Module):
    method __init__ (line 10) | def __init__(self, *args, **kwdargs):
    method forward (line 16) | def forward(self, x):

FILE: layers/modules/multibox_loss.py
  function ciou (line 11) | def ciou(bboxes1, bboxes2):
  function diou (line 62) | def diou(bboxes1, bboxes2):
  class MultiBoxLoss (line 109) | class MultiBoxLoss(nn.Module):
    method __init__ (line 132) | def __init__(self, num_classes, pos_threshold, neg_threshold, negpos_r...
    method forward (line 149) | def forward(self, net, predictions, targets, masks, num_crowds):
    method class_existence_loss (line 320) | def class_existence_loss(self, class_data, class_existence_t):
    method semantic_segmentation_loss (line 323) | def semantic_segmentation_loss(self, segment_data, mask_t, class_t, in...
    method ohem_conf_loss (line 347) | def ohem_conf_loss(self, conf_data, conf_t, pos, num):
    method focal_conf_loss (line 403) | def focal_conf_loss(self, conf_data, conf_t):
    method focal_conf_sigmoid_loss (line 433) | def focal_conf_sigmoid_loss(self, conf_data, conf_t):
    method focal_conf_objectness_loss (line 464) | def focal_conf_objectness_loss(self, conf_data, conf_t):
    method conf_objectness_loss (line 497) | def conf_objectness_loss(self, conf_data, conf_t, batch_size, loc_p, l...
    method direct_mask_loss (line 536) | def direct_mask_loss(self, pos_idx, idx_t, loc_data, mask_data, priors...
    method coeff_diversity_loss (line 580) | def coeff_diversity_loss(self, coeffs, instance_t):
    method lincomb_mask_loss (line 604) | def lincomb_mask_loss(self, pos, idx_t, loc_data, mask_data, priors, p...
    method _mask_iou (line 781) | def _mask_iou(self, mask1, mask2):
    method mask_iou_loss (line 789) | def mask_iou_loss(self, net, maskiou_targets):

FILE: layers/output_utils.py
  function postprocess (line 15) | def postprocess(det_output, w, h, batch_idx=0, interpolation_mode='bilin...
  function undo_image_transformation (line 128) | def undo_image_transformation(img, w, h):
  function display_lincomb (line 147) | def display_lincomb(proto_data, masks):

FILE: scripts/augment_bbox.py
  function augment_boxes (line 18) | def augment_boxes(bboxes):
  function prep_box (line 27) | def prep_box(box_list):
  function intersect (line 91) | def intersect(box_a, box_b):
  function jaccard_numpy (line 98) | def jaccard_numpy(box_a, box_b):
  function random_sample_crop (line 118) | def random_sample_crop(height, width, boxes=None):

FILE: scripts/bbox_recall.py
  function intersect (line 24) | def intersect(box_a, box_b):
  function jaccard (line 45) | def jaccard(box_a, box_b, iscrowd=False):
  function to_relative (line 70) | def to_relative(bboxes):
  function make_priors (line 74) | def make_priors(conv_size, scales, aspect_ratios):

FILE: scripts/cluster_bbox_sizes.py
  function to_relative (line 21) | def to_relative(bboxes):
  function process (line 24) | def process(bboxes):

FILE: scripts/compute_masks.py
  function mask_iou (line 10) | def mask_iou(mask1, mask2):
  function paint_mask (line 22) | def paint_mask(img_numpy, mask, color):
  function logit (line 41) | def logit(x):
  function sigmoid (line 44) | def sigmoid(x):

FILE: scripts/convert_sbd.py
  function mask2bbox (line 6) | def mask2bbox(mask):

FILE: scripts/make_grid.py
  function render (line 27) | def render():
  function update_scale (line 63) | def update_scale(val):
  function update_angle (line 69) | def update_angle(val):
  function update_centerx (line 75) | def update_centerx(val):
  function update_centery (line 81) | def update_centery(val):
  function update_spacing (line 87) | def update_spacing(val):
  function randomize (line 93) | def randomize(val):
  function add (line 113) | def add(val):
  function add_randomize (line 123) | def add_randomize(val):
  function export (line 127) | def export(val):
  function test_uniqueness (line 138) | def test_uniqueness(grids):

FILE: scripts/optimize_bboxes.py
  function intersect (line 24) | def intersect(box_a, box_b):
  function jaccard (line 45) | def jaccard(box_a, box_b, iscrowd=False):
  function to_relative (line 70) | def to_relative(bboxes):
  function make_priors (line 74) | def make_priors(conv_size, scales, aspect_ratios):
  function compute_hits (line 104) | def compute_hits(bboxes, anchors, iou_threshold=0.5):
  function compute_recall (line 110) | def compute_recall(hits, base_hits):
  function step (line 115) | def step(x, x_func, bboxes, base_hits, optim_idx):
  function optimize (line 124) | def optimize(full_bboxes, optim_idx, batch_size=5000):
  function pretty_str (line 157) | def pretty_str(x:list):
  function print_out (line 182) | def print_out():

FILE: scripts/parse_eval.py
  function grabMAP (line 20) | def grabMAP(string):

FILE: scripts/plot_loss.py
  function smoother (line 35) | def smoother(y, interval=100):
  function plot_train (line 44) | def plot_train(data):
  function plot_val (line 63) | def plot_val(data):

FILE: train.py
  function str2bool (line 27) | def str2bool(v):
  function replace (line 101) | def replace(name):
  class NetLoss (line 132) | class NetLoss(nn.Module):
    method __init__ (line 138) | def __init__(self, net:Yolact, criterion:MultiBoxLoss):
    method forward (line 144) | def forward(self, images, targets, masks, num_crowds):
  class CustomDataParallel (line 149) | class CustomDataParallel(nn.DataParallel):
    method scatter (line 155) | def scatter(self, inputs, kwargs, device_ids):
    method gather (line 164) | def gather(self, outputs, output_device):
  function train (line 172) | def train():
  function set_lr (line 388) | def set_lr(optimizer, new_lr):
  function gradinator (line 395) | def gradinator(x):
  function prepare_data (line 399) | def prepare_data(datum, devices:list=None, allocation:list=None):
  function no_inf_mean (line 439) | def no_inf_mean(x:torch.Tensor):
  function compute_validation_loss (line 452) | def compute_validation_loss(net, data_loader, criterion):
  function compute_validation_map (line 485) | def compute_validation_map(epoch, iteration, yolact_net, dataset, log:Lo...
  function setup_eval (line 500) | def setup_eval():

FILE: utils/augmentations.py
  function intersect (line 12) | def intersect(box_a, box_b):
  function jaccard_numpy (line 19) | def jaccard_numpy(box_a, box_b):
  class Compose (line 39) | class Compose(object):
    method __init__ (line 50) | def __init__(self, transforms):
    method __call__ (line 53) | def __call__(self, img, masks=None, boxes=None, labels=None):
  class Lambda (line 59) | class Lambda(object):
    method __init__ (line 62) | def __init__(self, lambd):
    method __call__ (line 66) | def __call__(self, img, masks=None, boxes=None, labels=None):
  class ConvertFromInts (line 70) | class ConvertFromInts(object):
    method __call__ (line 71) | def __call__(self, image, masks=None, boxes=None, labels=None):
  class ToAbsoluteCoords (line 76) | class ToAbsoluteCoords(object):
    method __call__ (line 77) | def __call__(self, image, masks=None, boxes=None, labels=None):
  class ToPercentCoords (line 87) | class ToPercentCoords(object):
    method __call__ (line 88) | def __call__(self, image, masks=None, boxes=None, labels=None):
  class Pad (line 98) | class Pad(object):
    method __init__ (line 105) | def __init__(self, width, height, mean=MEANS, pad_gt=True):
    method __call__ (line 111) | def __call__(self, image, masks, boxes=None, labels=None):
  class Resize (line 129) | class Resize(object):
    method calc_size_preserve_ar (line 133) | def calc_size_preserve_ar(img_w, img_h, max_size):
    method __init__ (line 140) | def __init__(self, resize_gt=True):
    method __call__ (line 145) | def __call__(self, image, masks, boxes, labels=None):
  class RandomSaturation (line 183) | class RandomSaturation(object):
    method __init__ (line 184) | def __init__(self, lower=0.5, upper=1.5):
    method __call__ (line 190) | def __call__(self, image, masks=None, boxes=None, labels=None):
  class RandomHue (line 197) | class RandomHue(object):
    method __init__ (line 198) | def __init__(self, delta=18.0):
    method __call__ (line 202) | def __call__(self, image, masks=None, boxes=None, labels=None):
  class RandomLightingNoise (line 210) | class RandomLightingNoise(object):
    method __init__ (line 211) | def __init__(self):
    method __call__ (line 216) | def __call__(self, image, masks=None, boxes=None, labels=None):
  class ConvertColor (line 226) | class ConvertColor(object):
    method __init__ (line 227) | def __init__(self, current='BGR', transform='HSV'):
    method __call__ (line 231) | def __call__(self, image, masks=None, boxes=None, labels=None):
  class RandomContrast (line 241) | class RandomContrast(object):
    method __init__ (line 242) | def __init__(self, lower=0.5, upper=1.5):
    method __call__ (line 249) | def __call__(self, image, masks=None, boxes=None, labels=None):
  class RandomBrightness (line 256) | class RandomBrightness(object):
    method __init__ (line 257) | def __init__(self, delta=32):
    method __call__ (line 262) | def __call__(self, image, masks=None, boxes=None, labels=None):
  class ToCV2Image (line 269) | class ToCV2Image(object):
    method __call__ (line 270) | def __call__(self, tensor, masks=None, boxes=None, labels=None):
  class ToTensor (line 274) | class ToTensor(object):
    method __call__ (line 275) | def __call__(self, cvimage, masks=None, boxes=None, labels=None):
  class RandomSampleCrop (line 279) | class RandomSampleCrop(object):
    method __init__ (line 292) | def __init__(self):
    method __call__ (line 305) | def __call__(self, image, masks, boxes=None, labels=None):
  class Expand (line 408) | class Expand(object):
    method __init__ (line 409) | def __init__(self, mean):
    method __call__ (line 412) | def __call__(self, image, masks, boxes, labels):
  class RandomMirror (line 443) | class RandomMirror(object):
    method __call__ (line 444) | def __call__(self, image, masks, boxes, labels):
  class RandomFlip (line 454) | class RandomFlip(object):
    method __call__ (line 455) | def __call__(self, image, masks, boxes, labels):
  class RandomRot90 (line 465) | class RandomRot90(object):
    method __call__ (line 466) | def __call__(self, image, masks, boxes, labels):
  class SwapChannels (line 478) | class SwapChannels(object):
    method __init__ (line 486) | def __init__(self, swaps):
    method __call__ (line 489) | def __call__(self, image):
  class PhotometricDistort (line 504) | class PhotometricDistort(object):
    method __init__ (line 505) | def __init__(self):
    method __call__ (line 517) | def __call__(self, image, masks, boxes, labels):
  class PrepareMasks (line 527) | class PrepareMasks(object):
    method __init__ (line 534) | def __init__(self, mask_size, use_gt_bboxes):
    method __call__ (line 538) | def __call__(self, image, masks, boxes, labels=None):
  class BackboneTransform (line 566) | class BackboneTransform(object):
    method __init__ (line 574) | def __init__(self, transform, mean, std, in_channel_order):
    method __call__ (line 583) | def __call__(self, img, masks=None, boxes=None, labels=None):
  class BaseTransform (line 601) | class BaseTransform(object):
    method __init__ (line 604) | def __init__(self, mean=MEANS, std=STD):
    method __call__ (line 611) | def __call__(self, img, masks=None, boxes=None, labels=None):
  class FastBaseTransform (line 616) | class FastBaseTransform(torch.nn.Module):
    method __init__ (line 623) | def __init__(self):
    method forward (line 630) | def forward(self, img):
  function do_nothing (line 660) | def do_nothing(img=None, masks=None, boxes=None, labels=None):
  function enable_if (line 664) | def enable_if(condition, obj):
  class SSDAugmentation (line 667) | class SSDAugmentation(object):
    method __init__ (line 670) | def __init__(self, mean=MEANS, std=STD):
    method __call__ (line 687) | def __call__(self, img, masks, boxes, labels):

FILE: utils/functions.py
  class MovingAverage (line 9) | class MovingAverage():
    method __init__ (line 12) | def __init__(self, max_window_size=1000):
    method add (line 16) | def add(self, elem):
    method append (line 28) | def append(self, elem):
    method reset (line 32) | def reset(self):
    method get_avg (line 37) | def get_avg(self):
    method __str__ (line 41) | def __str__(self):
    method __repr__ (line 44) | def __repr__(self):
    method __len__ (line 47) | def __len__(self):
  class ProgressBar (line 51) | class ProgressBar():
    method __init__ (line 54) | def __init__(self, length, max_val):
    method set_val (line 62) | def set_val(self, new_val):
    method is_finished (line 72) | def is_finished(self):
    method _update_str (line 75) | def _update_str(self):
    method __repr__ (line 82) | def __repr__(self):
    method __str__ (line 85) | def __str__(self):
  function init_console (line 89) | def init_console():
  class SavePath (line 98) | class SavePath:
    method __init__ (line 105) | def __init__(self, model_name:str, epoch:int, iteration:int):
    method get_path (line 110) | def get_path(self, root:str=''):
    method from_str (line 115) | def from_str(path:str):
    method remove_interrupt (line 133) | def remove_interrupt(save_folder):
    method get_interrupt (line 138) | def get_interrupt(save_folder):
    method get_latest (line 144) | def get_latest(save_folder, config):
  function make_net (line 163) | def make_net(in_channels, conf, include_last_relu=True):

FILE: utils/logger.py
  class Log (line 21) | class Log:
    method __init__ (line 34) | def __init__(self, log_name:str, log_dir:str='logs/', session_data:dic...
    method _log_session_header (line 72) | def _log_session_header(self, session_data:dict):
    method log (line 98) | def log(self, type:str, data:dict={}, **kwdargs):
  class LogEntry (line 130) | class LogEntry():
    method __init__ (line 133) | def __init__(self, entry:Union[dict, list]):
    method __getattr__ (line 136) | def __getattr__(self, name):
    method __getitem__ (line 147) | def __getitem__(self, name):
    method __len__ (line 150) | def __len__(self):
  class LogVisualizer (line 153) | class LogVisualizer():
    method __init__ (line 169) | def __init__(self):
    method _decode (line 174) | def _decode(self, query:str) -> list:
    method _follow (line 189) | def _follow(self, entry:LogEntry, query:list):
    method _color (line 205) | def _color(self, idx:int):
    method sessions (line 208) | def sessions(self, path:str):
    method add (line 241) | def add(self, path:str, session:Union[int,list]=None):
    method query (line 290) | def query(self, x:Union[str, list], entry_type:str=None, x_idx:int=Non...
    method check (line 321) | def check(self, entry_type:str, x:str):
    method plot (line 338) | def plot(self, entry_type:str, x:str, y:str, smoothness:int=0):
    method bar (line 375) | def bar(self, entry_type:str, x:str, labels:list=None, diff:bool=False...
    method elapsed_time (line 454) | def elapsed_time(self, cond1:str='', cond2:str='', legible:bool=True) ...

FILE: utils/nvinfo.py
  function gpu_info (line 7) | def gpu_info() -> list:
  function nvsmi_available (line 43) | def nvsmi_available() -> bool:
  function visible_gpus (line 48) | def visible_gpus() -> list:
  function _run_cmd (line 59) | def _run_cmd(cmd:list) -> list:

FILE: utils/timer.py
  function disable_all (line 11) | def disable_all():
  function enable_all (line 15) | def enable_all():
  function disable (line 19) | def disable(fn_name):
  function enable (line 23) | def enable(fn_name):
  function reset (line 27) | def reset():
  function start (line 35) | def start(fn_name, use_stack=True):
  function stop (line 55) | def stop(fn_name=None, use_stack=True):
  function print_stats (line 85) | def print_stats():
  function total_time (line 109) | def total_time():
  class env (line 114) | class env():
    method __init__ (line 122) | def __init__(self, fn_name, use_stack=True):
    method __enter__ (line 126) | def __enter__(self):
    method __exit__ (line 129) | def __exit__(self, e, ev, t):

FILE: web/scripts/iou.js
  function Box2 (line 69) | function Box2() {
  function addRect (line 152) | function addRect(x, y, w, h, fill) {
  function init2 (line 165) | function init2() {
  function clear (line 222) | function clear(c) {
  function mainDraw (line 229) | function mainDraw() {
  function computeIoU (line 248) | function computeIoU(a, b) {
  function myMove (line 269) | function myMove(e){
  function myDown (line 383) | function myDown(e){
  function myUp (line 425) | function myUp(){
  function myDblClick (line 432) | function myDblClick(e) {
  function invalidate (line 442) | function invalidate() {
  function getMouse (line 448) | function getMouse(e) {

FILE: web/scripts/jquery.js
  function m (line 2) | function m(e,t,n){var i,o=(t=t||r).createElement("script");if(o.text=e,n...
  function x (line 2) | function x(e){return null==e?e+"":"object"==typeof e||"function"==typeof...
  function C (line 2) | function C(e){var t=!!e&&"length"in e&&e.length,n=x(e);return!g(e)&&!y(e...
  function oe (line 2) | function oe(e,t,r,i){var o,s,l,c,f,h,v,m=t&&t.ownerDocument,T=t?t.nodeTy...
  function ae (line 2) | function ae(){var e=[];function t(n,i){return e.push(n+" ")>r.cacheLengt...
  function se (line 2) | function se(e){return e[b]=!0,e}
  function ue (line 2) | function ue(e){var t=d.createElement("fieldset");try{return!!e(t)}catch(...
  function le (line 2) | function le(e,t){var n=e.split("|"),i=n.length;while(i--)r.attrHandle[n[...
  function ce (line 2) | function ce(e,t){var n=t&&e,r=n&&1===e.nodeType&&1===t.nodeType&&e.sourc...
  function fe (line 2) | function fe(e){return function(t){return"input"===t.nodeName.toLowerCase...
  function pe (line 2) | function pe(e){return function(t){var n=t.nodeName.toLowerCase();return(...
  function de (line 2) | function de(e){return function(t){return"form"in t?t.parentNode&&!1===t....
  function he (line 2) | function he(e){return se(function(t){return t=+t,se(function(n,r){var i,...
  function ge (line 2) | function ge(e){return e&&"undefined"!=typeof e.getElementsByTagName&&e}
  function ye (line 2) | function ye(){}
  function ve (line 2) | function ve(e){for(var t=0,n=e.length,r="";t<n;t++)r+=e[t].value;return r}
  function me (line 2) | function me(e,t,n){var r=t.dir,i=t.next,o=i||r,a=n&&"parentNode"===o,s=C...
  function xe (line 2) | function xe(e){return e.length>1?function(t,n,r){var i=e.length;while(i-...
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  function N (line 2) | function N(e,t){return e.nodeName&&e.nodeName.toLowerCase()===t.toLowerC...
  function j (line 2) | function j(e,t,n){return g(t)?w.grep(e,function(e,r){return!!t.call(e,r,...
  function P (line 2) | function P(e,t){while((e=e[t])&&1!==e.nodeType);return e}
  function R (line 2) | function R(e){var t={};return w.each(e.match(M)||[],function(e,n){t[n]=!...
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  function W (line 2) | function W(e){throw e}
  function $ (line 2) | function $(e,t,n,r){var i;try{e&&g(i=e.promise)?i.call(e).done(t).fail(n...
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  function _ (line 2) | function _(){r.removeEventListener("DOMContentLoaded",_),e.removeEventLi...
  function V (line 2) | function V(e,t){return t.toUpperCase()}
  function G (line 2) | function G(e){return e.replace(X,"ms-").replace(U,V)}
  function Q (line 2) | function Q(){this.expando=w.expando+Q.uid++}
  function te (line 2) | function te(e){return"true"===e||"false"!==e&&("null"===e?null:e===+e+""...
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  function Se (line 2) | function Se(){try{return r.activeElement}catch(e){}}
  function De (line 2) | function De(e,t,n,r,i,o){var a,s;if("object"==typeof t){"string"!=typeof...
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FILE: web/scripts/js.cookie.js
  function extend (line 27) | function extend () {
  function init (line 39) | function init (converter) {

FILE: web/scripts/utils.js
  function load_RLE (line 1) | function load_RLE(rle_obj, fillColor=[255, 255, 255], alpha=255) {
  function uncompress_RLE (line 43) | function uncompress_RLE(rle_str) {
  function hexToRgb (line 68) | function hexToRgb(hex) {

FILE: web/scripts/viewer.js
  function save_settings (line 25) | function save_settings() {
  function load_settings (line 29) | function load_settings() {
  function is_object (line 77) | function is_object(val) { return val === Object(val); }
  function fill_info (line 79) | function fill_info(info) {
  function fill_controls (line 105) | function fill_controls() {
  function render (line 169) | function render() {

FILE: web/server.py
  class Handler (line 9) | class Handler(SimpleHTTPRequestHandler):
    method do_GET (line 11) | def do_GET(self):
    method send_str (line 21) | def send_str(self, string):
    method send_file (line 30) | def send_file(self, path):
    method send_response (line 49) | def send_response(self, code, message=None):

FILE: yolact.py
  class Concat (line 34) | class Concat(nn.Module):
    method __init__ (line 35) | def __init__(self, nets, extra_params):
    method forward (line 41) | def forward(self, x):
  class PredictionModule (line 47) | class PredictionModule(nn.Module):
    method __init__ (line 73) | def __init__(self, in_channels, out_channels=1024, aspect_ratios=[[1]]...
    method forward (line 133) | def forward(self, x):
    method make_priors (line 214) | def make_priors(self, conv_h, conv_w, device):
  class FPN (line 265) | class FPN(ScriptModuleWrapper):
    method __init__ (line 283) | def __init__(self, in_channels):
    method forward (line 311) | def forward(self, convouts:List[torch.Tensor]):
  class FastMaskIoUNet (line 363) | class FastMaskIoUNet(ScriptModuleWrapper):
    method __init__ (line 365) | def __init__(self):
    method forward (line 371) | def forward(self, x):
  class Yolact (line 379) | class Yolact(nn.Module):
    method __init__ (line 399) | def __init__(self):
    method save_weights (line 473) | def save_weights(self, path):
    method load_weights (line 477) | def load_weights(self, path):
    method init_weights (line 492) | def init_weights(self, backbone_path):
    method train (line 549) | def train(self, mode=True):
    method freeze_bn (line 555) | def freeze_bn(self, enable=False):
    method forward (line 564) | def forward(self, x):