SYMBOL INDEX (251 symbols across 25 files)

FILE: backbone/__init__.py
  function build_backbone (line 7) | def build_backbone(model_name='resnet18', pretrained=False):

FILE: backbone/darknet19.py
  class Conv_BN_LeakyReLU (line 14) | class Conv_BN_LeakyReLU(nn.Module):
    method __init__ (line 15) | def __init__(self, in_channels, out_channels, ksize, padding=0, stride...
    method forward (line 23) | def forward(self, x):
  class DarkNet_19 (line 27) | class DarkNet_19(nn.Module):
    method __init__ (line 28) | def __init__(self):
    method forward (line 78) | def forward(self, x):
  function build_darknet19 (line 95) | def build_darknet19(pretrained=False):

FILE: backbone/darknet53.py
  class Conv_BN_LeakyReLU (line 13) | class Conv_BN_LeakyReLU(nn.Module):
    method __init__ (line 14) | def __init__(self, in_channels, out_channels, ksize, padding=0, stride...
    method forward (line 22) | def forward(self, x):
  class ResBlock (line 26) | class ResBlock(nn.Module):
    method __init__ (line 27) | def __init__(self, ch, nblocks=1):
    method forward (line 37) | def forward(self, x):
  class DarkNet_53 (line 43) | class DarkNet_53(nn.Module):
    method __init__ (line 47) | def __init__(self):
    method forward (line 77) | def forward(self, x, targets=None):
  function build_darknet53 (line 93) | def build_darknet53(pretrained=False):

FILE: backbone/darknet_tiny.py
  class Conv_BN_LeakyReLU (line 13) | class Conv_BN_LeakyReLU(nn.Module):
    method __init__ (line 14) | def __init__(self, in_channels, out_channels, ksize, padding=0, stride...
    method forward (line 22) | def forward(self, x):
  class DarkNet_Tiny (line 26) | class DarkNet_Tiny(nn.Module):
    method __init__ (line 27) | def __init__(self):
    method forward (line 55) | def forward(self, x):
  function build_darknet_tiny (line 79) | def build_darknet_tiny(pretrained=False):

FILE: backbone/resnet.py
  function conv3x3 (line 19) | def conv3x3(in_planes, out_planes, stride=1):
  function conv1x1 (line 24) | def conv1x1(in_planes, out_planes, stride=1):
  class BasicBlock (line 28) | class BasicBlock(nn.Module):
    method __init__ (line 31) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 41) | def forward(self, x):
  class Bottleneck (line 59) | class Bottleneck(nn.Module):
    method __init__ (line 62) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 74) | def forward(self, x):
  class ResNet (line 96) | class ResNet(nn.Module):
    method __init__ (line 98) | def __init__(self, block, layers, zero_init_residual=False):
    method _make_layer (line 128) | def _make_layer(self, block, planes, blocks, stride=1):
    method forward (line 144) | def forward(self, x):
  function resnet18 (line 164) | def resnet18(pretrained=False, **kwargs):
  function resnet34 (line 176) | def resnet34(pretrained=False, **kwargs):
  function resnet50 (line 187) | def resnet50(pretrained=False, **kwargs):
  function resnet101 (line 198) | def resnet101(pretrained=False, **kwargs):
  function resnet152 (line 209) | def resnet152(pretrained=False, **kwargs):
  function build_resnet (line 221) | def build_resnet(model_name='resnet18', pretrained=False):

FILE: data/__init__.py
  function detection_collate (line 9) | def detection_collate(batch):
  function base_transform (line 30) | def base_transform(image, size, mean, std):
  class BaseTransform (line 38) | class BaseTransform:
    method __init__ (line 39) | def __init__(self, size, mean=(0.406, 0.456, 0.485), std=(0.225, 0.224...
    method __call__ (line 44) | def __call__(self, image, boxes=None, labels=None):

FILE: data/coco2017.py
  class COCODataset (line 32) | class COCODataset(Dataset):
    method __init__ (line 36) | def __init__(self,
    method __len__ (line 60) | def __len__(self):
    method pull_image (line 64) | def pull_image(self, index):
    method pull_anno (line 78) | def pull_anno(self, index):
    method __getitem__ (line 102) | def __getitem__(self, index):
    method pull_item (line 108) | def pull_item(self, index):
  function base_transform (line 166) | def base_transform(image, size, mean):
  class BaseTransform (line 172) | class BaseTransform:
    method __init__ (line 173) | def __init__(self, size, mean):
    method __call__ (line 177) | def __call__(self, image, boxes=None, labels=None):

FILE: data/voc0712.py
  class VOCAnnotationTransform (line 26) | class VOCAnnotationTransform(object):
    method __init__ (line 39) | def __init__(self, class_to_ind=None, keep_difficult=False):
    method __call__ (line 44) | def __call__(self, target, width, height):
  class VOCDetection (line 75) | class VOCDetection(data.Dataset):
    method __init__ (line 92) | def __init__(self,
    method __getitem__ (line 112) | def __getitem__(self, index):
    method __len__ (line 118) | def __len__(self):
    method pull_item (line 122) | def pull_item(self, index):
    method pull_image (line 151) | def pull_image(self, index):
    method pull_anno (line 166) | def pull_anno(self, index):
    method pull_tensor (line 184) | def pull_tensor(self, index):
  function base_transform (line 199) | def base_transform(image, size, mean):
  class BaseTransform (line 205) | class BaseTransform:
    method __init__ (line 206) | def __init__(self, size, mean):
    method __call__ (line 210) | def __call__(self, image, boxes=None, labels=None):

FILE: demo.py
  function parse_args (line 12) | def parse_args():
  function plot_bbox_labels (line 42) | def plot_bbox_labels(img, bbox, label, cls_color, test_scale=0.4):
  function visualize (line 56) | def visualize(img, bboxes, scores, cls_inds, class_colors, vis_thresh=0.3):
  function detect (line 68) | def detect(net,
  function run (line 196) | def run():

FILE: eval.py
  function voc_test (line 30) | def voc_test(model, data_dir, device, input_size):
  function coco_test (line 41) | def coco_test(model, data_dir, device, input_size, test=False):

FILE: models/yolov2_d19.py
  class YOLOv2D19 (line 10) | class YOLOv2D19(nn.Module):
    method __init__ (line 11) | def __init__(self, device, input_size=None, num_classes=20, trainable=...
    method create_grid (line 42) | def create_grid(self, input_size):
    method set_grid (line 56) | def set_grid(self, input_size):
    method decode_xywh (line 61) | def decode_xywh(self, txtytwth_pred):
    method decode_boxes (line 81) | def decode_boxes(self, txtytwth_pred):
    method nms (line 100) | def nms(self, dets, scores):
    method postprocess (line 132) | def postprocess(self, bboxes, scores):
    method inference (line 167) | def inference(self, x):
    method forward (line 218) | def forward(self, x, target=None):

FILE: models/yolov2_r50.py
  class YOLOv2R50 (line 10) | class YOLOv2R50(nn.Module):
    method __init__ (line 11) | def __init__(self, device, input_size=None, num_classes=20, trainable=...
    method init_bias (line 50) | def init_bias(self):
    method create_grid (line 57) | def create_grid(self, input_size):
    method set_grid (line 72) | def set_grid(self, input_size):
    method decode_xywh (line 77) | def decode_xywh(self, txtytwth_pred):
    method decode_boxes (line 97) | def decode_boxes(self, txtytwth_pred):
    method nms (line 116) | def nms(self, dets, scores):
    method postprocess (line 148) | def postprocess(self, bboxes, scores):
    method inference (line 183) | def inference(self, x):
    method forward (line 234) | def forward(self, x, target=None):

FILE: models/yolov3.py
  class YOLOv3 (line 10) | class YOLOv3(nn.Module):
    method __init__ (line 11) | def __init__(self,
    method init_yolo (line 74) | def init_yolo(self):
    method create_grid (line 84) | def create_grid(self, input_size):
    method set_grid (line 113) | def set_grid(self, input_size):
    method decode_xywh (line 118) | def decode_xywh(self, txtytwth_pred):
    method decode_boxes (line 136) | def decode_boxes(self, txtytwth_pred):
    method nms (line 155) | def nms(self, dets, scores):
    method postprocess (line 187) | def postprocess(self, bboxes, scores):
    method inference (line 228) | def inference(self, x):
    method forward (line 307) | def forward(self, x, target=None):

FILE: models/yolov3_spp.py
  class YOLOv3Spp (line 12) | class YOLOv3Spp(nn.Module):
    method __init__ (line 13) | def __init__(self,
    method init_yolo (line 77) | def init_yolo(self):
    method create_grid (line 87) | def create_grid(self, input_size):
    method set_grid (line 116) | def set_grid(self, input_size):
    method decode_xywh (line 121) | def decode_xywh(self, txtytwth_pred):
    method decode_boxes (line 139) | def decode_boxes(self, txtytwth_pred):
    method nms (line 158) | def nms(self, dets, scores):
    method postprocess (line 190) | def postprocess(self, bboxes, scores):
    method inference (line 225) | def inference(self, x):
    method forward (line 304) | def forward(self, x, target=None):

FILE: models/yolov3_tiny.py
  class YOLOv3tiny (line 12) | class YOLOv3tiny(nn.Module):
    method __init__ (line 13) | def __init__(self, device, input_size=None, num_classes=20, trainable=...
    method init_yolo (line 46) | def init_yolo(self):
    method create_grid (line 56) | def create_grid(self, input_size):
    method set_grid (line 85) | def set_grid(self, input_size):
    method decode_xywh (line 90) | def decode_xywh(self, txtytwth_pred):
    method decode_boxes (line 108) | def decode_boxes(self, txtytwth_pred):
    method nms (line 127) | def nms(self, dets, scores):
    method postprocess (line 159) | def postprocess(self, bboxes, scores):
    method inference (line 194) | def inference(self, x):
    method forward (line 266) | def forward(self, x, target=None):

FILE: test.py
  function plot_bbox_labels (line 43) | def plot_bbox_labels(img, bbox, label=None, cls_color=None, text_scale=0...
  function visualize (line 59) | def visualize(img,
  function test (line 88) | def test(net,

FILE: tools.py
  class MSEWithLogitsLoss (line 10) | class MSEWithLogitsLoss(nn.Module):
    method __init__ (line 11) | def __init__(self, reduction='mean'):
    method forward (line 15) | def forward(self, logits, targets, mask):
  function compute_iou (line 35) | def compute_iou(anchor_boxes, gt_box):
  function set_anchors (line 76) | def set_anchors(anchor_size):
  function generate_txtytwth (line 95) | def generate_txtytwth(gt_label, w, h, s, all_anchor_size):
  function gt_creator (line 165) | def gt_creator(input_size, stride, label_lists, anchor_size):
  function multi_gt_creator (line 218) | def multi_gt_creator(input_size, strides, label_lists, anchor_size):
  function iou_score (line 340) | def iou_score(bboxes_a, bboxes_b):
  function loss (line 355) | def loss(pred_conf, pred_cls, pred_txtytwth, pred_iou, label):

FILE: train.py
  function parse_args (line 32) | def parse_args():
  function train (line 97) | def train():
  function set_lr (line 457) | def set_lr(optimizer, lr):
  function vis_data (line 462) | def vis_data(images, targets, input_size):

FILE: utils/augmentations.py
  function intersect (line 6) | def intersect(box_a, box_b):
  function jaccard_numpy (line 13) | def jaccard_numpy(box_a, box_b):
  class Compose (line 33) | class Compose(object):
    method __init__ (line 44) | def __init__(self, transforms):
    method __call__ (line 47) | def __call__(self, img, boxes=None, labels=None):
  class ConvertFromInts (line 53) | class ConvertFromInts(object):
    method __call__ (line 54) | def __call__(self, image, boxes=None, labels=None):
  class Normalize (line 58) | class Normalize(object):
    method __init__ (line 59) | def __init__(self, mean=None, std=None):
    method __call__ (line 63) | def __call__(self, image, boxes=None, labels=None):
  class ToAbsoluteCoords (line 72) | class ToAbsoluteCoords(object):
    method __call__ (line 73) | def __call__(self, image, boxes=None, labels=None):
  class ToPercentCoords (line 83) | class ToPercentCoords(object):
    method __call__ (line 84) | def __call__(self, image, boxes=None, labels=None):
  class Resize (line 94) | class Resize(object):
    method __init__ (line 95) | def __init__(self, size=416):
    method __call__ (line 98) | def __call__(self, image, boxes=None, labels=None):
  class RandomSaturation (line 103) | class RandomSaturation(object):
    method __init__ (line 104) | def __init__(self, lower=0.5, upper=1.5):
    method __call__ (line 110) | def __call__(self, image, boxes=None, labels=None):
  class RandomHue (line 117) | class RandomHue(object):
    method __init__ (line 118) | def __init__(self, delta=18.0):
    method __call__ (line 122) | def __call__(self, image, boxes=None, labels=None):
  class RandomLightingNoise (line 130) | class RandomLightingNoise(object):
    method __init__ (line 131) | def __init__(self):
    method __call__ (line 136) | def __call__(self, image, boxes=None, labels=None):
  class ConvertColor (line 144) | class ConvertColor(object):
    method __init__ (line 145) | def __init__(self, current='BGR', transform='HSV'):
    method __call__ (line 149) | def __call__(self, image, boxes=None, labels=None):
  class RandomContrast (line 159) | class RandomContrast(object):
    method __init__ (line 160) | def __init__(self, lower=0.5, upper=1.5):
    method __call__ (line 167) | def __call__(self, image, boxes=None, labels=None):
  class RandomBrightness (line 174) | class RandomBrightness(object):
    method __init__ (line 175) | def __init__(self, delta=32):
    method __call__ (line 180) | def __call__(self, image, boxes=None, labels=None):
  class RandomSampleCrop (line 187) | class RandomSampleCrop(object):
    method __init__ (line 200) | def __init__(self):
    method __call__ (line 213) | def __call__(self, image, boxes=None, labels=None):
  class RandomMirror (line 292) | class RandomMirror(object):
    method __call__ (line 293) | def __call__(self, image, boxes, classes):
  class SwapChannels (line 302) | class SwapChannels(object):
    method __init__ (line 310) | def __init__(self, swaps):
    method __call__ (line 313) | def __call__(self, image):
  class PhotometricDistort (line 328) | class PhotometricDistort(object):
    method __init__ (line 329) | def __init__(self):
    method __call__ (line 341) | def __call__(self, image, boxes, labels):
  class SSDAugmentation (line 353) | class SSDAugmentation(object):
    method __init__ (line 354) | def __init__(self, size=416, mean=(0.406, 0.456, 0.485), std=(0.225, 0...
    method __call__ (line 369) | def __call__(self, img, boxes, labels):
  class ColorAugmentation (line 373) | class ColorAugmentation(object):
    method __init__ (line 374) | def __init__(self, size=416, mean=(0.406, 0.456, 0.485), std=(0.225, 0...
    method __call__ (line 388) | def __call__(self, img, boxes, labels):

FILE: utils/cocoapi_evaluator.py
  class COCOAPIEvaluator (line 11) | class COCOAPIEvaluator():
    method __init__ (line 17) | def __init__(self, data_dir, img_size, device, testset=False, transfor...
    method evaluate (line 48) | def evaluate(self, model):

FILE: utils/com_paras_flops.py
  function FLOPs_and_Params (line 5) | def FLOPs_and_Params(model, size, device):

FILE: utils/distributed_utils.py
  function all_gather (line 10) | def all_gather(data):
  function reduce_dict (line 53) | def reduce_dict(input_dict, average=True):
  function get_sha (line 80) | def get_sha():
  function setup_for_distributed (line 100) | def setup_for_distributed(is_master):
  function is_dist_avail_and_initialized (line 115) | def is_dist_avail_and_initialized():
  function get_world_size (line 123) | def get_world_size():
  function get_rank (line 129) | def get_rank():
  function is_main_process (line 135) | def is_main_process():
  function save_on_master (line 139) | def save_on_master(*args, **kwargs):
  function init_distributed_mode (line 144) | def init_distributed_mode(args):

FILE: utils/kmeans_anchor.py
  function parse_args (line 12) | def parse_args():
  class Box (line 30) | class Box():
    method __init__ (line 31) | def __init__(self, x, y, w, h):
  function iou (line 38) | def iou(box1, box2):
  function init_centroids (line 61) | def init_centroids(boxes, n_anchors):
  function do_kmeans (line 98) | def do_kmeans(n_anchors, boxes, centroids):
  function anchor_box_kmeans (line 129) | def anchor_box_kmeans(total_gt_boxes, n_anchors, loss_convergence, iters...

FILE: utils/modules.py
  class Conv (line 7) | class Conv(nn.Module):
    method __init__ (line 8) | def __init__(self, in_ch, out_ch, k=1, p=0, s=1, d=1, g=1, act=True):
    method forward (line 22) | def forward(self, x):
  class UpSample (line 26) | class UpSample(nn.Module):
    method __init__ (line 27) | def __init__(self, size=None, scale_factor=None, mode='nearest', align...
    method forward (line 34) | def forward(self, x):
  class reorg_layer (line 39) | class reorg_layer(nn.Module):
    method __init__ (line 40) | def __init__(self, stride):
    method forward (line 44) | def forward(self, x):
  class SPP (line 56) | class SPP(nn.Module):
    method __init__ (line 60) | def __init__(self):
    method forward (line 63) | def forward(self, x):
  class ModelEMA (line 72) | class ModelEMA(object):
    method __init__ (line 73) | def __init__(self, model, decay=0.9999, updates=0):
    method update (line 81) | def update(self, model):

FILE: utils/vocapi_evaluator.py
  class VOCAPIEvaluator (line 17) | class VOCAPIEvaluator():
    method __init__ (line 19) | def __init__(self, data_root, img_size, device, transform, set_type='t...
    method evaluate (line 42) | def evaluate(self, net):
    method parse_rec (line 89) | def parse_rec(self, filename):
    method get_output_dir (line 109) | def get_output_dir(self, name, phase):
    method get_voc_results_file_template (line 121) | def get_voc_results_file_template(self, cls):
    method write_voc_results_file (line 131) | def write_voc_results_file(self, all_boxes):
    method do_python_eval (line 149) | def do_python_eval(self, use_07=True):
    method voc_ap (line 188) | def voc_ap(self, rec, prec, use_07_metric=True):
    method voc_eval (line 222) | def voc_eval(self, detpath, classname, cachedir, ovthresh=0.5, use_07_...
    method evaluate_detections (line 330) | def evaluate_detections(self, box_list):