SYMBOL INDEX (213 symbols across 13 files)

FILE: detect.py
  function detect (line 21) | def detect(save_img=False):

FILE: hubconf.py
  function create (line 17) | def create(name, pretrained, channels, classes):
  function yolov5s (line 46) | def yolov5s(pretrained=False, channels=3, classes=80):
  function yolov5m (line 60) | def yolov5m(pretrained=False, channels=3, classes=80):
  function yolov5l (line 74) | def yolov5l(pretrained=False, channels=3, classes=80):
  function yolov5x (line 88) | def yolov5x(pretrained=False, channels=3, classes=80):

FILE: models/common.py
  function autopad (line 8) | def autopad(k, p=None):  # kernel, padding
  function DWConv (line 15) | def DWConv(c1, c2, k=1, s=1, act=True):
  class Conv (line 20) | class Conv(nn.Module):
    method __init__ (line 22) | def __init__(self, c1, c2, k=1, s=1, p=None, g=1, act=True):  # ch_in,...
    method forward (line 28) | def forward(self, x):
    method fuseforward (line 31) | def fuseforward(self, x):
  class Bottleneck (line 35) | class Bottleneck(nn.Module):
    method __init__ (line 37) | def __init__(self, c1, c2, shortcut=True, g=1, e=0.5):  # ch_in, ch_ou...
    method forward (line 44) | def forward(self, x):
  class BottleneckCSP (line 48) | class BottleneckCSP(nn.Module):
    method __init__ (line 50) | def __init__(self, c1, c2, n=1, shortcut=True, g=1, e=0.5):  # ch_in, ...
    method forward (line 61) | def forward(self, x):
  class SPP (line 67) | class SPP(nn.Module):
    method __init__ (line 69) | def __init__(self, c1, c2, k=(5, 9, 13)):
    method forward (line 76) | def forward(self, x):
  class Focus (line 81) | class Focus(nn.Module):
    method __init__ (line 83) | def __init__(self, c1, c2, k=1, s=1, p=None, g=1, act=True):  # ch_in,...
    method forward (line 87) | def forward(self, x):  # x(b,c,w,h) -> y(b,4c,w/2,h/2)
  class Concat (line 91) | class Concat(nn.Module):
    method __init__ (line 93) | def __init__(self, dimension=1):
    method forward (line 97) | def forward(self, x):
  class Flatten (line 101) | class Flatten(nn.Module):
    method forward (line 104) | def forward(x):
  class Classify (line 108) | class Classify(nn.Module):
    method __init__ (line 110) | def __init__(self, c1, c2, k=1, s=1, p=None, g=1):  # ch_in, ch_out, k...
    method forward (line 116) | def forward(self, x):

FILE: models/experimental.py
  class CrossConv (line 11) | class CrossConv(nn.Module):
    method __init__ (line 13) | def __init__(self, c1, c2, k=3, s=1, g=1, e=1.0, shortcut=False):
    method forward (line 21) | def forward(self, x):
  class C3 (line 25) | class C3(nn.Module):
    method __init__ (line 27) | def __init__(self, c1, c2, n=1, shortcut=True, g=1, e=0.5):  # ch_in, ...
    method forward (line 38) | def forward(self, x):
  class Sum (line 44) | class Sum(nn.Module):
    method __init__ (line 46) | def __init__(self, n, weight=False):  # n: number of inputs
    method forward (line 53) | def forward(self, x):
  class GhostConv (line 65) | class GhostConv(nn.Module):
    method __init__ (line 67) | def __init__(self, c1, c2, k=1, s=1, g=1, act=True):  # ch_in, ch_out,...
    method forward (line 73) | def forward(self, x):
  class GhostBottleneck (line 78) | class GhostBottleneck(nn.Module):
    method __init__ (line 80) | def __init__(self, c1, c2, k, s):
    method forward (line 89) | def forward(self, x):
  class MixConv2d (line 93) | class MixConv2d(nn.Module):
    method __init__ (line 95) | def __init__(self, c1, c2, k=(1, 3), s=1, equal_ch=True):
    method forward (line 113) | def forward(self, x):
  class Ensemble (line 117) | class Ensemble(nn.ModuleList):
    method __init__ (line 119) | def __init__(self):
    method forward (line 122) | def forward(self, x, augment=False):
  function attempt_load (line 132) | def attempt_load(weights, map_location=None):

FILE: models/yolo.py
  class Detect (line 19) | class Detect(nn.Module):
    method __init__ (line 23) | def __init__(self, nc=80, anchors=(), ch=()):  # detection layer
    method forward (line 35) | def forward(self, x):
    method _make_grid (line 56) | def _make_grid(nx=20, ny=20):
  class Model (line 61) | class Model(nn.Module):
    method __init__ (line 62) | def __init__(self, cfg='yolov5s.yaml', ch=3, nc=None):  # model, input...
    method forward (line 95) | def forward(self, x, augment=False, profile=False):
    method forward_once (line 115) | def forward_once(self, x, profile=False):
    method _initialize_biases (line 140) | def _initialize_biases(self, cf=None):  # initialize biases into Detec...
    method _print_biases (line 149) | def _print_biases(self):
    method fuse (line 160) | def fuse(self):  # fuse model Conv2d() + BatchNorm2d() layers
    method info (line 171) | def info(self, verbose=False):  # print model information
  function parse_model (line 175) | def parse_model(d, ch):  # model_dict, input_channels(3)

FILE: sotabench.py
  function test (line 27) | def test(data,

FILE: test.py
  function test (line 21) | def test(data,

FILE: train.py
  function train (line 36) | def train(hyp, opt, device, tb_writer=None):

FILE: utils/activations.py
  class Swish (line 7) | class Swish(nn.Module):  #
    method forward (line 9) | def forward(x):
  class Hardswish (line 13) | class Hardswish(nn.Module):  # export-friendly version of nn.Hardswish()
    method forward (line 15) | def forward(x):
  class MemoryEfficientSwish (line 20) | class MemoryEfficientSwish(nn.Module):
    class F (line 21) | class F(torch.autograd.Function):
      method forward (line 23) | def forward(ctx, x):
      method backward (line 28) | def backward(ctx, grad_output):
    method forward (line 33) | def forward(self, x):
  class Mish (line 38) | class Mish(nn.Module):
    method forward (line 40) | def forward(x):
  class MemoryEfficientMish (line 44) | class MemoryEfficientMish(nn.Module):
    class F (line 45) | class F(torch.autograd.Function):
      method forward (line 47) | def forward(ctx, x):
      method backward (line 52) | def backward(ctx, grad_output):
    method forward (line 58) | def forward(self, x):
  class FReLU (line 63) | class FReLU(nn.Module):
    method __init__ (line 64) | def __init__(self, c1, k=3):  # ch_in, kernel
    method forward (line 69) | def forward(self, x):

FILE: utils/datasets.py
  function get_hash (line 29) | def get_hash(files):
  function exif_size (line 34) | def exif_size(img):
  function create_dataloader (line 49) | def create_dataloader(path, imgsz, batch_size, stride, opt, hyp=None, au...
  class InfiniteDataLoader (line 75) | class InfiniteDataLoader(torch.utils.data.dataloader.DataLoader):
    method __init__ (line 81) | def __init__(self, *args, **kwargs):
    method __len__ (line 86) | def __len__(self):
    method __iter__ (line 89) | def __iter__(self):
    class _RepeatSampler (line 93) | class _RepeatSampler(object):
      method __init__ (line 100) | def __init__(self, sampler):
      method __iter__ (line 103) | def __iter__(self):
  class LoadImages (line 108) | class LoadImages:  # for inference
    method __init__ (line 109) | def __init__(self, path, img_size=640):
    method __iter__ (line 137) | def __iter__(self):
    method __next__ (line 141) | def __next__(self):
    method new_video (line 180) | def new_video(self, path):
    method __len__ (line 185) | def __len__(self):
  class LoadWebcam (line 189) | class LoadWebcam:  # for inference
    method __init__ (line 190) | def __init__(self, pipe=0, img_size=640):
    method __iter__ (line 211) | def __iter__(self):
    method __next__ (line 215) | def __next__(self):
    method __len__ (line 250) | def __len__(self):
  class LoadStreams (line 254) | class LoadStreams:  # multiple IP or RTSP cameras
    method __init__ (line 255) | def __init__(self, sources='streams.txt', img_size=640):
    method update (line 288) | def update(self, index, cap):
    method __iter__ (line 300) | def __iter__(self):
    method __next__ (line 304) | def __next__(self):
    method __len__ (line 323) | def __len__(self):
  class LoadImagesAndLabels (line 327) | class LoadImagesAndLabels(Dataset):  # for training/testing
    method __init__ (line 328) | def __init__(self, path, img_size=640, batch_size=16, augment=False, h...
    method cache_labels (line 478) | def cache_labels(self, path='labels.cache'):
    method __len__ (line 504) | def __len__(self):
    method __getitem__ (line 513) | def __getitem__(self, index):
    method collate_fn (line 597) | def collate_fn(batch):
  function load_image (line 605) | def load_image(self, index):
  function augment_hsv (line 622) | def augment_hsv(img, hgain=0.5, sgain=0.5, vgain=0.5):
  function load_mosaic (line 641) | def load_mosaic(self, index):
  function replicate (line 699) | def replicate(img, labels):
  function letterbox (line 716) | def letterbox(img, new_shape=(640, 640), color=(114, 114, 114), auto=Tru...
  function random_perspective (line 749) | def random_perspective(img, targets=(), degrees=10, translate=.1, scale=...
  function box_candidates (line 836) | def box_candidates(box1, box2, wh_thr=2, ar_thr=20, area_thr=0.1):  # bo...
  function cutout (line 844) | def cutout(image, labels):
  function reduce_img_size (line 890) | def reduce_img_size(path='path/images', img_size=1024):  # from utils.da...
  function recursive_dataset2bmp (line 907) | def recursive_dataset2bmp(dataset='path/dataset_bmp'):  # from utils.dat...
  function imagelist2folder (line 927) | def imagelist2folder(path='path/images.txt'):  # from utils.datasets imp...
  function create_folder (line 936) | def create_folder(path='./new'):

FILE: utils/general.py
  function torch_distributed_zero_first (line 39) | def torch_distributed_zero_first(local_rank: int):
  function set_logging (line 50) | def set_logging(rank=-1):
  function init_seeds (line 56) | def init_seeds(seed=0):
  function get_latest_run (line 62) | def get_latest_run(search_dir='./runs'):
  function check_git_status (line 68) | def check_git_status():
  function check_img_size (line 76) | def check_img_size(img_size, s=32):
  function check_anchors (line 84) | def check_anchors(dataset, model, thr=4.0, imgsz=640):
  function check_anchor_order (line 118) | def check_anchor_order(m):
  function check_file (line 129) | def check_file(file):
  function check_dataset (line 139) | def check_dataset(dict):
  function make_divisible (line 159) | def make_divisible(x, divisor):
  function labels_to_class_weights (line 164) | def labels_to_class_weights(labels, nc=80):
  function labels_to_image_weights (line 183) | def labels_to_image_weights(labels, nc=80, class_weights=np.ones(80)):
  function coco80_to_coco91_class (line 192) | def coco80_to_coco91_class():  # converts 80-index (val2014) to 91-index...
  function xyxy2xywh (line 204) | def xyxy2xywh(x):
  function xywh2xyxy (line 214) | def xywh2xyxy(x):
  function scale_coords (line 224) | def scale_coords(img1_shape, coords, img0_shape, ratio_pad=None):
  function clip_coords (line 240) | def clip_coords(boxes, img_shape):
  function ap_per_class (line 248) | def ap_per_class(tp, conf, pred_cls, target_cls):
  function compute_ap (line 311) | def compute_ap(recall, precision):
  function bbox_iou (line 340) | def bbox_iou(box1, box2, x1y1x2y2=True, GIoU=False, DIoU=False, CIoU=Fal...
  function box_iou (line 385) | def box_iou(box1, box2):
  function wh_iou (line 410) | def wh_iou(wh1, wh2):
  class FocalLoss (line 418) | class FocalLoss(nn.Module):
    method __init__ (line 420) | def __init__(self, loss_fcn, gamma=1.5, alpha=0.25):
    method forward (line 428) | def forward(self, pred, true):
  function smooth_BCE (line 448) | def smooth_BCE(eps=0.1):  # https://github.com/ultralytics/yolov3/issues...
  class BCEBlurWithLogitsLoss (line 453) | class BCEBlurWithLogitsLoss(nn.Module):
    method __init__ (line 455) | def __init__(self, alpha=0.05):
    method forward (line 460) | def forward(self, pred, true):
  function compute_loss (line 470) | def compute_loss(p, targets, model):  # predictions, targets, model
  function build_targets (line 533) | def build_targets(p, targets, model):
  function non_max_suppression (line 590) | def non_max_suppression(prediction, conf_thres=0.1, iou_thres=0.6, merge...
  function strip_optimizer (line 672) | def strip_optimizer(f='weights/best.pt', s=''):  # from utils.general im...
  function coco_class_count (line 686) | def coco_class_count(path='../coco/labels/train2014/'):
  function coco_only_people (line 697) | def coco_only_people(path='../coco/labels/train2017/'):  # from utils.ge...
  function crop_images_random (line 706) | def crop_images_random(path='../images/', scale=0.50):  # from utils.gen...
  function coco_single_class_labels (line 729) | def coco_single_class_labels(path='../coco/labels/train2014/', label_cla...
  function kmean_anchors (line 751) | def kmean_anchors(path='./data/coco128.yaml', n=9, img_size=640, thr=4.0...
  function print_mutation (line 850) | def print_mutation(hyp, results, yaml_file='hyp_evolved.yaml', bucket=''):
  function apply_classifier (line 881) | def apply_classifier(x, model, img, im0):
  function fitness (line 916) | def fitness(x):
  function output_to_target (line 922) | def output_to_target(output, width, height):
  function increment_dir (line 944) | def increment_dir(dir, comment=''):
  function hist2d (line 955) | def hist2d(x, y, n=100):
  function butter_lowpass_filtfilt (line 964) | def butter_lowpass_filtfilt(data, cutoff=1500, fs=50000, order=5):
  function plot_one_box (line 976) | def plot_one_box(x, img, color=None, label=None, line_thickness=None):
  function plot_wh_methods (line 990) | def plot_wh_methods():  # from utils.general import *; plot_wh_methods()
  function plot_images (line 1011) | def plot_images(images, targets, paths=None, fname='images.jpg', names=N...
  function plot_lr_scheduler (line 1094) | def plot_lr_scheduler(optimizer, scheduler, epochs=300, save_dir=''):
  function plot_test_txt (line 1111) | def plot_test_txt():  # from utils.general import *; plot_test()
  function plot_targets_txt (line 1128) | def plot_targets_txt():  # from utils.general import *; plot_targets_txt()
  function plot_study_txt (line 1141) | def plot_study_txt(f='study.txt', x=None):  # from utils.general import ...
  function plot_labels (line 1173) | def plot_labels(labels, save_dir=''):
  function plot_evolution (line 1205) | def plot_evolution(yaml_file='data/hyp.finetune.yaml'):  # from utils.ge...
  function plot_results_overlay (line 1229) | def plot_results_overlay(start=0, stop=0):  # from utils.general import ...
  function plot_results (line 1252) | def plot_results(start=0, stop=0, bucket='', id=(), labels=(),

FILE: utils/google_utils.py
  function gsutil_getsize (line 14) | def gsutil_getsize(url=''):
  function attempt_download (line 20) | def attempt_download(weights):
  function gdrive_download (line 56) | def gdrive_download(id='1n_oKgR81BJtqk75b00eAjdv03qVCQn2f', name='coco12...
  function get_token (line 90) | def get_token(cookie="./cookie"):

FILE: utils/torch_utils.py
  function init_seeds (line 16) | def init_seeds(seed=0):
  function select_device (line 28) | def select_device(device='', batch_size=None):
  function time_synchronized (line 55) | def time_synchronized():
  function is_parallel (line 60) | def is_parallel(model):
  function intersect_dicts (line 64) | def intersect_dicts(da, db, exclude=()):
  function initialize_weights (line 69) | def initialize_weights(model):
  function find_modules (line 81) | def find_modules(model, mclass=nn.Conv2d):
  function sparsity (line 86) | def sparsity(model):
  function prune (line 95) | def prune(model, amount=0.3):
  function fuse_conv_and_bn (line 106) | def fuse_conv_and_bn(conv, bn):
  function model_info (line 131) | def model_info(model, verbose=False):
  function load_classifier (line 153) | def load_classifier(name='resnet101', n=2):
  function scale_img (line 174) | def scale_img(img, ratio=1.0, same_shape=False):  # img(16,3,256,416), r...
  function copy_attr (line 188) | def copy_attr(a, b, include=(), exclude=()):
  class ModelEMA (line 197) | class ModelEMA:
    method __init__ (line 207) | def __init__(self, model, decay=0.9999, updates=0):
    method update (line 217) | def update(self, model):
    method update_attr (line 229) | def update_attr(self, model, include=(), exclude=('process_group', 're...