SYMBOL INDEX (505 symbols across 31 files)

FILE: confluence.py
  function assign_boxes_to_classes (line 15) | def assign_boxes_to_classes(bounding_boxes, classes, scores):
  function normalise_coordinates (line 30) | def normalise_coordinates(x1, y1, x2, y2,min_x,max_x,min_y,max_y):
  function confluence_nms (line 41) | def confluence_nms(bounding_boxes,scores,classes,confluence_thr,gaussian...
  function confluence (line 92) | def confluence(bounding_boxes,scores,classes,confluence_thr,gaussian,sco...

FILE: descriptor/CFOG.py
  function denseCFOG (line 9) | def denseCFOG(image):
  function denseCFOG2D (line 27) | def denseCFOG2D(image):

FILE: descriptor/LSS.py
  function denseLSS (line 8) | def denseLSS(image):
  function denseLSS2D (line 26) | def denseLSS2D(image):
  function denseLSS_matlab (line 35) | def denseLSS_matlab(image):
  function denseLSS2D_matlab (line 53) | def denseLSS2D_matlab(image):

FILE: detect_twostream.py
  function detect (line 19) | def detect(opt):

FILE: evaluation_script/coco.py
  function _isArrayLike (line 66) | def _isArrayLike(obj):
  class COCO (line 70) | class COCO:
    method __init__ (line 71) | def __init__(self, annotation_file=None):
    method createIndex (line 90) | def createIndex(self):
    method info (line 121) | def info(self):
    method getAnnIds (line 129) | def getAnnIds(self, imgIds=[], catIds=[], areaRng=[], iscrowd=None):
    method getCatIds (line 157) | def getCatIds(self, catNms=[], supNms=[], catIds=[]):
    method getImgIds (line 179) | def getImgIds(self, imgIds=[], catIds=[]):
    method loadAnns (line 200) | def loadAnns(self, ids=[]):
    method loadCats (line 211) | def loadCats(self, ids=[]):
    method loadImgs (line 222) | def loadImgs(self, ids=[]):
    method showAnns (line 233) | def showAnns(self, anns, draw_bbox=False):
    method loadRes (line 305) | def loadRes(self, resFile):
    method download (line 366) | def download(self, tarDir = None, imgIds = [] ):
    method loadNumpyAnnotations (line 390) | def loadNumpyAnnotations(self, data):
    method annToRLE (line 413) | def annToRLE(self, ann):
    method annToMask (line 434) | def annToMask(self, ann):

FILE: evaluation_script/cocoeval.py
  class COCOeval (line 10) | class COCOeval:
    method __init__ (line 60) | def __init__(self, cocoGt=None, cocoDt=None, iouType='segm'):
    method _prepare (line 84) | def _prepare(self):
    method evaluate (line 121) | def evaluate(self):
    method computeIoU (line 163) | def computeIoU(self, imgId, catId):
    method computeOks (line 192) | def computeOks(self, imgId, catId):
    method evaluateImg (line 235) | def evaluateImg(self, imgId, catId, aRng, maxDet):
    method accumulate (line 315) | def accumulate(self, p = None):
    method summarize (line 422) | def summarize(self):
    method __str__ (line 495) | def __str__(self):
  class Params (line 498) | class Params:
    method setDetParams (line 502) | def setDetParams(self):
    method setKpParams (line 513) | def setKpParams(self):
    method __init__ (line 525) | def __init__(self, iouType='segm'):

FILE: evaluation_script/evaluation_script.py
  class KAISTPedEval (line 32) | class KAISTPedEval(COCOeval):
    method __init__ (line 34) | def __init__(self, kaistGt=None, kaistDt=None, iouType='segm', method=...
    method _prepare (line 46) | def _prepare(self, id_setup):
    method evaluate (line 83) | def evaluate(self, id_setup):
    method computeIoU (line 119) | def computeIoU(self, imgId, catId):
    method iou (line 148) | def iou(self, dts, gts, pyiscrowd):
    method evaluateImg (line 181) | def evaluateImg(self, imgId, catId, hRng, oRng, maxDet):
    method accumulate (line 296) | def accumulate(self, p=None):
    method draw_figure (line 398) | def draw_figure(ax, eval_results, methods, colors):
    method summarize (line 432) | def summarize(self, id_setup, res_file=None):
  class KAISTParams (line 478) | class KAISTParams(Params):
    method setDetParams (line 481) | def setDetParams(self):
  class KAIST (line 500) | class KAIST(COCO):
    method txt2json (line 502) | def txt2json(self, txt):
    method loadRes (line 523) | def loadRes(self, resFile):
  function evaluate (line 546) | def evaluate(test_annotation_file: str, user_submission_file: str, phase...
  function draw_all (line 649) | def draw_all(eval_results, filename='figure.jpg'):

FILE: global_var.py
  function _init (line 7) | def _init():  # 初始化
  function set_value (line 12) | def set_value(key, value):
  function get_value (line 17) | def get_value(key):

FILE: gradcam_visual.py
  function get_res_img2 (line 32) | def get_res_img2(heat, mask, res_img):
  function get_res_img (line 40) | def get_res_img(bbox, mask, res_img):
  function put_text_box (line 50) | def put_text_box(bbox, cls_name, res_img):
  function concat_images (line 61) | def concat_images(images):
  function main (line 71) | def main(img_vis_path, img_ir_path):

FILE: hubconf.py
  function create (line 21) | def create(name, pretrained, channels, classes, autoshape, verbose):
  function custom (line 59) | def custom(path_or_model='path/to/model.pt', autoshape=True, verbose=True):
  function yolov5s (line 85) | def yolov5s(pretrained=True, channels=3, classes=80, autoshape=True, ver...
  function yolov5m (line 90) | def yolov5m(pretrained=True, channels=3, classes=80, autoshape=True, ver...
  function yolov5l (line 95) | def yolov5l(pretrained=True, channels=3, classes=80, autoshape=True, ver...
  function yolov5x (line 100) | def yolov5x(pretrained=True, channels=3, classes=80, autoshape=True, ver...
  function yolov5s6 (line 105) | def yolov5s6(pretrained=True, channels=3, classes=80, autoshape=True, ve...
  function yolov5m6 (line 110) | def yolov5m6(pretrained=True, channels=3, classes=80, autoshape=True, ve...
  function yolov5l6 (line 115) | def yolov5l6(pretrained=True, channels=3, classes=80, autoshape=True, ve...
  function yolov5x6 (line 120) | def yolov5x6(pretrained=True, channels=3, classes=80, autoshape=True, ve...

FILE: models/common.py
  function autopad (line 36) | def autopad(k, p=None):  # kernel, padding
  function DWConv (line 43) | def DWConv(c1, c2, k=1, s=1, act=True):
  class Conv (line 48) | class Conv(nn.Module):
    method __init__ (line 50) | def __init__(self, c1, c2, k=1, s=1, p=None, g=1, act=True):  # ch_in,...
    method forward (line 56) | def forward(self, x):
    method fuseforward (line 59) | def fuseforward(self, x):
  class TransformerLayer (line 63) | class TransformerLayer(nn.Module):
    method __init__ (line 65) | def __init__(self, c, num_heads):
    method forward (line 74) | def forward(self, x):
  class TransformerBlock (line 80) | class TransformerBlock(nn.Module):
    method __init__ (line 82) | def __init__(self, c1, c2, num_heads, num_layers):
    method forward (line 91) | def forward(self, x):
  class VGGblock (line 109) | class VGGblock(nn.Module):
    method __init__ (line 110) | def __init__(self, num_convs, c1, c2):
    method forward (line 125) | def forward(self, x):
  class ResNetblock (line 131) | class ResNetblock(nn.Module):
    method __init__ (line 134) | def __init__(self, c1, c2, stride=1):
    method forward (line 149) | def forward(self, x):
  class ResNetlayer (line 159) | class ResNetlayer(nn.Module):
    method __init__ (line 162) | def __init__(self, c1, c2, stride=1, is_first=False, num_blocks=1):
    method forward (line 178) | def forward(self, x):
  class Bottleneck (line 184) | class Bottleneck(nn.Module):
    method __init__ (line 186) | def __init__(self, c1, c2, shortcut=True, g=1, e=0.5):  # ch_in, ch_ou...
    method forward (line 193) | def forward(self, x):
  class BottleneckCSP (line 197) | class BottleneckCSP(nn.Module):
    method __init__ (line 199) | def __init__(self, c1, c2, n=1, shortcut=True, g=1, e=0.5):  # ch_in, ...
    method forward (line 210) | def forward(self, x):
  class C3 (line 216) | class C3(nn.Module):
    method __init__ (line 218) | def __init__(self, c1, c2, n=1, shortcut=True, g=1, e=0.5):  # ch_in, ...
    method forward (line 226) | def forward(self, x):
  class C3TR (line 230) | class C3TR(C3):
    method __init__ (line 232) | def __init__(self, c1, c2, n=1, shortcut=True, g=1, e=0.5):
  class SPP (line 238) | class SPP(nn.Module):
    method __init__ (line 240) | def __init__(self, c1, c2, k=(5, 9, 13)):
    method forward (line 247) | def forward(self, x):
  class SPPF (line 252) | class SPPF(nn.Module):
    method __init__ (line 254) | def __init__(self, c1, c2, k=5):  # equivalent to SPP(k=(5, 9, 13))
    method forward (line 261) | def forward(self, x):
  class Focus (line 270) | class Focus(nn.Module):
    method __init__ (line 272) | def __init__(self, c1, c2, k=1, s=1, p=None, g=1, act=True):  # ch_in,...
    method forward (line 278) | def forward(self, x):  # x(b,c,w,h) -> y(b,4c,w/2,h/2)
  class Contract (line 285) | class Contract(nn.Module):
    method __init__ (line 287) | def __init__(self, gain=2):
    method forward (line 291) | def forward(self, x):
  class Expand (line 299) | class Expand(nn.Module):
    method __init__ (line 301) | def __init__(self, gain=2):
    method forward (line 305) | def forward(self, x):
  class Concat (line 313) | class Concat(nn.Module):
    method __init__ (line 315) | def __init__(self, dimension=1):
    method forward (line 319) | def forward(self, x):
  class Add (line 324) | class Add(nn.Module):
    method __init__ (line 326) | def __init__(self, weight=0.5):
    method forward (line 330) | def forward(self, x):
  class Add2 (line 334) | class Add2(nn.Module):
    method __init__ (line 336) | def __init__(self, c1, index):
    method forward (line 340) | def forward(self, x):
  class NiNfusion (line 348) | class NiNfusion(nn.Module):
    method __init__ (line 349) | def __init__(self, c1, c2, k=1, s=1, p=None, g=1):
    method forward (line 356) | def forward(self, x):
  class DMAF (line 363) | class DMAF(nn.Module):
    method __init__ (line 364) | def __init__(self, c2):
    method forward (line 368) | def forward(self, x):
  class NMS (line 386) | class NMS(nn.Module):
    method __init__ (line 392) | def __init__(self):
    method forward (line 395) | def forward(self, x):
  class autoShape (line 399) | class autoShape(nn.Module):
    method __init__ (line 405) | def __init__(self, model):
    method autoshape (line 409) | def autoshape(self):
    method forward (line 414) | def forward(self, imgs, size=640, augment=False, profile=False):
  class Detections (line 469) | class Detections:
    method __init__ (line 471) | def __init__(self, imgs, pred, files, times=None, names=None, shape=No...
    method display (line 487) | def display(self, pprint=False, show=False, save=False, crop=False, re...
    method print (line 514) | def print(self):
    method show (line 518) | def show(self):
    method save (line 521) | def save(self, save_dir='runs/hub/exp'):
    method crop (line 525) | def crop(self, save_dir='runs/hub/exp'):
    method render (line 530) | def render(self):
    method pandas (line 534) | def pandas(self):
    method tolist (line 544) | def tolist(self):
    method __len__ (line 552) | def __len__(self):
  class Classify (line 556) | class Classify(nn.Module):
    method __init__ (line 558) | def __init__(self, c1, c2, k=1, s=1, p=None, g=1):  # ch_in, ch_out, k...
    method forward (line 564) | def forward(self, x):
  class LearnableCoefficient (line 569) | class LearnableCoefficient(nn.Module):
    method __init__ (line 570) | def __init__(self):
    method forward (line 574) | def forward(self, x):
  class LearnableWeights (line 579) | class LearnableWeights(nn.Module):
    method __init__ (line 580) | def __init__(self):
    method forward (line 585) | def forward(self, x1, x2):
  class CrossAttention (line 590) | class CrossAttention(nn.Module):
    method __init__ (line 591) | def __init__(self, d_model, d_k, d_v, h, attn_pdrop=.1, resid_pdrop=.1):
    method init_weights (line 627) | def init_weights(self):
    method forward (line 641) | def forward(self, x, attention_mask=None, attention_weights=None):
  class CrossTransformerBlock (line 690) | class CrossTransformerBlock(nn.Module):
    method __init__ (line 691) | def __init__(self, d_model, d_k, d_v, h, block_exp, attn_pdrop, resid_...
    method forward (line 737) | def forward(self, x):
  class TransformerFusionBlock (line 762) | class TransformerFusionBlock(nn.Module):
    method __init__ (line 763) | def __init__(self, d_model, vert_anchors=16, horz_anchors=16, h=8, blo...
    method _init_weights (line 800) | def _init_weights(module):
    method forward (line 809) | def forward(self, x):
  class AdaptivePool2d (line 868) | class AdaptivePool2d(nn.Module):
    method __init__ (line 869) | def __init__(self, output_h, output_w, pool_type='avg'):
    method forward (line 876) | def forward(self, x):
  class SE_Block (line 893) | class SE_Block(nn.Module):
    method __init__ (line 894) | def __init__(self, inchannel, ratio=16):
    method forward (line 904) | def forward(self, x):
  class Channel_Attention (line 913) | class Channel_Attention(nn.Module):
    method __init__ (line 914) | def __init__(self, in_channels, reduction_ratio=16, pool_types=['avg',...
    method forward (line 931) | def forward(self, x):
  class Spatial_Attention (line 951) | class Spatial_Attention(nn.Module):
    method __init__ (line 952) | def __init__(self, kernel_size=7):
    method forward (line 959) | def forward(self, x):
  class CBAM (line 967) | class CBAM(nn.Module):
    method __init__ (line 968) | def __init__(self, in_channels, reduction_ratio=16, pool_types=['avg',...
    method forward (line 977) | 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 Sum (line 25) | class Sum(nn.Module):
    method __init__ (line 27) | def __init__(self, n, weight=False):  # n: number of inputs
    method forward (line 34) | def forward(self, x):
  class GhostConv (line 46) | class GhostConv(nn.Module):
    method __init__ (line 48) | def __init__(self, c1, c2, k=1, s=1, g=1, act=True):  # ch_in, ch_out,...
    method forward (line 54) | def forward(self, x):
  class GhostBottleneck (line 59) | class GhostBottleneck(nn.Module):
    method __init__ (line 61) | def __init__(self, c1, c2, k=3, s=1):  # ch_in, ch_out, kernel, stride
    method forward (line 70) | def forward(self, x):
  class MixConv2d (line 74) | class MixConv2d(nn.Module):
    method __init__ (line 76) | def __init__(self, c1, c2, k=(1, 3), s=1, equal_ch=True):
    method forward (line 94) | def forward(self, x):
  class Ensemble (line 98) | class Ensemble(nn.ModuleList):
    method __init__ (line 100) | def __init__(self):
    method forward (line 103) | def forward(self, x, augment=False):
  function attempt_load (line 113) | def attempt_load(weights, map_location=None):

FILE: models/gradcam.py
  function find_yolo_layer (line 6) | def find_yolo_layer(model, layer_name):
  class YOLOV5GradCAM (line 24) | class YOLOV5GradCAM:
    method __init__ (line 26) | def __init__(self, model, layer_name, img_size=(640, 640)):
    method forward (line 47) | def forward(self, img_vis, img_ir, class_idx=True):
    method __call__ (line 83) | def __call__(self, img_vis, img_ir):

FILE: models/yolo.py
  class Detect (line 25) | class Detect(nn.Module):
    method __init__ (line 29) | def __init__(self, nc=80, anchors=(), ch=()):  # detection layer
    method forward (line 41) | def forward(self, x):
    method _make_grid (line 62) | def _make_grid(nx=20, ny=20):
  class Model (line 67) | class Model(nn.Module):
    method __init__ (line 68) | def __init__(self, cfg='yolov5s.yaml', ch=3, nc=None, anchors=None):  ...
    method forward (line 112) | def forward(self, x, augment=False, profile=False):
    method forward_once (line 132) | def forward_once(self, x, profile=False):
    method _initialize_biases (line 155) | def _initialize_biases(self, cf=None):  # initialize biases into Detec...
    method _print_biases (line 165) | def _print_biases(self):
    method fuse (line 177) | def fuse(self):  # fuse model Conv2d() + BatchNorm2d() layers
    method nms (line 187) | def nms(self, mode=True):  # add or remove NMS module
    method autoshape (line 201) | def autoshape(self):  # add autoShape module
    method info (line 207) | def info(self, verbose=False, img_size=640):  # print model information
  function parse_model (line 211) | def parse_model(d, ch):  # model_dict, input_channels(3)

FILE: models/yolo_test.py
  class Detect (line 26) | class Detect(nn.Module):
    method __init__ (line 30) | def __init__(self, nc=80, anchors=(), ch=()):  # detection layer
    method forward (line 43) | def forward(self, x):
    method _make_grid (line 68) | def _make_grid(nx=20, ny=20):
  class Model (line 73) | class Model(nn.Module):
    method __init__ (line 75) | def __init__(self, cfg='yolov5s.yaml', ch=3, nc=None, anchors=None):  ...
    method forward (line 115) | def forward(self, x, x2, augment=False, profile=False):
    method forward_once (line 136) | def forward_once(self, x, x2, profile=False):
    method _initialize_biases (line 165) | def _initialize_biases(self, cf=None):  # initialize biases into Detec...
    method _print_biases (line 175) | def _print_biases(self):
    method fuse (line 182) | def fuse(self):  # fuse model Conv2d() + BatchNorm2d() layers
    method nms (line 192) | def nms(self, mode=True):  # add or remove NMS module
    method autoshape (line 206) | def autoshape(self):  # add autoShape module
    method info (line 212) | def info(self, verbose=False, img_size=640):  # print model information
  function parse_model (line 216) | def parse_model(d, ch):  # model_dict, input_channels(3)

FILE: test.py
  function test (line 23) | def test(data,

FILE: train.py
  function train_rgb_ir (line 42) | def train_rgb_ir(hyp, opt, device, tb_writer=None):

FILE: utils/activations.py
  class SiLU (line 9) | class SiLU(nn.Module):  # export-friendly version of nn.SiLU()
    method forward (line 11) | def forward(x):
  class Hardswish (line 15) | class Hardswish(nn.Module):  # export-friendly version of nn.Hardswish()
    method forward (line 17) | def forward(x):
  class Mish (line 23) | class Mish(nn.Module):
    method forward (line 25) | def forward(x):
  class MemoryEfficientMish (line 29) | class MemoryEfficientMish(nn.Module):
    class F (line 30) | class F(torch.autograd.Function):
      method forward (line 32) | def forward(ctx, x):
      method backward (line 37) | def backward(ctx, grad_output):
    method forward (line 43) | def forward(self, x):
  class FReLU (line 48) | class FReLU(nn.Module):
    method __init__ (line 49) | def __init__(self, c1, k=3):  # ch_in, kernel
    method forward (line 54) | def forward(self, x):
  class AconC (line 59) | class AconC(nn.Module):
    method __init__ (line 65) | def __init__(self, c1):
    method forward (line 71) | def forward(self, x):
  class MetaAconC (line 76) | class MetaAconC(nn.Module):
    method __init__ (line 82) | def __init__(self, c1, k=1, s=1, r=16):  # ch_in, kernel, stride, r
    method forward (line 92) | def forward(self, x):

FILE: utils/autoanchor.py
  function check_anchor_order (line 12) | def check_anchor_order(m):
  function check_anchors (line 23) | def check_anchors(dataset, model, thr=4.0, imgsz=640):
  function check_anchors_rgb_ir (line 62) | def check_anchors_rgb_ir(dataset, model, thr=4.0, imgsz=640):
  function kmean_anchors (line 103) | def kmean_anchors(path='./data/coco128.yaml', n=9, img_size=640, thr=4.0...

FILE: utils/confluence.py
  function xywh2xyxy (line 6) | def xywh2xyxy(x):
  function scale_coords_x (line 15) | def scale_coords_x(img1_shape, coords, img0_shape):
  function clip_coords (line 27) | def clip_coords(boxes, img_shape):
  function plot_one_box (line 34) | def plot_one_box(x, img, color=None, label=None, line_thickness=None):
  function confluence_process (line 50) | def confluence_process(prediction, conf_thres=0.1, p_thres=0.6):
  function confluence (line 109) | def confluence(prediction, class_num, p_thres=0.6):
  function test (line 198) | def test():

FILE: utils/datasets.py
  class RandomSampler (line 38) | class RandomSampler(torch.utils.data.sampler.RandomSampler):
    method __init__ (line 40) | def __init__(self, data_source, replacement=False, num_samples=None):
    method num_samples (line 58) | def num_samples(self):
    method __iter__ (line 64) | def __iter__(self):
    method __len__ (line 72) | def __len__(self):
  function get_hash (line 82) | def get_hash(files):
  function exif_size (line 87) | def exif_size(img):
  function create_dataloader_rgb_ir (line 102) | def create_dataloader_rgb_ir(path1, path2,  imgsz, batch_size, stride, o...
  class InfiniteDataLoader (line 138) | class InfiniteDataLoader(torch.utils.data.dataloader.DataLoader):
    method __init__ (line 144) | def __init__(self, *args, **kwargs):
    method __len__ (line 149) | def __len__(self):
    method __iter__ (line 152) | def __iter__(self):
  class _RepeatSampler (line 157) | class _RepeatSampler(object):
    method __init__ (line 164) | def __init__(self, sampler):
    method __iter__ (line 167) | def __iter__(self):
  class LoadImages (line 172) | class LoadImages:  # for inference
    method __init__ (line 173) | def __init__(self, path, img_size=640, stride=32):
    method __iter__ (line 201) | def __iter__(self):
    method __next__ (line 205) | def __next__(self):
    method new_video (line 243) | def new_video(self, path):
    method __len__ (line 248) | def __len__(self):
  class LoadWebcam (line 252) | class LoadWebcam:  # for inference
    method __init__ (line 253) | def __init__(self, pipe='0', img_size=640, stride=32):
    method __iter__ (line 267) | def __iter__(self):
    method __next__ (line 271) | def __next__(self):
    method __len__ (line 306) | def __len__(self):
  class LoadStreams (line 310) | class LoadStreams:  # multiple IP or RTSP cameras
    method __init__ (line 311) | def __init__(self, sources='streams.txt', img_size=640, stride=32):
    method update (line 351) | def update(self, index, cap):
    method __iter__ (line 364) | def __iter__(self):
    method __next__ (line 368) | def __next__(self):
    method __len__ (line 387) | def __len__(self):
  function img2label_paths (line 391) | def img2label_paths(img_paths):
  class LoadImagesAndLabels (line 404) | class LoadImagesAndLabels(Dataset):  # for training/testing
    method __init__ (line 405) | def __init__(self, path, img_size=640, batch_size=16, augment=False, h...
    method cache_labels (line 512) | def cache_labels(self, path=Path('./labels.cache'), prefix=''):
    method __len__ (line 567) | def __len__(self):
    method __getitem__ (line 576) | def __getitem__(self, index):
    method collate_fn (line 654) | def collate_fn(batch):
    method collate_fn4 (line 661) | def collate_fn4(batch):
  class LoadMultiModalImagesAndLabels (line 690) | class LoadMultiModalImagesAndLabels(Dataset):  # for training/testing
    method __init__ (line 694) | def __init__(self, path_rgb, path_ir, img_size=640, batch_size=16, aug...
    method cache_labels (line 882) | def cache_labels(self, imgfiles, labelfiles, path=Path('./labels.cache...
    method __len__ (line 939) | def __len__(self):
    method __getitem__ (line 948) | def __getitem__(self, index):
    method collate_fn (line 1027) | def collate_fn(batch):
    method collate_fn4 (line 1034) | def collate_fn4(batch):
  function shift_augment (line 1061) | def shift_augment(self, img):
  function load_image (line 1080) | def load_image(self, index):
  function load_image_rgb_ir (line 1097) | def load_image_rgb_ir(self, index):
  function augment_hsv (line 1129) | def augment_hsv(img, hgain=0.5, sgain=0.5, vgain=0.5):
  function hist_equalize (line 1143) | def hist_equalize(img, clahe=True, bgr=False):
  function load_mosaic (line 1154) | def load_mosaic(self, index):
  function load_mosaic_RGB_IR (line 1208) | def load_mosaic_RGB_IR(self, index1, index2):
  function load_mosaic9 (line 1313) | def load_mosaic9(self, index):
  function replicate (line 1387) | def replicate(img, labels):
  function letterbox (line 1404) | def letterbox(img, new_shape=(640, 640), color=(114, 114, 114), auto=Tru...
  function random_perspective (line 1447) | def random_perspective(img, targets=(), segments=(), degrees=10, transla...
  function random_perspective_rgb_ir (line 1535) | def random_perspective_rgb_ir(img_rgb, img_ir, targets_rgb=(),targets_ir...
  function box_candidates (line 1633) | def box_candidates(box1, box2, wh_thr=2, ar_thr=20, area_thr=0.1, eps=1e...
  function cutout (line 1641) | def cutout(image, labels):
  function create_folder (line 1687) | def create_folder(path='./new'):
  function flatten_recursive (line 1694) | def flatten_recursive(path='../coco128'):
  function extract_boxes (line 1702) | def extract_boxes(path='../coco128/'):  # from utils.datasets import *; ...
  function autosplit (line 1737) | def autosplit(path='../coco128', weights=(0.9, 0.1, 0.0), annotated_only...

FILE: utils/flask_rest_api/restapi.py
  function predict (line 17) | def predict():

FILE: utils/general.py
  function set_logging (line 39) | def set_logging(rank=-1, verbose=True):
  function init_seeds (line 45) | def init_seeds(seed=0, deterministic=False):
  function get_latest_run (line 60) | def get_latest_run(search_dir='.'):
  function isdocker (line 66) | def isdocker():
  function emojis (line 71) | def emojis(str=''):
  function file_size (line 76) | def file_size(file):
  function check_online (line 81) | def check_online():
  function check_git_status (line 91) | def check_git_status():
  function check_requirements (line 113) | def check_requirements(requirements='requirements.txt', exclude=()):
  function check_img_size (line 142) | def check_img_size(img_size, s=32):
  function check_imshow (line 150) | def check_imshow():
  function check_file (line 164) | def check_file(file):
  function check_dataset (line 175) | def check_dataset(dict):
  function check_version (line 198) | def check_version(current='0.0.0', minimum='0.0.0', name='version ', pin...
  function download (line 210) | def download(url, dir='.', multi_thread=False):
  function make_divisible (line 234) | def make_divisible(x, divisor):
  function clean_str (line 239) | def clean_str(s):
  function one_cycle (line 244) | def one_cycle(y1=0.0, y2=1.0, steps=100):
  function colorstr (line 249) | def colorstr(*input):
  function labels_to_class_weights (line 274) | def labels_to_class_weights(labels, nc=80):
  function labels_to_image_weights (line 293) | def labels_to_image_weights(labels, nc=80, class_weights=np.ones(80)):
  function coco80_to_coco91_class (line 301) | def coco80_to_coco91_class():  # converts 80-index (val2014) to 91-index...
  function xyxy2xywh2 (line 312) | def xyxy2xywh2(x):
  function xyxy2xywh (line 322) | def xyxy2xywh(x):
  function xywh2xyxy (line 332) | def xywh2xyxy(x):
  function xywhn2xyxy (line 342) | def xywhn2xyxy(x, w=640, h=640, padw=0, padh=0):
  function xyn2xy (line 352) | def xyn2xy(x, w=640, h=640, padw=0, padh=0):
  function segment2box (line 360) | def segment2box(segment, width=640, height=640):
  function segments2boxes (line 368) | def segments2boxes(segments):
  function resample_segments (line 377) | def resample_segments(segments, n=1000):
  function scale_coords (line 386) | def scale_coords(img1_shape, coords, img0_shape, ratio_pad=None):
  function clip_coords (line 402) | def clip_coords(boxes, img_shape):
  function bbox_iou (line 410) | def bbox_iou(box1, box2, x1y1x2y2=True, GIoU=False, DIoU=False, CIoU=Fal...
  function box_iou (line 455) | def box_iou(box1, box2):
  function wh_iou (line 480) | def wh_iou(wh1, wh2):
  function python_nms (line 488) | def python_nms(dets, scores, iou_thresh):
  function non_max_suppression (line 518) | def non_max_suppression(prediction, conf_thres=0.25, iou_thres=0.45, cla...
  function strip_optimizer (line 610) | def strip_optimizer(f='best.pt', s=''):  # from utils.general import *; ...
  function print_mutation (line 626) | def print_mutation(hyp, results, yaml_file='hyp_evolved.yaml', bucket=''):
  function apply_classifier (line 657) | def apply_classifier(x, model, img, im0):
  function save_one_box (line 692) | def save_one_box(xyxy, im, file='image.jpg', gain=1.02, pad=10, square=F...
  function increment_path (line 705) | def increment_path(path, exist_ok=False, sep='', mkdir=False):

FILE: utils/google_utils.py
  function gsutil_getsize (line 13) | def gsutil_getsize(url=''):
  function attempt_download (line 19) | def attempt_download(file, repo='ultralytics/yolov5'):
  function gdrive_download (line 59) | def gdrive_download(id='16TiPfZj7htmTyhntwcZyEEAejOUxuT6m', file='tmp.zi...
  function get_token (line 94) | def get_token(cookie="./cookie"):

FILE: utils/gradcam.py
  function preprocess_image (line 18) | def preprocess_image(img):
  function show_cam_on_image (line 33) | def show_cam_on_image(img, mask, epoch, layer):
  function calcGradCam (line 43) | def calcGradCam(imgpath, feature, epoch, layer):

FILE: utils/loss.py
  function smooth_BCE (line 15) | def smooth_BCE(eps=0.1):  # https://github.com/ultralytics/yolov3/issues...
  class BCEBlurWithLogitsLoss (line 20) | class BCEBlurWithLogitsLoss(nn.Module):
    method __init__ (line 22) | def __init__(self, alpha=0.05):
    method forward (line 27) | def forward(self, pred, true):
  class FocalLoss (line 37) | class FocalLoss(nn.Module):
    method __init__ (line 39) | def __init__(self, loss_fcn, gamma=1.5, alpha=0.25):
    method forward (line 47) | def forward(self, pred, true):
  class QFocalLoss (line 67) | class QFocalLoss(nn.Module):
    method __init__ (line 69) | def __init__(self, loss_fcn, gamma=1.5, alpha=0.25):
    method forward (line 77) | def forward(self, pred, true):
  class VFLoss (line 94) | class VFLoss(nn.Module):
    method __init__ (line 95) | def __init__(self, loss_fcn, gamma=2.0, alpha=0.25):
    method forward (line 104) | def forward(self, pred, true):
  class RankingLoss2 (line 121) | class RankingLoss2(nn.Module):
    method __init__ (line 122) | def __init__(self, threshold):
    method forward (line 127) | def forward(self, pred, true):
  class RankingLoss (line 139) | class RankingLoss(nn.Module):
    method __init__ (line 140) | def __init__(self, gamma):
    method forward (line 145) | def forward(self, pred, true):
  class SimLoss (line 177) | class SimLoss(nn.Module):
    method __init__ (line 178) | def __init__(self, gamma):
    method des_SSD (line 183) | def des_SSD(self, i, j, descriptor):
    method des_NCC (line 202) | def des_NCC(self, i, j, descriptor):
    method gradient_loss (line 220) | def gradient_loss(self, s, penalty='l2'):
    method mse_loss (line 229) | def mse_loss(self, x, y):
    method DSC (line 232) | def DSC(self, pred, target):
    method gncc_loss (line 239) | def gncc_loss(self, I, J, eps=1e-5):
    method compute_local_sums (line 252) | def compute_local_sums(self, I, J, filt, stride, padding, win):
    method cc_loss (line 267) | def cc_loss(self, x, y):
    method Get_Ja (line 277) | def Get_Ja(self, flow):
    method NJ_loss (line 286) | def NJ_loss(self, ypred):
    method lncc_loss (line 290) | def lncc_loss(self, i, j, win=[9, 9], eps=1e-5):
    method forward (line 313) | def forward(self, reference, sensed_tran, sensed, reference_inv_tran, ...
  class ComputeLoss (line 325) | class ComputeLoss:
    method __init__ (line 327) | def __init__(self, model, autobalance=False):
    method __call__ (line 354) | def __call__(self, p, targets):  # predictions, targets, model
    method build_targets (line 409) | def build_targets(self, p, targets):

FILE: utils/metrics.py
  function fitness (line 12) | def fitness(x):
  function ap_per_class (line 18) | def ap_per_class(tp, conf, pred_cls, target_cls, plot=False, save_dir='....
  function compute_ap (line 85) | def compute_ap(recall, precision):
  class ConfusionMatrix (line 113) | class ConfusionMatrix:
    method __init__ (line 115) | def __init__(self, nc, conf=0.25, iou_thres=0.45):
    method process_batch (line 121) | def process_batch(self, detections, labels):
    method matrix (line 161) | def matrix(self):
    method plot (line 164) | def plot(self, save_dir='', names=()):
    method print (line 183) | def print(self):
  function plot_pr_curve (line 190) | def plot_pr_curve(px, py, ap, save_dir='pr_curve.png', names=()):
  function plot_mc_curve (line 210) | def plot_mc_curve(px, py, save_dir='mc_curve.png', names=(), xlabel='Con...

FILE: utils/plots.py
  class Colors (line 29) | class Colors:
    method __init__ (line 31) | def __init__(self):
    method __call__ (line 35) | def __call__(self, i, bgr=False):
    method hex2rgb (line 40) | def hex2rgb(h):  # rgb order (PIL)
  function hist2d (line 47) | def hist2d(x, y, n=100):
  function butter_lowpass_filtfilt (line 56) | def butter_lowpass_filtfilt(data, cutoff=1500, fs=50000, order=5):
  function plot_one_box (line 67) | def plot_one_box(x, im, color=None, label=None, line_thickness=3):
  function plot_one_box_PIL (line 84) | def plot_one_box_PIL(box, im, color=None, label=None, line_thickness=None):
  function plot_wh_methods (line 99) | def plot_wh_methods():  # from utils.plots import *; plot_wh_methods()
  function output_to_target (line 119) | def output_to_target(output):
  function plot_samples (line 128) | def plot_samples(batch_index, images, path, tcls, tbox, indices, anchors...
  function plot_images (line 173) | def plot_images(images, targets, paths=None, fname='images.jpg', names=N...
  function plot_lr_scheduler (line 251) | def plot_lr_scheduler(optimizer, scheduler, epochs=300, save_dir=''):
  function plot_test_txt (line 268) | def plot_test_txt():  # from utils.plots import *; plot_test()
  function plot_targets_txt (line 285) | def plot_targets_txt():  # from utils.plots import *; plot_targets_txt()
  function plot_study_txt (line 298) | def plot_study_txt(path='', x=None):  # from utils.plots import *; plot_...
  function plot_labels (line 330) | def plot_labels(labels, names=(), save_dir=Path(''), loggers=None):
  function plot_evolution (line 378) | def plot_evolution(yaml_file='data/hyp.finetune.yaml'):  # from utils.pl...
  function profile_idetection (line 402) | def profile_idetection(start=0, stop=0, labels=(), save_dir=''):
  function plot_results_overlay (line 434) | def plot_results_overlay(start=0, stop=0):  # from utils.plots import *;...
  function plot_results (line 457) | def plot_results(file='path/to/results.csv', dir=''):

FILE: utils/torch_utils.py
  function torch_distributed_zero_first (line 28) | def torch_distributed_zero_first(local_rank: int):
  function init_torch_seeds (line 39) | def init_torch_seeds(seed=0):
  function date_modified (line 48) | def date_modified(path=__file__):
  function git_describe (line 54) | def git_describe(path=Path(__file__).parent):  # path must be a directory
  function select_device (line 63) | def select_device(device='', batch_size=None):
  function time_synchronized (line 89) | def time_synchronized():
  function profile (line 96) | def profile(x, ops, n=100, device=None):
  function is_parallel (line 135) | def is_parallel(model):
  function intersect_dicts (line 139) | def intersect_dicts(da, db, exclude=()):
  function initialize_weights (line 144) | def initialize_weights(model):
  function find_modules (line 157) | def find_modules(model, mclass=nn.Conv2d):
  function sparsity (line 162) | def sparsity(model):
  function prune (line 171) | def prune(model, amount=0.3):
  function fuse_conv_and_bn (line 182) | def fuse_conv_and_bn(conv, bn):
  function model_info (line 205) | def model_info(model, verbose=False, img_size=640):
  function load_classifier (line 238) | def load_classifier(name='resnet101', n=2):
  function scale_img (line 257) | def scale_img(img, ratio=1.0, same_shape=False, gs=32):  # img(16,3,256,...
  function copy_attr (line 270) | def copy_attr(a, b, include=(), exclude=()):
  class ModelEMA (line 279) | class ModelEMA:
    method __init__ (line 289) | def __init__(self, model, decay=0.9999, updates=0):
    method update (line 299) | def update(self, model):
    method update_attr (line 311) | def update_attr(self, model, include=(), exclude=('process_group', 're...

FILE: utils/wandb_logging/log_dataset.py
  function create_dataset_artifact (line 10) | def create_dataset_artifact(opt):

FILE: utils/wandb_logging/wandb_utils.py
  function remove_prefix (line 23) | def remove_prefix(from_string, prefix=WANDB_ARTIFACT_PREFIX):
  function check_wandb_config_file (line 27) | def check_wandb_config_file(data_config_file):
  function get_run_info (line 34) | def get_run_info(run_path):
  function check_wandb_resume (line 42) | def check_wandb_resume(opt):
  function process_wandb_config_ddp_mode (line 56) | def process_wandb_config_ddp_mode(opt):
  class WandbLogger (line 80) | class WandbLogger():
    method __init__ (line 81) | def __init__(self, opt, name, run_id, data_dict, job_type='Training'):
    method check_and_upload_dataset (line 115) | def check_and_upload_dataset(self, opt):
    method setup_training (line 126) | def setup_training(self, opt, data_dict):
    method download_dataset_artifact (line 159) | def download_dataset_artifact(self, path, alias):
    method download_model_artifact (line 167) | def download_model_artifact(self, opt):
    method log_model (line 179) | def log_model(self, path, opt, epoch, fitness_score, best_model=False):
    method log_dataset_artifact (line 193) | def log_dataset_artifact(self, data_file, single_cls, project, overwri...
    method map_val_table_path (line 222) | def map_val_table_path(self):
    method create_dataset_table (line 228) | def create_dataset_table(self, dataset, class_to_id, name='dataset'):
    method log_training_progress (line 263) | def log_training_progress(self, predn, path, names):
    method log (line 285) | def log(self, log_dict):
    method end_epoch (line 290) | def end_epoch(self, best_result=False):
    method finish_run (line 302) | def finish_run(self):