SYMBOL INDEX (573 symbols across 34 files)

FILE: RSChatGPT-shell.py
  function prompts (line 19) | def prompts(name, description):
  function get_new_image_name (line 25) | def get_new_image_name(org_img_name, func_name="update"):
  class EdgeDetection (line 35) | class EdgeDetection:
    method __init__ (line 36) | def __init__(self, device):
    method inference (line 44) | def inference(self, inputs):
  class ObjectCounting (line 49) | class ObjectCounting:
    method __init__ (line 50) | def __init__(self, device):
    method inference (line 57) | def inference(self, inputs):
  class InstanceSegmentation (line 63) | class InstanceSegmentation:
    method __init__ (line 64) | def __init__(self, device):
    method inference (line 73) | def inference(self, inputs):
  class SceneClassification (line 79) | class SceneClassification:
    method __init__ (line 80) | def __init__(self, device):
    method inference (line 88) | def inference(self, inputs):
  class LandUseSegmentation (line 93) | class LandUseSegmentation:
    method __init__ (line 94) | def __init__(self, device):
    method inference (line 104) | def inference(self, inputs):
  class ObjectDetection (line 110) | class ObjectDetection:
    method __init__ (line 111) | def __init__(self, device):
    method inference (line 121) | def inference(self, inputs):
  class ImageCaptioning (line 127) | class ImageCaptioning:
    method __init__ (line 128) | def __init__(self, device):
    method inference (line 135) | def inference(self, image_path):
  class RSChatGPT (line 140) | class RSChatGPT:
    method __init__ (line 141) | def __init__(self, gpt_name,load_dict,openai_key,proxy_url):
    method initialize (line 171) | def initialize(self):
    method run_text (line 183) | def run_text(self, text, state):
    method run_image (line 191) | def run_image(self, image_dir, state, txt=None):

FILE: RStask/EdgeDetection/Canny.py
  class Image2Canny (line 4) | class Image2Canny:
    method __init__ (line 5) | def __init__(self):
    method inference (line 10) | def inference(self, inputs,new_image_name):

FILE: RStask/ImageCaptioning/blip.py
  class BLIP (line 5) | class BLIP:
    method __init__ (line 6) | def __init__(self, device):
    method inference (line 12) | def inference(self, image_path):

FILE: RStask/InstanceSegmentation/SwinUpper.py
  class SwinInstance (line 6) | class SwinInstance:
    method __init__ (line 7) | def __init__(self, device):
    method inference (line 24) | def inference(self, image_path, det_prompt ,updated_image_path):

FILE: RStask/InstanceSegmentation/model.py
  class SegmentationHead (line 7) | class SegmentationHead(nn.Sequential):
    method __init__ (line 8) | def __init__(self, in_channels, out_channels, kernel_size=3, activatio...
  class ClassificationHead (line 15) | class ClassificationHead(nn.Sequential):
    method __init__ (line 16) | def __init__(self, in_channels, classes, pooling="avg", dropout=0.2, a...
  function initialize_decoder (line 27) | def initialize_decoder(module):
  function initialize_head (line 45) | def initialize_head(module):
  class SwinUPer (line 56) | class SwinUPer(torch.nn.Module):
    method __init__ (line 57) | def __init__(self, classes: int = 16):
    method initialize (line 77) | def initialize(self):
    method forward (line 80) | def forward(self, x):

FILE: RStask/InstanceSegmentation/swin.py
  class Mlp (line 26) | class Mlp(nn.Module):
    method __init__ (line 29) | def __init__(self, in_features, hidden_features=None, out_features=Non...
    method forward (line 38) | def forward(self, x):
  function window_partition (line 47) | def window_partition(x, window_size):
  function window_reverse (line 62) | def window_reverse(windows, window_size, H, W):
  class WindowAttention (line 79) | class WindowAttention(nn.Module):
    method __init__ (line 93) | def __init__(self, dim, window_size, num_heads, qkv_bias=True, qk_scal...
    method forward (line 127) | def forward(self, x, mask=None):
  class SwinTransformerBlock (line 162) | class SwinTransformerBlock(nn.Module):
    method __init__ (line 180) | def __init__(self, dim, num_heads, window_size=7, shift_size=0,
    method forward (line 204) | def forward(self, x, mask_matrix):
  class PatchMerging (line 264) | class PatchMerging(nn.Module):
    method __init__ (line 271) | def __init__(self, dim, norm_layer=nn.LayerNorm):
    method forward (line 277) | def forward(self, x, H, W):
  class BasicLayer (line 307) | class BasicLayer(nn.Module):
    method __init__ (line 326) | def __init__(self,
    method forward (line 368) | def forward(self, x, H, W):
  class PatchEmbed (line 411) | class PatchEmbed(nn.Module):
    method __init__ (line 421) | def __init__(self, patch_size=4, in_chans=3, embed_dim=96, norm_layer=...
    method forward (line 435) | def forward(self, x):
  class swin (line 455) | class swin(nn.Module):
    method __init__ (line 484) | def __init__(self,
    method _freeze_stages (line 580) | def _freeze_stages(self):
    method init_weights (line 597) | def init_weights(self, pretrained):
    method forward (line 665) | def forward(self, x):
    method train (line 694) | def train(self, mode=True):

FILE: RStask/InstanceSegmentation/uper.py
  function resize (line 17) | def resize(input,
  class PPM (line 38) | class PPM(nn.ModuleList):
    method __init__ (line 52) | def __init__(self, pool_scales, in_channels, channels, conv_cfg, norm_...
    method forward (line 75) | def forward(self, x):
  class BaseDecodeHead (line 88) | class BaseDecodeHead(BaseModule, metaclass=ABCMeta):
    method __init__ (line 154) | def __init__(self,
    method extra_repr (line 233) | def extra_repr(self):
    method _init_inputs (line 240) | def _init_inputs(self, in_channels, in_index, input_transform):
    method _transform_inputs (line 278) | def _transform_inputs(self, inputs):
    method forward (line 306) | def forward(self, inputs):
    method cls_seg (line 310) | def cls_seg(self, feat):
    method predict (line 318) | def predict(self, inputs: Tuple[Tensor], batch_img_metas: List[dict],
    method _stack_batch_gt (line 338) | def _stack_batch_gt(self, batch_data_samples) -> Tensor:
    method predict_by_feat (line 345) | def predict_by_feat(self, seg_logits: Tensor,
  class UPerHead (line 366) | class UPerHead(BaseDecodeHead):
    method __init__ (line 377) | def __init__(self, pool_scales=(1, 2, 3, 6), **kwargs):
    method psp_forward (line 429) | def psp_forward(self, inputs):
    method _forward_feature (line 439) | def _forward_feature(self, inputs):
    method forward (line 488) | def forward(self, *inputs):

FILE: RStask/LanduseSegmentation/seg_hrnet.py
  function conv3x3 (line 17) | def conv3x3(in_planes, out_planes, stride=1):
  class BasicBlock (line 23) | class BasicBlock(nn.Module):
    method __init__ (line 26) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 36) | def forward(self, x):
  class Bottleneck (line 55) | class Bottleneck(nn.Module):
    method __init__ (line 58) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 73) | def forward(self, x):
  class HighResolutionModule (line 96) | class HighResolutionModule(nn.Module):
    method __init__ (line 97) | def __init__(self, num_branches, blocks, num_blocks, num_inchannels,
    method _check_branches (line 114) | def _check_branches(self, num_branches, blocks, num_blocks,
    method _make_one_branch (line 131) | def _make_one_branch(self, branch_index, block, num_blocks, num_channels,
    method _make_branches (line 155) | def _make_branches(self, num_branches, block, num_blocks, num_channels):
    method _make_fuse_layers (line 164) | def _make_fuse_layers(self):
    method get_num_inchannels (line 210) | def get_num_inchannels(self):
    method forward (line 213) | def forward(self, x):
  class hrmodel (line 245) | class hrmodel(nn.Module):
    method __init__ (line 246) | def __init__(self):
    method _make_transition_layer (line 298) | def _make_transition_layer(
    method _make_layer (line 334) | def _make_layer(self, block, inplanes, planes, blocks, stride=1):
    method _make_stage (line 351) | def _make_stage(self, layer_config, num_inchannels,
    method forward (line 380) | def forward(self, x,gts=None):
  class ConvModule (line 434) | class ConvModule(nn.Module):
    method __init__ (line 435) | def __init__(self):
    method forward (line 440) | def forward(self,x):
  class HRNet48 (line 442) | class HRNet48(nn.Module):
    method __init__ (line 443) | def __init__(self,device):
    method visualize (line 458) | def visualize(self,pred,cls):
    method inference (line 473) | def inference(self,image_path, det_prompt,updated_image_path):

FILE: RStask/ObjectCounting/Yolocounting.py
  class YoloCounting (line 7) | class YoloCounting:
    method __init__ (line 8) | def __init__(self, device):
    method inference (line 21) | def inference(self, image_path, det_prompt):
    method non_max_suppression (line 57) | def non_max_suppression(self, prediction,

FILE: RStask/ObjectDetection/YOLOv5.py
  class YoloDetection (line 8) | class YoloDetection:
    method __init__ (line 9) | def __init__(self, device):
    method inference (line 20) | def inference(self, image_path, det_prompt,updated_image_path):
    method visualize (line 42) | def visualize(self,image_path, newpic_path,detections):
    method non_max_suppression (line 54) | def non_max_suppression(self, prediction,

FILE: RStask/ObjectDetection/models/common.py
  function autopad (line 31) | def autopad(k, p=None):  # kernel, padding
  class Conv (line 38) | class Conv(nn.Module):
    method __init__ (line 40) | def __init__(self, c1, c2, k=1, s=1, p=None, g=1, act=True):  # ch_in,...
    method forward (line 46) | def forward(self, x):
    method forward_fuse (line 49) | def forward_fuse(self, x):
  class DWConv (line 53) | class DWConv(Conv):
    method __init__ (line 55) | def __init__(self, c1, c2, k=1, s=1, act=True):  # ch_in, ch_out, kern...
  class TransformerLayer (line 59) | class TransformerLayer(nn.Module):
    method __init__ (line 61) | def __init__(self, c, num_heads):
    method forward (line 70) | def forward(self, x):
  class TransformerBlock (line 76) | class TransformerBlock(nn.Module):
    method __init__ (line 78) | def __init__(self, c1, c2, num_heads, num_layers):
    method forward (line 87) | def forward(self, x):
  class Bottleneck (line 95) | class Bottleneck(nn.Module):
    method __init__ (line 97) | def __init__(self, c1, c2, shortcut=True, g=1, e=0.5):  # ch_in, ch_ou...
    method forward (line 104) | def forward(self, x):
  class BottleneckCSP (line 108) | class BottleneckCSP(nn.Module):
    method __init__ (line 110) | def __init__(self, c1, c2, n=1, shortcut=True, g=1, e=0.5):  # ch_in, ...
    method forward (line 121) | def forward(self, x):
  class C3 (line 127) | class C3(nn.Module):
    method __init__ (line 129) | def __init__(self, c1, c2, n=1, shortcut=True, g=1, e=0.5):  # ch_in, ...
    method forward (line 138) | def forward(self, x):
  class C3TR (line 142) | class C3TR(C3):
    method __init__ (line 144) | def __init__(self, c1, c2, n=1, shortcut=True, g=1, e=0.5):
  class C3SPP (line 150) | class C3SPP(C3):
    method __init__ (line 152) | def __init__(self, c1, c2, k=(5, 9, 13), n=1, shortcut=True, g=1, e=0.5):
  class C3Ghost (line 158) | class C3Ghost(C3):
    method __init__ (line 160) | def __init__(self, c1, c2, n=1, shortcut=True, g=1, e=0.5):
  class SPP (line 166) | class SPP(nn.Module):
    method __init__ (line 168) | def __init__(self, c1, c2, k=(5, 9, 13)):
    method forward (line 175) | def forward(self, x):
  class SPPF (line 182) | class SPPF(nn.Module):
    method __init__ (line 184) | def __init__(self, c1, c2, k=5):  # equivalent to SPP(k=(5, 9, 13))
    method forward (line 191) | def forward(self, x):
  class Focus (line 200) | class Focus(nn.Module):
    method __init__ (line 202) | def __init__(self, c1, c2, k=1, s=1, p=None, g=1, act=True):  # ch_in,...
    method forward (line 207) | def forward(self, x):  # x(b,c,w,h) -> y(b,4c,w/2,h/2)
  class GhostConv (line 212) | class GhostConv(nn.Module):
    method __init__ (line 214) | def __init__(self, c1, c2, k=1, s=1, g=1, act=True):  # ch_in, ch_out,...
    method forward (line 220) | def forward(self, x):
  class GhostBottleneck (line 225) | class GhostBottleneck(nn.Module):
    method __init__ (line 227) | def __init__(self, c1, c2, k=3, s=1):  # ch_in, ch_out, kernel, stride
    method forward (line 237) | def forward(self, x):
  class Contract (line 241) | class Contract(nn.Module):
    method __init__ (line 243) | def __init__(self, gain=2):
    method forward (line 247) | def forward(self, x):
  class Expand (line 255) | class Expand(nn.Module):
    method __init__ (line 257) | def __init__(self, gain=2):
    method forward (line 261) | def forward(self, x):
  class Concat (line 269) | class Concat(nn.Module):
    method __init__ (line 271) | def __init__(self, dimension=1):
    method forward (line 275) | def forward(self, x):
  class DetectMultiBackend (line 279) | class DetectMultiBackend(nn.Module):
    method __init__ (line 281) | def __init__(self, weights='yolov5s.pt', device=torch.device('cpu'), d...
    method forward (line 304) | def forward(self, im, augment=False, visualize=False, val=False):
  class AutoShape (line 316) | class AutoShape(nn.Module):
    method __init__ (line 326) | def __init__(self, model):
    method _apply (line 334) | def _apply(self, fn):
    method forward (line 346) | def forward(self, imgs, size=640, augment=False, profile=False):
  class Detections (line 408) | class Detections:
    method __init__ (line 410) | def __init__(self, imgs, pred, files, times=(0, 0, 0, 0), names=None, ...
    method display (line 427) | def display(self, pprint=False, show=False, save=False, crop=False, re...
    method print (line 470) | def print(self):
    method show (line 474) | def show(self, labels=True):
    method save (line 477) | def save(self, labels=True, save_dir='runs/detect/exp'):
    method crop (line 481) | def crop(self, save=True, save_dir='runs/detect/exp'):
    method render (line 485) | def render(self, labels=True):
    method pandas (line 489) | def pandas(self):
    method tolist (line 499) | def tolist(self):
    method __len__ (line 508) | def __len__(self):
    method __str__ (line 511) | def __str__(self):
  class Classify (line 516) | class Classify(nn.Module):
    method __init__ (line 518) | def __init__(self, c1, c2, k=1, s=1, p=None, g=1):  # ch_in, ch_out, k...
    method forward (line 524) | def forward(self, x):

FILE: RStask/ObjectDetection/models/experimental.py
  class CrossConv (line 15) | class CrossConv(nn.Module):
    method __init__ (line 17) | def __init__(self, c1, c2, k=3, s=1, g=1, e=1.0, shortcut=False):
    method forward (line 25) | def forward(self, x):
  class Sum (line 29) | class Sum(nn.Module):
    method __init__ (line 31) | def __init__(self, n, weight=False):  # n: number of inputs
    method forward (line 38) | def forward(self, x):
  class MixConv2d (line 50) | class MixConv2d(nn.Module):
    method __init__ (line 52) | def __init__(self, c1, c2, k=(1, 3), s=1, equal_ch=True):  # ch_in, ch...
    method forward (line 71) | def forward(self, x):
  class Ensemble (line 75) | class Ensemble(nn.ModuleList):
    method __init__ (line 77) | def __init__(self):
    method forward (line 80) | def forward(self, x, augment=False, profile=False, visualize=False):
  function attempt_load (line 90) | def attempt_load(weights, map_location=None, inplace=True, fuse=True):

FILE: RStask/ObjectDetection/models/tf.py
  class TFBN (line 37) | class TFBN(keras.layers.Layer):
    method __init__ (line 39) | def __init__(self, w=None):
    method call (line 48) | def call(self, inputs):
  class TFPad (line 52) | class TFPad(keras.layers.Layer):
    method __init__ (line 54) | def __init__(self, pad):
    method call (line 58) | def call(self, inputs):
  class TFConv (line 62) | class TFConv(keras.layers.Layer):
    method __init__ (line 64) | def __init__(self, c1, c2, k=1, s=1, p=None, g=1, act=True, w=None):
    method call (line 93) | def call(self, inputs):
  class TFFocus (line 97) | class TFFocus(keras.layers.Layer):
    method __init__ (line 99) | def __init__(self, c1, c2, k=1, s=1, p=None, g=1, act=True, w=None):
    method call (line 104) | def call(self, inputs):  # x(b,w,h,c) -> y(b,w/2,h/2,4c)
  class TFBottleneck (line 112) | class TFBottleneck(keras.layers.Layer):
    method __init__ (line 114) | def __init__(self, c1, c2, shortcut=True, g=1, e=0.5, w=None):  # ch_i...
    method call (line 121) | def call(self, inputs):
  class TFConv2d (line 125) | class TFConv2d(keras.layers.Layer):
    method __init__ (line 127) | def __init__(self, c1, c2, k, s=1, g=1, bias=True, w=None):
    method call (line 140) | def call(self, inputs):
  class TFBottleneckCSP (line 144) | class TFBottleneckCSP(keras.layers.Layer):
    method __init__ (line 146) | def __init__(self, c1, c2, n=1, shortcut=True, g=1, e=0.5, w=None):
    method call (line 158) | def call(self, inputs):
  class TFC3 (line 164) | class TFC3(keras.layers.Layer):
    method __init__ (line 166) | def __init__(self, c1, c2, n=1, shortcut=True, g=1, e=0.5, w=None):
    method call (line 175) | def call(self, inputs):
  class TFSPP (line 179) | class TFSPP(keras.layers.Layer):
    method __init__ (line 181) | def __init__(self, c1, c2, k=(5, 9, 13), w=None):
    method call (line 188) | def call(self, inputs):
  class TFSPPF (line 193) | class TFSPPF(keras.layers.Layer):
    method __init__ (line 195) | def __init__(self, c1, c2, k=5, w=None):
    method call (line 202) | def call(self, inputs):
  class TFDetect (line 209) | class TFDetect(keras.layers.Layer):
    method __init__ (line 211) | def __init__(self, nc=80, anchors=(), ch=(), imgsz=(640, 640), w=None)...
    method call (line 228) | def call(self, inputs):
    method _make_grid (line 252) | def _make_grid(nx=20, ny=20):
  class TFUpsample (line 259) | class TFUpsample(keras.layers.Layer):
    method __init__ (line 261) | def __init__(self, size, scale_factor, mode, w=None):  # warning: all ...
    method call (line 270) | def call(self, inputs):
  class TFConcat (line 274) | class TFConcat(keras.layers.Layer):
    method __init__ (line 276) | def __init__(self, dimension=1, w=None):
    method call (line 281) | def call(self, inputs):
  function parse_model (line 285) | def parse_model(d, ch, model, imgsz):  # model_dict, input_channels(3)
  class TFModel (line 337) | class TFModel:
    method __init__ (line 339) | def __init__(self, cfg='yolov5s.yaml', ch=3, nc=None, model=None, imgs...
    method predict (line 355) | def predict(self,
    method _xywh2xyxy (line 400) | def _xywh2xyxy(xywh):
  class AgnosticNMS (line 406) | class AgnosticNMS(keras.layers.Layer):
    method call (line 408) | def call(self, input, topk_all, iou_thres, conf_thres):
    method _nms (line 416) | def _nms(x, topk_all=100, iou_thres=0.45, conf_thres=0.25):  # agnosti...
  function representative_dataset_gen (line 444) | def representative_dataset_gen(dataset, ncalib=100):
  function run (line 455) | def run(
  function parse_opt (line 480) | def parse_opt():
  function main (line 492) | def main(opt):

FILE: RStask/ObjectDetection/models/yolo.py
  class Detect (line 37) | class Detect(nn.Module):
    method __init__ (line 42) | def __init__(self, nc=80, anchors=(), ch=(), inplace=True):  # detecti...
    method forward (line 54) | def forward(self, x):
    method _make_grid (line 78) | def _make_grid(self, nx=20, ny=20, i=0):
  class Model (line 92) | class Model(nn.Module):
    method __init__ (line 94) | def __init__(self, cfg='yolov5s.yaml', ch=3, nc=None, anchors=None):  ...
    method forward (line 132) | def forward(self, x, augment=False, profile=False, visualize=False):
    method _forward_augment (line 137) | def _forward_augment(self, x):
    method _forward_once (line 151) | def _forward_once(self, x, profile=False, visualize=False):
    method _descale_pred (line 164) | def _descale_pred(self, p, flips, scale, img_size):
    method _clip_augmented (line 181) | def _clip_augmented(self, y):
    method _profile_one_layer (line 192) | def _profile_one_layer(self, m, x, dt):
    method _initialize_biases (line 205) | def _initialize_biases(self, cf=None):  # initialize biases into Detec...
    method _print_biases (line 215) | def _print_biases(self):
    method fuse (line 227) | def fuse(self):  # fuse model Conv2d() + BatchNorm2d() layers
    method info (line 236) | def info(self, verbose=False, img_size=640):  # print model information
    method _apply (line 239) | def _apply(self, fn):
  function parse_model (line 251) | def parse_model(d, ch):  # model_dict, input_channels(3)

FILE: RStask/ObjectDetection/utils/__init__.py
  function notebook_init (line 7) | def notebook_init(verbose=True):

FILE: RStask/ObjectDetection/utils/activations.py
  class SiLU (line 11) | class SiLU(nn.Module):
    method forward (line 14) | def forward(x):
  class Hardswish (line 18) | class Hardswish(nn.Module):
    method forward (line 21) | def forward(x):
  class Mish (line 26) | class Mish(nn.Module):
    method forward (line 29) | def forward(x):
  class MemoryEfficientMish (line 33) | class MemoryEfficientMish(nn.Module):
    class F (line 35) | class F(torch.autograd.Function):
      method forward (line 38) | def forward(ctx, x):
      method backward (line 43) | def backward(ctx, grad_output):
    method forward (line 49) | def forward(self, x):
  class FReLU (line 53) | class FReLU(nn.Module):
    method __init__ (line 55) | def __init__(self, c1, k=3):  # ch_in, kernel
    method forward (line 60) | def forward(self, x):
  class AconC (line 64) | class AconC(nn.Module):
    method __init__ (line 70) | def __init__(self, c1):
    method forward (line 76) | def forward(self, x):
  class MetaAconC (line 81) | class MetaAconC(nn.Module):
    method __init__ (line 87) | def __init__(self, c1, k=1, s=1, r=16):  # ch_in, kernel, stride, r
    method forward (line 97) | def forward(self, x):

FILE: RStask/ObjectDetection/utils/augmentations.py
  class Albumentations (line 16) | class Albumentations:
    method __init__ (line 18) | def __init__(self):
    method __call__ (line 40) | def __call__(self, im, labels, p=1.0):
  function augment_hsv (line 47) | def augment_hsv(im, hgain=0.5, sgain=0.5, vgain=0.5):
  function hist_equalize (line 63) | def hist_equalize(im, clahe=True, bgr=False):
  function replicate (line 74) | def replicate(im, labels):
  function letterbox (line 91) | def letterbox(im, new_shape=(640, 640), color=(114, 114, 114), auto=True...
  function random_perspective (line 124) | def random_perspective(im,
  function copy_paste (line 220) | def copy_paste(im, labels, segments, p=0.5):
  function cutout (line 244) | def cutout(im, labels, p=0.5):
  function mixup (line 271) | def mixup(im, labels, im2, labels2):
  function box_candidates (line 279) | def box_candidates(box1, box2, wh_thr=2, ar_thr=100, area_thr=0.1, eps=1...

FILE: RStask/ObjectDetection/utils/autoanchor.py
  function check_anchor_order (line 18) | def check_anchor_order(m):
  function check_anchors (line 28) | def check_anchors(dataset, model, thr=4.0, imgsz=640):
  function kmean_anchors (line 68) | def kmean_anchors(dataset='./data/coco128.yaml', n=9, img_size=640, thr=...

FILE: RStask/ObjectDetection/utils/autobatch.py
  function check_train_batch_size (line 16) | def check_train_batch_size(model, imgsz=640):
  function autobatch (line 22) | def autobatch(model, imgsz=640, fraction=0.9, batch_size=16):

FILE: RStask/ObjectDetection/utils/benchmarks.py
  function run (line 48) | def run(
  function test (line 96) | def test(
  function parse_opt (line 128) | def parse_opt():
  function main (line 143) | def main(opt):

FILE: RStask/ObjectDetection/utils/callbacks.py
  class Callbacks (line 7) | class Callbacks:
    method __init__ (line 12) | def __init__(self):
    method register_action (line 36) | def register_action(self, hook, name='', callback=None):
    method get_registered_actions (line 49) | def get_registered_actions(self, hook=None):
    method run (line 58) | def run(self, hook, *args, **kwargs):

FILE: RStask/ObjectDetection/utils/datasets.py
  function get_hash (line 47) | def get_hash(paths):
  function exif_size (line 55) | def exif_size(img):
  function exif_transpose (line 70) | def exif_transpose(image):
  function create_dataloader (line 96) | def create_dataloader(path,
  class InfiniteDataLoader (line 144) | class InfiniteDataLoader(dataloader.DataLoader):
    method __init__ (line 150) | def __init__(self, *args, **kwargs):
    method __len__ (line 155) | def __len__(self):
    method __iter__ (line 158) | def __iter__(self):
  class _RepeatSampler (line 163) | class _RepeatSampler:
    method __init__ (line 170) | def __init__(self, sampler):
    method __iter__ (line 173) | def __iter__(self):
  class LoadImages (line 178) | class LoadImages:
    method __init__ (line 180) | def __init__(self, path, img_size=640, stride=32, auto=True):
    method __iter__ (line 209) | def __iter__(self):
    method __next__ (line 213) | def __next__(self):
    method new_video (line 251) | def new_video(self, path):
    method __len__ (line 256) | def __len__(self):
  class LoadWebcam (line 260) | class LoadWebcam:  # for inference
    method __init__ (line 262) | def __init__(self, pipe='0', img_size=640, stride=32):
    method __iter__ (line 269) | def __iter__(self):
    method __next__ (line 273) | def __next__(self):
    method __len__ (line 298) | def __len__(self):
  class LoadStreams (line 302) | class LoadStreams:
    method __init__ (line 304) | def __init__(self, sources='streams.txt', img_size=640, stride=32, aut...
    method update (line 347) | def update(self, i, cap, stream):
    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 397) | class LoadImagesAndLabels(Dataset):
    method __init__ (line 401) | def __init__(self,
    method cache_labels (line 535) | def cache_labels(self, path=Path('./labels.cache'), prefix=''):
    method __len__ (line 573) | def __len__(self):
    method __getitem__ (line 582) | def __getitem__(self, index):
    method load_image (line 637) | def load_image(self, i):
    method cache_images_to_disk (line 655) | def cache_images_to_disk(self, i):
    method load_mosaic (line 661) | def load_mosaic(self, index):
    method load_mosaic9 (line 719) | def load_mosaic9(self, index):
    method collate_fn (line 796) | def collate_fn(batch):
    method collate_fn4 (line 803) | def collate_fn4(batch):
  function create_folder (line 830) | def create_folder(path='./new'):
  function flatten_recursive (line 837) | def flatten_recursive(path=DATASETS_DIR / 'coco128'):
  function extract_boxes (line 845) | def extract_boxes(path=DATASETS_DIR / 'coco128'):  # from utils.datasets...
  function autosplit (line 879) | def autosplit(path=DATASETS_DIR / 'coco128/images', weights=(0.9, 0.1, 0...
  function verify_image_label (line 903) | def verify_image_label(args):
  function dataset_stats (line 955) | def dataset_stats(path='coco128.yaml', autodownload=False, verbose=False...

FILE: RStask/ObjectDetection/utils/downloads.py
  function gsutil_getsize (line 19) | def gsutil_getsize(url=''):
  function safe_download (line 25) | def safe_download(file, url, url2=None, min_bytes=1E0, error_msg=''):
  function attempt_download (line 46) | def attempt_download(file, repo='ultralytics/yolov5'):  # from utils.dow...
  function gdrive_download (line 90) | def gdrive_download(id='16TiPfZj7htmTyhntwcZyEEAejOUxuT6m', file='tmp.zi...
  function get_token (line 125) | def get_token(cookie="./cookie"):

FILE: RStask/ObjectDetection/utils/flask_rest_api/restapi.py
  function predict (line 19) | def predict():

FILE: RStask/ObjectDetection/utils/general.py
  function is_kaggle (line 55) | def is_kaggle():
  function is_writeable (line 65) | def is_writeable(dir, test=False):
  function set_logging (line 80) | def set_logging(name=None, verbose=VERBOSE):
  function user_config_dir (line 99) | def user_config_dir(dir='Ultralytics', env_var='YOLOV5_CONFIG_DIR'):
  class Profile (line 115) | class Profile(contextlib.ContextDecorator):
    method __enter__ (line 117) | def __enter__(self):
    method __exit__ (line 120) | def __exit__(self, type, value, traceback):
  class Timeout (line 124) | class Timeout(contextlib.ContextDecorator):
    method __init__ (line 126) | def __init__(self, seconds, *, timeout_msg='', suppress_timeout_errors...
    method _timeout_handler (line 131) | def _timeout_handler(self, signum, frame):
    method __enter__ (line 134) | def __enter__(self):
    method __exit__ (line 139) | def __exit__(self, exc_type, exc_val, exc_tb):
  class WorkingDirectory (line 146) | class WorkingDirectory(contextlib.ContextDecorator):
    method __init__ (line 148) | def __init__(self, new_dir):
    method __enter__ (line 152) | def __enter__(self):
    method __exit__ (line 155) | def __exit__(self, exc_type, exc_val, exc_tb):
  function try_except (line 159) | def try_except(func):
  function methods (line 170) | def methods(instance):
  function print_args (line 175) | def print_args(args: Optional[dict] = None, show_file=True, show_fcn=Fal...
  function init_seeds (line 186) | def init_seeds(seed=0):
  function intersect_dicts (line 196) | def intersect_dicts(da, db, exclude=()):
  function get_latest_run (line 201) | def get_latest_run(search_dir='.'):
  function is_docker (line 207) | def is_docker():
  function is_colab (line 212) | def is_colab():
  function is_pip (line 221) | def is_pip():
  function is_ascii (line 226) | def is_ascii(s=''):
  function is_chinese (line 232) | def is_chinese(s='人工智能'):
  function emojis (line 237) | def emojis(str=''):
  function file_age (line 242) | def file_age(path=__file__):
  function file_update_date (line 248) | def file_update_date(path=__file__):
  function file_size (line 254) | def file_size(path):
  function check_online (line 266) | def check_online():
  function git_describe (line 276) | def git_describe(path=ROOT):  # path must be a directory
  function check_git_status (line 287) | def check_git_status():
  function check_python (line 306) | def check_python(minimum='3.7.0'):
  function check_version (line 311) | def check_version(current='0.0.0', minimum='0.0.0', name='version ', pin...
  function check_requirements (line 324) | def check_requirements(requirements=ROOT / 'requirements.txt', exclude=(...
  function check_img_size (line 360) | def check_img_size(imgsz, s=32, floor=0):
  function check_imshow (line 372) | def check_imshow():
  function check_suffix (line 387) | def check_suffix(file='yolov5s.pt', suffix=('.pt',), msg=''):
  function check_yaml (line 398) | def check_yaml(file, suffix=('.yaml', '.yml')):
  function check_file (line 403) | def check_file(file, suffix=''):
  function check_font (line 428) | def check_font(font=FONT, progress=False):
  function check_dataset (line 438) | def check_dataset(data, autodownload=True):
  function url2file (line 472) | def url2file(url):
  function download (line 479) | def download(url, dir='.', unzip=True, delete=True, curl=False, threads=...
  function make_divisible (line 525) | def make_divisible(x, divisor):
  function clean_str (line 532) | def clean_str(s):
  function one_cycle (line 537) | def one_cycle(y1=0.0, y2=1.0, steps=100):
  function colorstr (line 542) | def colorstr(*input):
  function labels_to_class_weights (line 568) | def labels_to_class_weights(labels, nc=80):
  function labels_to_image_weights (line 587) | def labels_to_image_weights(labels, nc=80, class_weights=np.ones(80)):
  function coco80_to_coco91_class (line 595) | def coco80_to_coco91_class():  # converts 80-index (val2014) to 91-index...
  function xyxy2xywh (line 608) | def xyxy2xywh(x):
  function xywh2xyxy (line 618) | def xywh2xyxy(x):
  function xywhn2xyxy (line 628) | def xywhn2xyxy(x, w=640, h=640, padw=0, padh=0):
  function xyxy2xywhn (line 638) | def xyxy2xywhn(x, w=640, h=640, clip=False, eps=0.0):
  function xyn2xy (line 650) | def xyn2xy(x, w=640, h=640, padw=0, padh=0):
  function segment2box (line 658) | def segment2box(segment, width=640, height=640):
  function segments2boxes (line 666) | def segments2boxes(segments):
  function resample_segments (line 675) | def resample_segments(segments, n=1000):
  function scale_coords (line 684) | def scale_coords(img1_shape, coords, img0_shape, ratio_pad=None):
  function clip_coords (line 700) | def clip_coords(boxes, shape):
  function non_max_suppression (line 712) | def non_max_suppression(prediction,
  function strip_optimizer (line 814) | def strip_optimizer(f='best.pt', s=''):  # from utils.general import *; ...
  function print_mutation (line 830) | def print_mutation(results, hyp, save_dir, bucket, prefix=colorstr('evol...
  function apply_classifier (line 870) | def apply_classifier(x, model, img, im0):
  function increment_path (line 906) | def increment_path(path, exist_ok=False, sep='', mkdir=False):
  function imread (line 925) | def imread(path, flags=cv2.IMREAD_COLOR):
  function imwrite (line 929) | def imwrite(path, im):
  function imshow (line 937) | def imshow(path, im):

FILE: RStask/ObjectDetection/utils/loggers/__init__.py
  class Loggers (line 37) | class Loggers():
    method __init__ (line 39) | def __init__(self, save_dir=None, weights=None, opt=None, hyp=None, lo...
    method on_train_start (line 92) | def on_train_start(self):
    method on_pretrain_routine_end (line 96) | def on_pretrain_routine_end(self):
    method on_train_batch_end (line 102) | def on_train_batch_end(self, ni, model, imgs, targets, paths, plots):
    method on_train_epoch_end (line 117) | def on_train_epoch_end(self, epoch):
    method on_val_image_end (line 122) | def on_val_image_end(self, pred, predn, path, names, im):
    method on_val_end (line 127) | def on_val_end(self):
    method on_fit_epoch_end (line 133) | def on_fit_epoch_end(self, vals, epoch, best_fitness, fi):
    method on_model_save (line 155) | def on_model_save(self, last, epoch, final_epoch, best_fitness, fi):
    method on_train_end (line 161) | def on_train_end(self, last, best, plots, epoch, results):
    method on_params_update (line 183) | def on_params_update(self, params):

FILE: RStask/ObjectDetection/utils/loggers/wandb/log_dataset.py
  function create_dataset_artifact (line 10) | def create_dataset_artifact(opt):

FILE: RStask/ObjectDetection/utils/loggers/wandb/sweep.py
  function sweep (line 17) | def sweep():

FILE: RStask/ObjectDetection/utils/loggers/wandb/wandb_utils.py
  function remove_prefix (line 32) | def remove_prefix(from_string, prefix=WANDB_ARTIFACT_PREFIX):
  function check_wandb_config_file (line 36) | def check_wandb_config_file(data_config_file):
  function check_wandb_dataset (line 43) | def check_wandb_dataset(data_file):
  function get_run_info (line 59) | def get_run_info(run_path):
  function check_wandb_resume (line 68) | def check_wandb_resume(opt):
  function process_wandb_config_ddp_mode (line 82) | def process_wandb_config_ddp_mode(opt):
  class WandbLogger (line 106) | class WandbLogger():
    method __init__ (line 120) | def __init__(self, opt, run_id=None, job_type='Training'):
    method check_and_upload_dataset (line 191) | def check_and_upload_dataset(self, opt):
    method setup_training (line 208) | def setup_training(self, opt):
    method download_dataset_artifact (line 260) | def download_dataset_artifact(self, path, alias):
    method download_model_artifact (line 280) | def download_model_artifact(self, opt):
    method log_model (line 298) | def log_model(self, path, opt, epoch, fitness_score, best_model=False):
    method log_dataset_artifact (line 323) | def log_dataset_artifact(self, data_file, single_cls, project, overwri...
    method map_val_table_path (line 381) | def map_val_table_path(self):
    method create_dataset_table (line 391) | def create_dataset_table(self, dataset: LoadImagesAndLabels, class_to_...
    method log_training_progress (line 437) | def log_training_progress(self, predn, path, names):
    method val_one_image (line 480) | def val_one_image(self, pred, predn, path, names, im):
    method log (line 508) | def log(self, log_dict):
    method end_epoch (line 519) | def end_epoch(self, best_result=False):
    method finish_run (line 554) | def finish_run(self):
  function all_logging_disabled (line 566) | def all_logging_disabled(highest_level=logging.CRITICAL):

FILE: RStask/ObjectDetection/utils/loss.py
  function smooth_BCE (line 13) | def smooth_BCE(eps=0.1):  # https://github.com/ultralytics/yolov3/issues...
  class BCEBlurWithLogitsLoss (line 18) | class BCEBlurWithLogitsLoss(nn.Module):
    method __init__ (line 20) | def __init__(self, alpha=0.05):
    method forward (line 25) | def forward(self, pred, true):
  class FocalLoss (line 35) | class FocalLoss(nn.Module):
    method __init__ (line 37) | def __init__(self, loss_fcn, gamma=1.5, alpha=0.25):
    method forward (line 45) | def forward(self, pred, true):
  class QFocalLoss (line 65) | class QFocalLoss(nn.Module):
    method __init__ (line 67) | def __init__(self, loss_fcn, gamma=1.5, alpha=0.25):
    method forward (line 75) | def forward(self, pred, true):
  class ComputeLoss (line 91) | class ComputeLoss:
    method __init__ (line 95) | def __init__(self, model, autobalance=False):
    method __call__ (line 121) | def __call__(self, p, targets):  # predictions, targets
    method build_targets (line 177) | def build_targets(self, p, targets):

FILE: RStask/ObjectDetection/utils/metrics.py
  function fitness (line 15) | def fitness(x):
  function ap_per_class (line 21) | def ap_per_class(tp, conf, pred_cls, target_cls, plot=False, save_dir='....
  function compute_ap (line 89) | def compute_ap(recall, precision):
  class ConfusionMatrix (line 117) | class ConfusionMatrix:
    method __init__ (line 119) | def __init__(self, nc, conf=0.25, iou_thres=0.45):
    method process_batch (line 125) | def process_batch(self, detections, labels):
    method matrix (line 165) | def matrix(self):
    method tp_fp (line 168) | def tp_fp(self):
    method plot (line 174) | def plot(self, normalize=True, save_dir='', names=()):
    method print (line 204) | def print(self):
  function bbox_iou (line 209) | def bbox_iou(box1, box2, xywh=True, GIoU=False, DIoU=False, CIoU=False, ...
  function box_area (line 250) | def box_area(box):
  function box_iou (line 255) | def box_iou(box1, box2):
  function bbox_ioa (line 276) | def bbox_ioa(box1, box2, eps=1E-7):
  function wh_iou (line 298) | def wh_iou(wh1, wh2):
  function plot_pr_curve (line 309) | def plot_pr_curve(px, py, ap, save_dir='pr_curve.png', names=()):
  function plot_mc_curve (line 330) | def plot_mc_curve(px, py, save_dir='mc_curve.png', names=(), xlabel='Con...

FILE: RStask/ObjectDetection/utils/plots.py
  class Colors (line 31) | class Colors:
    method __init__ (line 33) | def __init__(self):
    method __call__ (line 40) | def __call__(self, i, bgr=False):
    method hex2rgb (line 45) | def hex2rgb(h):  # rgb order (PIL)
  function check_pil_font (line 52) | def check_pil_font(font=FONT, size=10):
  class Annotator (line 68) | class Annotator:
    method __init__ (line 70) | def __init__(self, im, line_width=None, font_size=None, font='Arial.tt...
    method box_label (line 83) | def box_label(self, box, label='', color=(128, 128, 128), txt_color=(2...
    method rectangle (line 114) | def rectangle(self, xy, fill=None, outline=None, width=1):
    method text (line 118) | def text(self, xy, text, txt_color=(255, 255, 255)):
    method result (line 123) | def result(self):
  function feature_visualization (line 128) | def feature_visualization(x, module_type, stage, n=32, save_dir=Path('ru...
  function hist2d (line 156) | def hist2d(x, y, n=100):
  function butter_lowpass_filtfilt (line 165) | def butter_lowpass_filtfilt(data, cutoff=1500, fs=50000, order=5):
  function output_to_target (line 178) | def output_to_target(output):
  function plot_images (line 187) | def plot_images(images, targets, paths=None, fname='images.jpg', names=N...
  function plot_lr_scheduler (line 248) | def plot_lr_scheduler(optimizer, scheduler, epochs=300, save_dir=''):
  function plot_val_txt (line 265) | def plot_val_txt():  # from utils.plots import *; plot_val()
  function plot_targets_txt (line 282) | def plot_targets_txt():  # from utils.plots import *; plot_targets_txt()
  function plot_val_study (line 295) | def plot_val_study(file='', dir='', x=None):  # from utils.plots import ...
  function plot_labels (line 342) | def plot_labels(labels, names=(), save_dir=Path('')):
  function plot_evolve (line 389) | def plot_evolve(evolve_csv='path/to/evolve.csv'):  # from utils.plots im...
  function plot_results (line 416) | def plot_results(file='path/to/results.csv', dir=''):
  function profile_idetection (line 442) | def profile_idetection(start=0, stop=0, labels=(), save_dir=''):
  function save_one_box (line 473) | def save_one_box(xyxy, im, file=Path('im.jpg'), gain=1.02, pad=10, squar...

FILE: RStask/ObjectDetection/utils/torch_utils.py
  function torch_distributed_zero_first (line 33) | def torch_distributed_zero_first(local_rank: int):
  function device_count (line 42) | def device_count():
  function select_device (line 52) | def select_device(device='', batch_size=0, newline=True):
  function time_sync (line 83) | def time_sync():
  function profile (line 90) | def profile(input, ops, n=10, device=None):
  function is_parallel (line 142) | def is_parallel(model):
  function de_parallel (line 147) | def de_parallel(model):
  function initialize_weights (line 152) | def initialize_weights(model):
  function find_modules (line 164) | def find_modules(model, mclass=nn.Conv2d):
  function sparsity (line 169) | def sparsity(model):
  function prune (line 178) | def prune(model, amount=0.3):
  function fuse_conv_and_bn (line 189) | def fuse_conv_and_bn(conv, bn):
  function model_info (line 212) | def model_info(model, verbose=False, img_size=640):
  function scale_img (line 237) | def scale_img(img, ratio=1.0, same_shape=False, gs=32):  # img(16,3,256,...
  function copy_attr (line 250) | def copy_attr(a, b, include=(), exclude=()):
  class EarlyStopping (line 259) | class EarlyStopping:
    method __init__ (line 261) | def __init__(self, patience=30):
    method __call__ (line 267) | def __call__(self, epoch, fitness):
  class ModelEMA (line 282) | class ModelEMA:
    method __init__ (line 288) | def __init__(self, model, decay=0.9999, tau=2000, updates=0):
    method update (line 298) | def update(self, model):
    method update_attr (line 310) | def update_attr(self, model, include=(), exclude=('process_group', 're...

FILE: RStask/SceneClassification/ResNetScene.py
  class ResNetAID (line 4) | class ResNetAID:
    method __init__ (line 5) | def __init__(self, device=None):
    method inference (line 29) | def inference(self, inputs):