SYMBOL INDEX (152 symbols across 15 files) FILE: eval/metrics.py function _prepare_data (line 17) | def _prepare_data(pred: np.ndarray, gt: np.ndarray) -> tuple: function _get_adaptive_threshold (line 25) | def _get_adaptive_threshold(matrix: np.ndarray, max_value: float = 1) ->... class Fmeasure (line 29) | class Fmeasure(object): method __init__ (line 30) | def __init__(self, length, beta: float = 0.3): method step (line 37) | def step(self, pred: np.ndarray, gt: np.ndarray, idx): method cal_adaptive_fm (line 48) | def cal_adaptive_fm(self, pred: np.ndarray, gt: np.ndarray) -> float: method cal_pr (line 61) | def cal_pr(self, pred: np.ndarray, gt: np.ndarray) -> tuple: method get_results (line 79) | def get_results(self): class MAE (line 89) | class MAE(object): method __init__ (line 90) | def __init__(self, length): method step (line 93) | def step(self, pred: np.ndarray, gt: np.ndarray, idx): method cal_mae (line 99) | def cal_mae(self, pred: np.ndarray, gt: np.ndarray) -> float: method get_results (line 103) | def get_results(self): class Smeasure (line 108) | class Smeasure(object): method __init__ (line 109) | def __init__(self, length, alpha: float = 0.5): method step (line 113) | def step(self, pred: np.ndarray, gt: np.ndarray, idx): method cal_sm (line 119) | def cal_sm(self, pred: np.ndarray, gt: np.ndarray) -> float: method object (line 130) | def object(self, pred: np.ndarray, gt: np.ndarray) -> float: method s_object (line 137) | def s_object(self, pred: np.ndarray, gt: np.ndarray) -> float: method region (line 143) | def region(self, pred: np.ndarray, gt: np.ndarray) -> float: method centroid (line 156) | def centroid(self, matrix: np.ndarray) -> tuple: method divide_with_xy (line 174) | def divide_with_xy(self, pred: np.ndarray, gt: np.ndarray, x, y) -> dict: method ssim (line 197) | def ssim(self, pred: np.ndarray, gt: np.ndarray) -> float: method get_results (line 219) | def get_results(self): class Emeasure (line 224) | class Emeasure(object): method __init__ (line 225) | def __init__(self, length): method step (line 229) | def step(self, pred: np.ndarray, gt: np.ndarray, idx): method cal_adaptive_em (line 239) | def cal_adaptive_em(self, pred: np.ndarray, gt: np.ndarray) -> float: method cal_changeable_em (line 244) | def cal_changeable_em(self, pred: np.ndarray, gt: np.ndarray) -> np.nd... method cal_em_with_threshold (line 248) | def cal_em_with_threshold(self, pred: np.ndarray, gt: np.ndarray, thre... method cal_em_with_cumsumhistogram (line 277) | def cal_em_with_cumsumhistogram(self, pred: np.ndarray, gt: np.ndarray... method generate_parts_numel_combinations (line 309) | def generate_parts_numel_combinations(self, fg_fg_numel, fg_bg_numel, ... method get_results (line 331) | def get_results(self): class WeightedFmeasure (line 337) | class WeightedFmeasure(object): method __init__ (line 338) | def __init__(self, length, beta: float = 1): method step (line 342) | def step(self, pred: np.ndarray, gt: np.ndarray, idx): method cal_wfm (line 351) | def cal_wfm(self, pred: np.ndarray, gt: np.ndarray) -> float: method matlab_style_gauss2D (line 385) | def matlab_style_gauss2D(self, shape: tuple = (7, 7), sigma: int = 5) ... method get_results (line 399) | def get_results(self): class Medical (line 404) | class Medical(object): method __init__ (line 405) | def __init__(self, length): method Fmeasure_calu (line 413) | def Fmeasure_calu(self, pred, gt, threshold): method step (line 446) | def step(self, pred, gt, idx): method get_results (line 463) | def get_results(self): FILE: eval/vps_evaluator.py function get_competitors (line 15) | def get_competitors(root): function evaluator (line 20) | def evaluator(gt_pth_lst, pred_pth_lst, metrics): function eval_engine_vps (line 61) | def eval_engine_vps(opt, txt_save_path): FILE: lib/dataloader/dataloader.py class VideoDataset (line 10) | class VideoDataset(Dataset): method __init__ (line 11) | def __init__(self, video_dataset, transform=None, time_interval=1): method __getitem__ (line 50) | def __getitem__(self, idx): method __len__ (line 74) | def __len__(self): function get_video_dataset (line 78) | def get_video_dataset(): FILE: lib/dataloader/preprocess.py class Compose_imglabel (line 7) | class Compose_imglabel(object): method __init__ (line 8) | def __init__(self, transforms): method __call__ (line 11) | def __call__(self, img, label): class Random_crop_Resize_Video (line 17) | class Random_crop_Resize_Video(object): method _randomCrop (line 18) | def _randomCrop(self, img, label, x, y): method __init__ (line 26) | def __init__(self, crop_size): method __call__ (line 29) | def __call__(self, imgs, labels): class Random_horizontal_flip_video (line 40) | class Random_horizontal_flip_video(object): method _horizontal_flip (line 41) | def _horizontal_flip(self, img, label): method __init__ (line 44) | def __init__(self, prob): method __call__ (line 51) | def __call__(self, imgs, labels): class Resize_video (line 70) | class Resize_video(object): method __init__ (line 71) | def __init__(self, height, width): method __call__ (line 75) | def __call__(self, imgs, labels): class Normalize_video (line 84) | class Normalize_video(object): method __init__ (line 85) | def __init__(self, mean, std): method __call__ (line 88) | def __call__(self, imgs, labels): class toTensor_video (line 99) | class toTensor_video(object): method __init__ (line 100) | def __init__(self): method __call__ (line 103) | def __call__(self, imgs, labels): FILE: lib/module/LightRFB.py class h_sigmoid (line 5) | class h_sigmoid(nn.Module): method __init__ (line 6) | def __init__(self, inplace=True): method forward (line 10) | def forward(self, x): class SELayer (line 14) | class SELayer(nn.Module): method __init__ (line 15) | def __init__(self, channel, reduction=4): method forward (line 25) | def forward(self, x): class BasicConv (line 32) | class BasicConv(nn.Module): method __init__ (line 34) | def __init__(self, in_planes, out_planes, kernel_size, stride=1, paddi... method forward (line 43) | def forward(self, x): class LightRFB (line 52) | class LightRFB(nn.Module): method __init__ (line 53) | def __init__(self, channels_in=1024, channels_mid=128, channels_out=32): method forward (line 92) | def forward(self, x): FILE: lib/module/PNS/PNS_Module/reference.cpp function sa_weight_forward_Ref (line 7) | void sa_weight_forward_Ref(const torch::Tensor& query,const torch::Tenso... function sa_weight_backward_query_Ref (line 37) | void sa_weight_backward_query_Ref(const torch::Tensor& dweight,const tor... function sa_weight_backward_key_Ref (line 68) | void sa_weight_backward_key_Ref(const torch::Tensor& dweight,const torch... function sa_map_forward_Ref (line 95) | void sa_map_forward_Ref(const torch::Tensor& weight,const torch::Tensor&... function sa_map_backward_weight_Ref (line 125) | void sa_map_backward_weight_Ref(const torch::Tensor& dout,const torch::T... function sa_map_backward_proj_Ref (line 156) | void sa_map_backward_proj_Ref(const torch::Tensor& dout,const torch::Ten... FILE: lib/module/PNS/PNS_Module/sa_ext.cpp function get_sizes (line 7) | void get_sizes(const torch::Tensor& t,int *B,int *T,int *C,int *H,int *W){ function sa_weight_forward (line 26) | void sa_weight_forward(const torch::Tensor& query,const torch::Tensor& k... function sa_map_forward (line 38) | void sa_map_forward(const torch::Tensor& weight,const torch::Tensor& pro... function sa_weight_backward (line 50) | void sa_weight_backward(const torch::Tensor& dw,const torch::Tensor& que... function sa_map_backward (line 62) | void sa_map_backward(const torch::Tensor& dout,const torch::Tensor& weig... function sa_weight_forward_ref (line 74) | void sa_weight_forward_ref(const torch::Tensor& query,const torch::Tenso... function sa_weight_backward_ref (line 80) | void sa_weight_backward_ref(const torch::Tensor& dw,const torch::Tensor&... function sa_map_forward_ref (line 87) | void sa_map_forward_ref(const torch::Tensor& weight,const torch::Tensor&... function sa_map_backward_ref (line 93) | void sa_map_backward_ref(const torch::Tensor& dout,const torch::Tensor& ... function PYBIND11_MODULE (line 101) | PYBIND11_MODULE(TORCH_EXTENSION_NAME, m) { FILE: lib/module/PNS/PNS_Module/timer.h function Start (line 23) | void Start() function Stop (line 28) | void Stop() function Elapsed (line 33) | float Elapsed() FILE: lib/module/PNSPlusModule.py function _check_contiguous (line 13) | def _check_contiguous(*args): class Relevance_Measuring (line 18) | class Relevance_Measuring(autograd.Function): method forward (line 20) | def forward(ctx, query, key, radius=1, dilation=1): method backward (line 36) | def backward(ctx, dw): class Spatial_Temporal_Aggregation (line 45) | class Spatial_Temporal_Aggregation(autograd.Function): method forward (line 47) | def forward(ctx, weight, proj, radius=1, dilation=1): method backward (line 58) | def backward(ctx, dout): class NS_Block (line 71) | class NS_Block(nn.Module): method __init__ (line 72) | def __init__(self, channels_in=32, n_head=4, d_k=8, d_v=8, radius=[3, ... method forward (line 86) | def forward(self, first, x): FILE: lib/module/PNSPlusNetwork.py class conbine_feature (line 12) | class conbine_feature(nn.Module): method __init__ (line 13) | def __init__(self): method forward (line 21) | def forward(self, low_fea, high_fea): class DilatedParallelConvBlockD2 (line 28) | class DilatedParallelConvBlockD2(nn.Module): method __init__ (line 29) | def __init__(self, nIn, nOut, add=False): method forward (line 41) | def forward(self, input): class PNSNet (line 55) | class PNSNet(nn.Module): method __init__ (line 56) | def __init__(self): method forward (line 68) | def forward(self, x): FILE: lib/module/Res2Net_v1b.py class Bottle2neck (line 15) | class Bottle2neck(nn.Module): method __init__ (line 18) | def __init__(self, inplanes, planes, stride=1, downsample=None, baseWi... method forward (line 58) | def forward(self, x): class Res2Net (line 94) | class Res2Net(nn.Module): method __init__ (line 96) | def __init__(self, block, layers, baseWidth=26, scale=4, num_classes=1... method _make_layer (line 127) | def _make_layer(self, block, planes, blocks, stride=1): method forward (line 147) | def forward(self, x): function res2net50_v1b (line 165) | def res2net50_v1b(pretrained=False, **kwargs): function res2net101_v1b (line 177) | def res2net101_v1b(pretrained=False, **kwargs): function res2net50_v1b_26w_4s (line 188) | def res2net50_v1b_26w_4s(pretrained=False, **kwargs): function res2net101_v1b_26w_4s (line 202) | def res2net101_v1b_26w_4s(pretrained=False, **kwargs): function res2net152_v1b_26w_4s (line 213) | def res2net152_v1b_26w_4s(pretrained=False, **kwargs): FILE: lib/utils/utils.py function clip_gradient (line 1) | def clip_gradient(optimizer, grad_clip): function adjust_lr (line 14) | def adjust_lr(optimizer, init_lr, epoch, decay_rate=0.1, decay_epoch=30): FILE: scripts/eval_eff.py function computeTime (line 11) | def computeTime(model, inputs, device='cuda'): FILE: scripts/my_test.py function safe_save (line 14) | def safe_save(img, save_path): class Normalize (line 19) | class Normalize(object): method __init__ (line 20) | def __init__(self, mean, std): method __call__ (line 23) | def __call__(self, img): class Test_Dataset (line 31) | class Test_Dataset(Dataset): method __init__ (line 32) | def __init__(self, root, testset): method __getitem__ (line 76) | def __getitem__(self, idx): method __len__ (line 91) | def __len__(self): class AutoTest (line 95) | class AutoTest: method __init__ (line 96) | def __init__(self, test_dataset, data_root, model_path): method test (line 114) | def test(self): FILE: scripts/my_train.py class CrossEntropyLoss (line 17) | class CrossEntropyLoss(nn.Module): method __init__ (line 18) | def __init__(self): method forward (line 21) | def forward(self, *inputs): function train (line 27) | def train(train_loader, model, optimizer, epoch, save_path, loss_func):