SYMBOL INDEX (196 symbols across 18 files)

FILE: corr/datasets/ml_dataset.py
  function read_json (line 21) | def read_json(file_path):
  function ids_to_mat (line 36) | def ids_to_mat(id1, id2):
  function adj_matrix (line 55) | def adj_matrix(topology):
  class MixamoLineArt (line 68) | class MixamoLineArt(data.Dataset):
    method __init__ (line 69) | def __init__(self, root, gap=0, split='train', model=None, action=None...
    method __getitem__ (line 127) | def __getitem__(self, index):
    method __rmul__ (line 272) | def __rmul__(self, v):
    method __len__ (line 278) | def __len__(self):
  function worker_init_fn (line 282) | def worker_init_fn(worker_id):
  function fetch_dataloader (line 285) | def fetch_dataloader(args, type='train',):

FILE: corr/main.py
  function parse_args (line 10) | def parse_args():
  function main (line 23) | def main():

FILE: corr/models/supergluet.py
  function MLP (line 10) | def MLP(channels: list, do_bn=True):
  function normalize_keypoints (line 24) | def normalize_keypoints(kpts, image_shape):
  class ThreeLayerEncoder (line 33) | class ThreeLayerEncoder(nn.Module):
    method __init__ (line 35) | def __init__(self, enc_dim):
    method forward (line 53) | def forward(self, img):
  class VertexDescriptor (line 61) | class VertexDescriptor(nn.Module):
    method __init__ (line 63) | def __init__(self, enc_dim):
    method forward (line 68) | def forward(self, img, vtx):
  class KeypointEncoder (line 76) | class KeypointEncoder(nn.Module):
    method __init__ (line 78) | def __init__(self, feature_dim, layers):
    method forward (line 87) | def forward(self, kpts):
  class TopoEncoder (line 94) | class TopoEncoder(nn.Module):
    method __init__ (line 96) | def __init__(self, feature_dim, layers):
    method forward (line 105) | def forward(self, kpts):
  function attention (line 113) | def attention(query, key, value, mask=None):
  class MultiHeadedAttention (line 125) | class MultiHeadedAttention(nn.Module):
    method __init__ (line 127) | def __init__(self, num_heads: int, d_model: int):
    method forward (line 135) | def forward(self, query, key, value, mask=None):
  class AttentionalPropagation (line 144) | class AttentionalPropagation(nn.Module):
    method __init__ (line 145) | def __init__(self, feature_dim: int, num_heads: int):
    method forward (line 151) | def forward(self, x, source, mask=None):
  class AttentionalGNN (line 156) | class AttentionalGNN(nn.Module):
    method __init__ (line 157) | def __init__(self, feature_dim: int, layer_names: list):
    method forward (line 164) | def forward(self, desc0, desc1, mask00=None, mask11=None, mask01=None,...
  function log_sinkhorn_iterations (line 179) | def log_sinkhorn_iterations(Z, log_mu, log_nu, iters: int):
  function log_optimal_transport (line 188) | def log_optimal_transport(scores, alpha, iters: int, ms=None, ns=None):
  function arange_like (line 229) | def arange_like(x, dim: int):
  class SuperGlueT (line 233) | class SuperGlueT(nn.Module):
    method __init__ (line 235) | def __init__(self, config=None):
    method forward (line 274) | def forward(self, data):

FILE: corr/utils/log.py
  class Logger (line 12) | class Logger:
    method __init__ (line 13) | def __init__(self, args, output_dir):
    method set_progress (line 38) | def set_progress(self, epoch, total):
    method update (line 45) | def update(self, stats):
    method log_eval (line 62) | def log_eval(self, stats, metrics_group=None):
    method __call__ (line 81) | def __call__(self, msg):
  class ProgressHandler (line 85) | class ProgressHandler(logging.Handler):
    method __init__ (line 86) | def __init__(self, level=logging.NOTSET):
    method emit (line 89) | def emit(self, record):

FILE: corr/utils/visualize_vtx_corr.py
  function make_inter_graph (line 6) | def make_inter_graph(v2d1, v2d2, topo1, topo2, match12):
  function make_inter_graph_valid (line 47) | def make_inter_graph_valid(v2d1, v2d2, topo1, topo2, match12):
  function visualize (line 94) | def visualize(dict):

FILE: corr/vtx_matching.py
  class VtxMat (line 36) | class VtxMat():
    method __init__ (line 37) | def __init__(self, args):
    method train (line 43) | def train(self):
    method eval (line 172) | def eval(self):
    method _build (line 269) | def _build(self):
    method _build_model (line 280) | def _build_model(self):
    method _build_train_loader (line 293) | def _build_train_loader(self):
    method _build_test_loader (line 297) | def _build_test_loader(self):
    method _build_optimizer (line 301) | def _build_optimizer(self):
    method _dir_setting (line 314) | def _dir_setting(self):

FILE: datasets/ml_seq.py
  function read_json (line 23) | def read_json(file_path):
  function matched_motion (line 39) | def matched_motion(v2d1, v2d2, match12, motion_pre=None):
  function unmatched_motion (line 47) | def unmatched_motion(topo1, v2d1, motion12, match12):
  function ids_to_mat (line 76) | def ids_to_mat(id1, id2):
  function adj_matrix (line 97) | def adj_matrix(topology):
  class MixamoLineArtMotionSequence (line 110) | class MixamoLineArtMotionSequence(data.Dataset):
    method __init__ (line 111) | def __init__(self, root, gap=0, split='train', model=None, action=None...
    method __getitem__ (line 184) | def __getitem__(self, index):
    method __rmul__ (line 505) | def __rmul__(self, v):
    method __len__ (line 510) | def __len__(self):
  function worker_init_fn (line 514) | def worker_init_fn(worker_id):
  function fetch_dataloader (line 517) | def fetch_dataloader(args, type='train',):

FILE: datasets/vd_seq.py
  function read_json (line 23) | def read_json(file_path):
  class VideoLinSeq (line 42) | class VideoLinSeq(data.Dataset):
    method __init__ (line 43) | def __init__(self, root, split='train'):
    method __getitem__ (line 78) | def __getitem__(self, index):
    method __rmul__ (line 171) | def __rmul__(self, v):
    method __len__ (line 176) | def __len__(self):
  function worker_init_fn (line 180) | def worker_init_fn(worker_id):
  function fetch_videoloader (line 183) | def fetch_videoloader(args, type='train',):

FILE: inbetween.py
  class DraftRefine (line 40) | class DraftRefine():
    method __init__ (line 41) | def __init__(self, args):
    method train (line 47) | def train(self):
    method eval (line 197) | def eval(self):
    method gen (line 325) | def gen(self):
    method _build (line 393) | def _build(self):
    method _build_model (line 406) | def _build_model(self):
    method _build_train_loader (line 419) | def _build_train_loader(self):
    method _build_test_loader (line 423) | def _build_test_loader(self):
    method _build_video_loader (line 426) | def _build_video_loader(self):
    method _build_optimizer (line 430) | def _build_optimizer(self):
    method _dir_setting (line 443) | def _dir_setting(self):

FILE: main.py
  function parse_args (line 10) | def parse_args():
  function main (line 24) | def main():

FILE: models/inbetweener_with_mask2.py
  function MLP (line 9) | def MLP(channels: list, do_bn=True):
  function normalize_keypoints (line 24) | def normalize_keypoints(kpts, image_shape):
  class ThreeLayerEncoder (line 33) | class ThreeLayerEncoder(nn.Module):
    method __init__ (line 35) | def __init__(self, enc_dim):
    method forward (line 53) | def forward(self, img):
  class VertexDescriptor (line 63) | class VertexDescriptor(nn.Module):
    method __init__ (line 65) | def __init__(self, enc_dim):
    method forward (line 72) | def forward(self, img, vtx):
  class KeypointEncoder (line 81) | class KeypointEncoder(nn.Module):
    method __init__ (line 83) | def __init__(self, feature_dim, layers):
    method forward (line 92) | def forward(self, kpts):
  function attention (line 100) | def attention(query, key, value, mask=None):
  class MultiHeadedAttention (line 119) | class MultiHeadedAttention(nn.Module):
    method __init__ (line 121) | def __init__(self, num_heads: int, d_model: int):
    method forward (line 129) | def forward(self, query, key, value, mask=None):
  class AttentionalPropagation (line 138) | class AttentionalPropagation(nn.Module):
    method __init__ (line 139) | def __init__(self, feature_dim: int, num_heads: int):
    method forward (line 145) | def forward(self, x, source, mask=None):
  class AttentionalGNN (line 150) | class AttentionalGNN(nn.Module):
    method __init__ (line 151) | def __init__(self, feature_dim: int, layer_names: list):
    method forward (line 158) | def forward(self, desc0, desc1, mask00=None, mask11=None, mask01=None,...
  function log_sinkhorn_iterations (line 173) | def log_sinkhorn_iterations(Z, log_mu, log_nu, iters: int):
  function log_optimal_transport (line 182) | def log_optimal_transport(scores, alpha, iters: int, ms=None, ns=None):
  function arange_like (line 223) | def arange_like(x, dim: int):
  class SuperGlueM (line 227) | class SuperGlueM(nn.Module):
    method __init__ (line 254) | def __init__(self, config=None):
    method forward (line 294) | def forward(self, data):
  function tensor_erode (line 402) | def tensor_erode(bin_img, ksize=5):
  class InbetweenerM (line 417) | class InbetweenerM(nn.Module):
    method __init__ (line 444) | def __init__(self, config=None):
    method forward (line 458) | def forward(self, data):

FILE: models/inbetweener_with_mask_with_spec.py
  function MLP (line 11) | def MLP(channels: list, do_bn=True):
  function normalize_keypoints (line 26) | def normalize_keypoints(kpts, image_shape):
  class ThreeLayerEncoder (line 35) | class ThreeLayerEncoder(nn.Module):
    method __init__ (line 37) | def __init__(self, enc_dim):
    method forward (line 55) | def forward(self, img):
  class VertexDescriptor (line 65) | class VertexDescriptor(nn.Module):
    method __init__ (line 67) | def __init__(self, enc_dim):
    method forward (line 74) | def forward(self, img, vtx):
  class KeypointEncoder (line 83) | class KeypointEncoder(nn.Module):
    method __init__ (line 85) | def __init__(self, feature_dim, layers):
    method forward (line 94) | def forward(self, kpts):
  class TopoEncoder (line 100) | class TopoEncoder(nn.Module):
    method __init__ (line 102) | def __init__(self, feature_dim, layers):
    method forward (line 111) | def forward(self, kpts):
  function attention (line 117) | def attention(query, key, value, mask=None):
  class MultiHeadedAttention (line 128) | class MultiHeadedAttention(nn.Module):
    method __init__ (line 130) | def __init__(self, num_heads: int, d_model: int):
    method forward (line 138) | def forward(self, query, key, value, mask=None):
  class AttentionalPropagation (line 147) | class AttentionalPropagation(nn.Module):
    method __init__ (line 148) | def __init__(self, feature_dim: int, num_heads: int):
    method forward (line 154) | def forward(self, x, source, mask=None):
  class AttentionalGNN (line 159) | class AttentionalGNN(nn.Module):
    method __init__ (line 160) | def __init__(self, feature_dim: int, layer_names: list):
    method forward (line 167) | def forward(self, desc0, desc1, mask00=None, mask11=None, mask01=None,...
  function log_sinkhorn_iterations (line 182) | def log_sinkhorn_iterations(Z, log_mu, log_nu, iters: int):
  function log_optimal_transport (line 191) | def log_optimal_transport(scores, alpha, iters: int, ms=None, ns=None):
  function arange_like (line 231) | def arange_like(x, dim: int):
  class SuperGlueT (line 235) | class SuperGlueT(nn.Module):
    method __init__ (line 262) | def __init__(self, config=None):
    method forward (line 300) | def forward(self, data):
  function tensor_erode (line 390) | def tensor_erode(bin_img, ksize=5):
  class InbetweenerTM (line 402) | class InbetweenerTM(nn.Module):
    method __init__ (line 418) | def __init__(self, config=None):
    method forward (line 426) | def forward(self, data):

FILE: utils/chamfer_distance.py
  function batch_edt (line 14) | def batch_edt(img, block=1024):
  function batch_chamfer_distance (line 46) | def batch_chamfer_distance(gt, pred, block=1024, return_more=False):
  function batch_chamfer_distance_t (line 51) | def batch_chamfer_distance_t(gt, pred, block=1024, return_more=False):
  function batch_chamfer_distance_p (line 61) | def batch_chamfer_distance_p(gt, pred, block=1024, return_more=False):
  function batch_hausdorff_distance (line 73) | def batch_hausdorff_distance(gt, pred, block=1024, return_more=False):
  class ChamferDistance2dMetric (line 90) | class ChamferDistance2dMetric(torchmetrics.Metric):
    method __init__ (line 92) | def __init__(
    method update (line 104) | def update(self, preds: torch.Tensor, target: torch.Tensor):
    method compute (line 110) | def compute(self):
  class ChamferDistance2dTMetric (line 113) | class ChamferDistance2dTMetric(ChamferDistance2dMetric):
    method update (line 114) | def update(self, preds: torch.Tensor, target: torch.Tensor):
  class ChamferDistance2dPMetric (line 122) | class ChamferDistance2dPMetric(ChamferDistance2dMetric):
    method update (line 123) | def update(self, preds: torch.Tensor, target: torch.Tensor):
  class HausdorffDistance2dMetric (line 132) | class HausdorffDistance2dMetric(torchmetrics.Metric):
    method __init__ (line 133) | def __init__(
    method update (line 148) | def update(self, preds: torch.Tensor, target: torch.Tensor):
    method compute (line 156) | def compute(self):
  function rgb2sketch (line 162) | def rgb2sketch(img, black_threshold):
  function rgb2gray (line 168) | def rgb2gray(rgb):
  function cd_score (line 174) | def cd_score(img1, img2):

FILE: utils/log.py
  class Logger (line 12) | class Logger:
    method __init__ (line 13) | def __init__(self, args, output_dir):
    method set_progress (line 38) | def set_progress(self, epoch, total):
    method update (line 45) | def update(self, stats):
    method log_eval (line 62) | def log_eval(self, stats, metrics_group=None):
    method __call__ (line 81) | def __call__(self, msg):
  class ProgressHandler (line 85) | class ProgressHandler(logging.Handler):
    method __init__ (line 86) | def __init__(self, level=logging.NOTSET):
    method emit (line 89) | def emit(self, record):

FILE: utils/visualize_inbetween.py
  function visualize (line 95) | def visualize(dict):

FILE: utils/visualize_inbetween2.py
  function visualize (line 95) | def visualize(dict):

FILE: utils/visualize_inbetween3.py
  function visualize (line 95) | def visualize(dict):

FILE: utils/visualize_video.py
  function visvid (line 7) | def visvid(dict, inter_frames=1):