SYMBOL INDEX (236 symbols across 23 files)

FILE: dataset/augmentation.py
  class MotionAugmentation (line 8) | class MotionAugmentation:
    method __init__ (line 9) | def __init__(self,
    method __call__ (line 35) | def __call__(self, fgrs, phas, bgrs):
    method _static_affine (line 106) | def _static_affine(self, *imgs, scale_ranges):
    method _motion_affine (line 113) | def _motion_affine(self, *imgs):
    method _motion_noise (line 133) | def _motion_noise(self, *imgs):
    method _motion_color_jitter (line 145) | def _motion_color_jitter(self, *imgs):
    method _motion_blur (line 160) | def _motion_blur(self, *imgs):
    method _motion_pause (line 178) | def _motion_pause(self, *imgs):
  function lerp (line 187) | def lerp(a, b, percentage):
  function random_easing_fn (line 191) | def random_easing_fn():
  class Step (line 229) | class Step: # Custom easing function for sudden change.
    method __call__ (line 230) | def __call__(self, value):
  class TrainFrameSampler (line 237) | class TrainFrameSampler:
    method __init__ (line 238) | def __init__(self, speed=[0.5, 1, 2, 3, 4, 5]):
    method __call__ (line 241) | def __call__(self, seq_length):
  class ValidFrameSampler (line 258) | class ValidFrameSampler:
    method __call__ (line 259) | def __call__(self, seq_length):

FILE: dataset/coco.py
  class CocoPanopticDataset (line 12) | class CocoPanopticDataset(Dataset):
    method __init__ (line 13) | def __init__(self,
    method __len__ (line 25) | def __len__(self):
    method __getitem__ (line 28) | def __getitem__(self, idx):
    method _load_img (line 38) | def _load_img(self, data):
    method _load_seg (line 42) | def _load_seg(self, data):
  class CocoPanopticTrainAugmentation (line 57) | class CocoPanopticTrainAugmentation:
    method __init__ (line 58) | def __init__(self, size):
    method __call__ (line 62) | def __call__(self, img, seg):
  class CocoPanopticValidAugmentation (line 89) | class CocoPanopticValidAugmentation:
    method __init__ (line 90) | def __init__(self, size):
    method __call__ (line 93) | def __call__(self, img, seg):

FILE: dataset/imagematte.py
  class ImageMatteDataset (line 9) | class ImageMatteDataset(Dataset):
    method __init__ (line 10) | def __init__(self,
    method __len__ (line 31) | def __len__(self):
    method __getitem__ (line 34) | def __getitem__(self, idx):
    method _get_imagematte (line 47) | def _get_imagematte(self, idx):
    method _get_random_image_background (line 56) | def _get_random_image_background(self):
    method _get_random_video_background (line 62) | def _get_random_video_background(self):
    method _downsample_if_needed (line 76) | def _downsample_if_needed(self, img):
  class ImageMatteAugmentation (line 85) | class ImageMatteAugmentation(MotionAugmentation):
    method __init__ (line 86) | def __init__(self, size):

FILE: dataset/spd.py
  class SuperviselyPersonDataset (line 6) | class SuperviselyPersonDataset(Dataset):
    method __init__ (line 7) | def __init__(self, imgdir, segdir, transform=None):
    method __len__ (line 15) | def __len__(self):
    method __getitem__ (line 18) | def __getitem__(self, idx):

FILE: dataset/videomatte.py
  class VideoMatteDataset (line 9) | class VideoMatteDataset(Dataset):
    method __init__ (line 10) | def __init__(self,
    method __len__ (line 37) | def __len__(self):
    method __getitem__ (line 40) | def __getitem__(self, idx):
    method _get_random_image_background (line 53) | def _get_random_image_background(self):
    method _get_random_video_background (line 59) | def _get_random_video_background(self):
    method _get_videomatte (line 73) | def _get_videomatte(self, idx):
    method _downsample_if_needed (line 88) | def _downsample_if_needed(self, img):
  class VideoMatteTrainAugmentation (line 97) | class VideoMatteTrainAugmentation(MotionAugmentation):
    method __init__ (line 98) | def __init__(self, size):
  class VideoMatteValidAugmentation (line 112) | class VideoMatteValidAugmentation(MotionAugmentation):
    method __init__ (line 113) | def __init__(self, size):

FILE: dataset/youtubevis.py
  class YouTubeVISDataset (line 12) | class YouTubeVISDataset(Dataset):
    method __init__ (line 13) | def __init__(self, videodir, annfile, size, seq_length, seq_sampler, t...
    method __len__ (line 44) | def __len__(self):
    method __getitem__ (line 47) | def __getitem__(self, idx):
    method _decode_rle (line 73) | def _decode_rle(self, rle):
    method _downsample_if_needed (line 85) | def _downsample_if_needed(self, img, resample):
  class YouTubeVISAugmentation (line 95) | class YouTubeVISAugmentation:
    method __init__ (line 96) | def __init__(self, size):
    method __call__ (line 100) | def __call__(self, imgs, segs):

FILE: evaluation/evaluate_hr.py
  class Evaluator (line 47) | class Evaluator:
    method __init__ (line 48) | def __init__(self):
    method parse_args (line 54) | def parse_args(self):
    method init_metrics (line 63) | def init_metrics(self):
    method evaluate (line 69) | def evaluate(self):
    method write_excel (line 83) | def write_excel(self):
    method evaluate_worker (line 109) | def evaluate_worker(self, dataset, clip, position):
  class MetricMAD (line 153) | class MetricMAD:
    method __call__ (line 154) | def __call__(self, pred, true):
  class MetricMSE (line 158) | class MetricMSE:
    method __call__ (line 159) | def __call__(self, pred, true):
  class MetricGRAD (line 163) | class MetricGRAD:
    method __init__ (line 164) | def __init__(self, sigma=1.4):
    method __call__ (line 169) | def __call__(self, pred, true):
    method gauss_gradient (line 174) | def gauss_gradient(self, img):
    method gauss_filter (line 180) | def gauss_filter(sigma, epsilon=1e-2):
    method gaussian (line 199) | def gaussian(x, sigma):
    method dgaussian (line 203) | def dgaussian(x, sigma):
  class MetricDTSSD (line 207) | class MetricDTSSD:
    method __call__ (line 208) | def __call__(self, pred_t, pred_tm1, true_t, true_tm1):

FILE: evaluation/evaluate_lr.py
  class Evaluator (line 45) | class Evaluator:
    method __init__ (line 46) | def __init__(self):
    method parse_args (line 52) | def parse_args(self):
    method init_metrics (line 61) | def init_metrics(self):
    method evaluate (line 68) | def evaluate(self):
    method write_excel (line 82) | def write_excel(self):
    method evaluate_worker (line 108) | def evaluate_worker(self, dataset, clip, position):
  class MetricMAD (line 148) | class MetricMAD:
    method __call__ (line 149) | def __call__(self, pred, true):
  class MetricMSE (line 153) | class MetricMSE:
    method __call__ (line 154) | def __call__(self, pred, true):
  class MetricGRAD (line 158) | class MetricGRAD:
    method __init__ (line 159) | def __init__(self, sigma=1.4):
    method __call__ (line 162) | def __call__(self, pred, true):
    method gauss_gradient (line 174) | def gauss_gradient(self, img):
    method gauss_filter (line 180) | def gauss_filter(sigma, epsilon=1e-2):
    method gaussian (line 199) | def gaussian(x, sigma):
    method dgaussian (line 203) | def dgaussian(x, sigma):
  class MetricCONN (line 207) | class MetricCONN:
    method __call__ (line 208) | def __call__(self, pred, true):
  class MetricDTSSD (line 244) | class MetricDTSSD:
    method __call__ (line 245) | def __call__(self, pred_t, pred_tm1, true_t, true_tm1):

FILE: evaluation/generate_imagematte_with_background_image.py
  function lerp (line 47) | def lerp(a, b, percentage):
  function motion_affine (line 50) | def motion_affine(*imgs):
  function process (line 72) | def process(i):

FILE: evaluation/generate_imagematte_with_background_video.py
  function lerp (line 95) | def lerp(a, b, percentage):
  function motion_affine (line 98) | def motion_affine(*imgs):
  function process (line 119) | def process(i):

FILE: hubconf.py
  function mobilenetv3 (line 17) | def mobilenetv3(pretrained: bool = True, progress: bool = True):
  function resnet50 (line 25) | def resnet50(pretrained: bool = True, progress: bool = True):
  function converter (line 33) | def converter():

FILE: inference.py
  function convert_video (line 24) | def convert_video(model,
  function auto_downsample_ratio (line 153) | def auto_downsample_ratio(h, w):
  class Converter (line 160) | class Converter:
    method __init__ (line 161) | def __init__(self, variant: str, checkpoint: str, device: str):
    method convert (line 168) | def convert(self, *args, **kwargs):

FILE: inference_speed_test.py
  class InferenceSpeedTest (line 17) | class InferenceSpeedTest:
    method __init__ (line 18) | def __init__(self):
    method parse_args (line 23) | def parse_args(self):
    method init_model (line 32) | def init_model(self):
    method loop (line 40) | def loop(self):

FILE: inference_utils.py
  class VideoReader (line 10) | class VideoReader(Dataset):
    method __init__ (line 11) | def __init__(self, path, transform=None):
    method frame_rate (line 17) | def frame_rate(self):
    method __len__ (line 20) | def __len__(self):
    method __getitem__ (line 23) | def __getitem__(self, idx):
  class VideoWriter (line 31) | class VideoWriter:
    method __init__ (line 32) | def __init__(self, path, frame_rate, bit_rate=1000000):
    method write (line 38) | def write(self, frames):
    method close (line 50) | def close(self):
  class ImageSequenceReader (line 55) | class ImageSequenceReader(Dataset):
    method __init__ (line 56) | def __init__(self, path, transform=None):
    method __len__ (line 61) | def __len__(self):
    method __getitem__ (line 64) | def __getitem__(self, idx):
  class ImageSequenceWriter (line 72) | class ImageSequenceWriter:
    method __init__ (line 73) | def __init__(self, path, extension='jpg'):
    method write (line 79) | def write(self, frames):
    method close (line 86) | def close(self):

FILE: model/decoder.py
  class RecurrentDecoder (line 7) | class RecurrentDecoder(nn.Module):
    method __init__ (line 8) | def __init__(self, feature_channels, decoder_channels):
    method forward (line 17) | def forward(self,
  class AvgPool (line 30) | class AvgPool(nn.Module):
    method __init__ (line 31) | def __init__(self):
    method forward_single_frame (line 35) | def forward_single_frame(self, s0):
    method forward_time_series (line 41) | def forward_time_series(self, s0):
    method forward (line 50) | def forward(self, s0):
  class BottleneckBlock (line 57) | class BottleneckBlock(nn.Module):
    method __init__ (line 58) | def __init__(self, channels):
    method forward (line 63) | def forward(self, x, r: Optional[Tensor]):
  class UpsamplingBlock (line 70) | class UpsamplingBlock(nn.Module):
    method __init__ (line 71) | def __init__(self, in_channels, skip_channels, src_channels, out_chann...
    method forward_single_frame (line 82) | def forward_single_frame(self, x, f, s, r: Optional[Tensor]):
    method forward_time_series (line 92) | def forward_time_series(self, x, f, s, r: Optional[Tensor]):
    method forward (line 107) | def forward(self, x, f, s, r: Optional[Tensor]):
  class OutputBlock (line 114) | class OutputBlock(nn.Module):
    method __init__ (line 115) | def __init__(self, in_channels, src_channels, out_channels):
    method forward_single_frame (line 127) | def forward_single_frame(self, x, s):
    method forward_time_series (line 134) | def forward_time_series(self, x, s):
    method forward (line 145) | def forward(self, x, s):
  class ConvGRU (line 152) | class ConvGRU(nn.Module):
    method __init__ (line 153) | def __init__(self,
    method forward_single_frame (line 168) | def forward_single_frame(self, x, h):
    method forward_time_series (line 174) | def forward_time_series(self, x, h):
    method forward (line 182) | def forward(self, x, h: Optional[Tensor]):
  class Projection (line 193) | class Projection(nn.Module):
    method __init__ (line 194) | def __init__(self, in_channels, out_channels):
    method forward_single_frame (line 198) | def forward_single_frame(self, x):
    method forward_time_series (line 201) | def forward_time_series(self, x):
    method forward (line 205) | def forward(self, x):

FILE: model/deep_guided_filter.py
  class DeepGuidedFilterRefiner (line 9) | class DeepGuidedFilterRefiner(nn.Module):
    method __init__ (line 10) | def __init__(self, hid_channels=16):
    method forward_single_frame (line 24) | def forward_single_frame(self, fine_src, base_src, base_fgr, base_pha,...
    method forward_time_series (line 45) | def forward_time_series(self, fine_src, base_src, base_fgr, base_pha, ...
    method forward (line 57) | def forward(self, fine_src, base_src, base_fgr, base_pha, base_hid):

FILE: model/fast_guided_filter.py
  class FastGuidedFilterRefiner (line 9) | class FastGuidedFilterRefiner(nn.Module):
    method __init__ (line 10) | def __init__(self, *args, **kwargs):
    method forward_single_frame (line 14) | def forward_single_frame(self, fine_src, base_src, base_fgr, base_pha):
    method forward_time_series (line 25) | def forward_time_series(self, fine_src, base_src, base_fgr, base_pha):
    method forward (line 36) | def forward(self, fine_src, base_src, base_fgr, base_pha, base_hid):
  class FastGuidedFilter (line 43) | class FastGuidedFilter(nn.Module):
    method __init__ (line 44) | def __init__(self, r: int, eps: float = 1e-5):
    method forward (line 50) | def forward(self, lr_x, lr_y, hr_x):
  class BoxFilter (line 62) | class BoxFilter(nn.Module):
    method __init__ (line 63) | def __init__(self, r):
    method forward (line 67) | def forward(self, x):

FILE: model/lraspp.py
  class LRASPP (line 3) | class LRASPP(nn.Module):
    method __init__ (line 4) | def __init__(self, in_channels, out_channels):
    method forward_single_frame (line 17) | def forward_single_frame(self, x):
    method forward_time_series (line 20) | def forward_time_series(self, x):
    method forward (line 25) | def forward(self, x):

FILE: model/mobilenetv3.py
  class MobileNetV3LargeEncoder (line 6) | class MobileNetV3LargeEncoder(MobileNetV3):
    method __init__ (line 7) | def __init__(self, pretrained: bool = False):
    method forward_single_frame (line 36) | def forward_single_frame(self, x):
    method forward_time_series (line 62) | def forward_time_series(self, x):
    method forward (line 68) | def forward(self, x):

FILE: model/model.py
  class MattingNetwork (line 14) | class MattingNetwork(nn.Module):
    method __init__ (line 15) | def __init__(self,
    method forward (line 40) | def forward(self,
    method _interpolate (line 70) | def _interpolate(self, x: Tensor, scale_factor: float):

FILE: model/resnet.py
  class ResNet50Encoder (line 5) | class ResNet50Encoder(ResNet):
    method __init__ (line 6) | def __init__(self, pretrained: bool = False):
    method forward_single_frame (line 20) | def forward_single_frame(self, x):
    method forward_time_series (line 35) | def forward_time_series(self, x):
    method forward (line 41) | def forward(self, x):

FILE: train.py
  class Trainer (line 126) | class Trainer:
    method __init__ (line 127) | def __init__(self, rank, world_size):
    method parse_args (line 136) | def parse_args(self):
    method init_distributed (line 175) | def init_distributed(self, rank, world_size):
    method init_datasets (line 183) | def init_datasets(self):
    method init_model (line 317) | def init_model(self):
    method init_writer (line 338) | def init_writer(self):
    method train (line 343) | def train(self):
    method train_mat (line 374) | def train_mat(self, true_fgr, true_pha, true_bgr, downsample_ratio, tag):
    method train_seg (line 401) | def train_seg(self, true_img, true_seg, log_label):
    method load_next_mat_hr_sample (line 424) | def load_next_mat_hr_sample(self):
    method load_next_seg_video_sample (line 433) | def load_next_seg_video_sample(self):
    method load_next_seg_image_sample (line 442) | def load_next_seg_image_sample(self):
    method validate (line 451) | def validate(self):
    method random_crop (line 473) | def random_crop(self, *imgs):
    method save (line 487) | def save(self):
    method cleanup (line 494) | def cleanup(self):
    method log (line 497) | def log(self, msg):

FILE: train_loss.py
  function matting_loss (line 7) | def matting_loss(pred_fgr, pred_pha, true_fgr, true_pha):
  function segmentation_loss (line 33) | def segmentation_loss(pred_seg, true_seg):
  function laplacian_loss (line 45) | def laplacian_loss(pred, true, max_levels=5):
  function laplacian_pyramid (line 54) | def laplacian_pyramid(img, kernel, max_levels):
  function gauss_kernel (line 66) | def gauss_kernel(device='cpu', dtype=torch.float32):
  function gauss_convolution (line 76) | def gauss_convolution(img, kernel):
  function downsample (line 84) | def downsample(img, kernel):
  function upsample (line 89) | def upsample(img, kernel):
  function crop_to_even_size (line 96) | def crop_to_even_size(img):