SYMBOL INDEX (136 symbols across 18 files)

FILE: config.py
  class DefaultConfig (line 6) | class DefaultConfig(object):
    method _parse (line 46) | def _parse(self, kwargs):
    method _state_dict (line 64) | def _state_dict(self):

FILE: datasets/data_loader.py
  function read_image (line 7) | def read_image(img_path):
  class ImageData (line 20) | class ImageData(Dataset):
    method __init__ (line 21) | def __init__(self, dataset, transform):
    method __getitem__ (line 25) | def __getitem__(self, item):
    method __len__ (line 32) | def __len__(self):

FILE: datasets/data_manager.py
  class Market1501 (line 11) | class Market1501(object):
    method __init__ (line 22) | def __init__(self, dataset_dir, mode, root='data'):
    method _check_before_run (line 57) | def _check_before_run(self):
    method _process_dir (line 68) | def _process_dir(self, dir_path, relabel=False):
  function init_dataset (line 96) | def init_dataset(name, mode):

FILE: datasets/samplers.py
  class RandomIdentitySampler (line 11) | class RandomIdentitySampler(Sampler):
    method __init__ (line 12) | def __init__(self, data_source, num_instances=4):
    method __iter__ (line 21) | def __iter__(self):
    method __len__ (line 32) | def __len__(self):

FILE: main_reid.py
  function train (line 28) | def train(**kwargs):
  function test (line 187) | def test(model, queryloader):

FILE: models/networks.py
  function weights_init_kaiming (line 20) | def weights_init_kaiming(m):
  function weights_init_classifier (line 35) | def weights_init_classifier(m):
  class SELayer (line 42) | class SELayer(nn.Module):
    method __init__ (line 43) | def __init__(self, channel, reduction=16):
    method forward (line 53) | def forward(self, x):
  class BatchDrop (line 59) | class BatchDrop(nn.Module):
    method __init__ (line 60) | def __init__(self, h_ratio, w_ratio):
    method forward (line 65) | def forward(self, x):
  class BatchCrop (line 77) | class BatchCrop(nn.Module):
    method __init__ (line 78) | def __init__(self, ratio):
    method forward (line 82) | def forward(self, x):
  class ResNetBuilder (line 96) | class ResNetBuilder(nn.Module):
    method __init__ (line 99) | def __init__(self, num_classes=None, last_stride=1, pretrained=False):
    method forward (line 118) | def forward(self, x):
    method get_optim_policy (line 129) | def get_optim_policy(self):
  class BFE (line 142) | class BFE(nn.Module):
    method __init__ (line 143) | def __init__(self, num_classes, width_ratio=0.5, height_ratio=0.5):
    method forward (line 190) | def forward(self, x):
    method get_optim_policy (line 226) | def get_optim_policy(self):
  class Resnet (line 238) | class Resnet(nn.Module):
    method __init__ (line 239) | def __init__(self, num_classes, resnet=None):
    method forward (line 256) | def forward(self, x):
    method get_optim_policy (line 270) | def get_optim_policy(self):
  class IDE (line 273) | class IDE(nn.Module):
    method __init__ (line 274) | def __init__(self, num_classes, resnet=None):
    method forward (line 290) | def forward(self, x):
    method get_optim_policy (line 303) | def get_optim_policy(self):

FILE: models/resnet.py
  class Bottleneck (line 9) | class Bottleneck(nn.Module):
    method __init__ (line 12) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 25) | def forward(self, x):
  class CBAM_Module (line 47) | class CBAM_Module(nn.Module):
    method __init__ (line 49) | def __init__(self, channels, reduction):
    method forward (line 62) | def forward(self, x):
  class CBAMBottleneck (line 86) | class CBAMBottleneck(nn.Module):
    method __init__ (line 89) | def __init__(self, inplanes, planes, stride=1, downsample=None):
    method forward (line 103) | def forward(self, x):
  function cbam_resnet50 (line 125) | def cbam_resnet50():
  class ResNet (line 129) | class ResNet(nn.Module):
    method __init__ (line 130) | def __init__(self, last_stride=2, block=Bottleneck, layers=[3, 4, 6, 3]):
    method _make_layer (line 144) | def _make_layer(self, block, planes, blocks, stride=1):
    method forward (line 161) | def forward(self, x):
    method load_param (line 174) | def load_param(self, param_dict):
    method random_init (line 180) | def random_init(self):

FILE: trainers/evaluator.py
  class ResNetEvaluator (line 10) | class ResNetEvaluator:
    method __init__ (line 11) | def __init__(self, model):
    method save_incorrect_pairs (line 14) | def save_incorrect_pairs(self, distmat, queryloader, galleryloader,
    method evaluate (line 45) | def evaluate(self, queryloader, galleryloader, queryFliploader, galler...
    method _parse_data (line 135) | def _parse_data(self, inputs):
    method _forward (line 139) | def _forward(self, inputs):
    method eval_func_gpu (line 144) | def eval_func_gpu(self, distmat, q_pids, g_pids, q_camids, g_camids, m...
    method eval_func (line 174) | def eval_func(self, distmat, q_pids, g_pids, q_camids, g_camids, max_r...

FILE: trainers/re_ranking.py
  function re_ranking (line 33) | def re_ranking(q_g_dist, q_q_dist, g_g_dist, k1=20, k2=6, lambda_value=0...
  function k_reciprocal_neigh (line 101) | def k_reciprocal_neigh( initial_rank, i, k1):
  function re_ranking_new (line 107) | def re_ranking_new(q_g_dist, q_q_dist, g_g_dist, k1=20, k2=6, lambda_val...

FILE: trainers/trainer.py
  class cls_tripletTrainer (line 13) | class cls_tripletTrainer:
    method __init__ (line 14) | def __init__(self, opt, model, optimzier, criterion, summary_writer):
    method train (line 21) | def train(self, epoch, data_loader):
    method _parse_data (line 64) | def _parse_data(self, inputs):
    method _forward (line 90) | def _forward(self):
    method _backward (line 94) | def _backward(self):

FILE: utils/DistWeightDevianceLoss.py
  function similarity (line 9) | def similarity(inputs_):
  function GaussDistribution (line 16) | def GaussDistribution(data):
  class DistWeightBinDevianceLoss (line 27) | class DistWeightBinDevianceLoss(nn.Module):
    method __init__ (line 28) | def __init__(self, margin=0.5):
    method forward (line 32) | def forward(self, inputs, targets):
  function main (line 95) | def main():

FILE: utils/LiftedStructure.py
  function similarity (line 10) | def similarity(inputs_):
  function pdist (line 16) | def pdist(A, squared = False, eps = 1e-4):
  class LiftedStructureLoss (line 22) | class LiftedStructureLoss(nn.Module):
    method __init__ (line 23) | def __init__(self, alpha=10, beta=2, margin=0.5, hard_mining=None, **k...
    method forward (line 30) | def forward(self, embeddings, labels):
  function main (line 65) | def main():

FILE: utils/loss.py
  function topk_mask (line 7) | def topk_mask(input, dim, K = 10, **kwargs):
  function pdist (line 11) | def pdist(A, squared = False, eps = 1e-4):
  function normalize (line 18) | def normalize(x, axis=-1):
  function euclidean_dist (line 29) | def euclidean_dist(x, y):
  function hard_example_mining (line 46) | def hard_example_mining(dist_mat, labels, margin, return_inds=False):
  class TripletLoss (line 101) | class TripletLoss(object):
    method __init__ (line 106) | def __init__(self, margin=None):
    method __call__ (line 113) | def __call__(self, global_feat, labels, normalize_feature=False):
  class CrossEntropyLabelSmooth (line 126) | class CrossEntropyLabelSmooth(nn.Module):
    method __init__ (line 136) | def __init__(self, num_classes, epsilon=0.1, use_gpu=True):
    method forward (line 143) | def forward(self, inputs, targets):
  class Margin (line 156) | class Margin:
    method __call__ (line 157) | def __call__(self, embeddings, labels):

FILE: utils/meters.py
  class AverageMeter (line 7) | class AverageMeter(object):
    method __init__ (line 8) | def __init__(self):
    method update (line 16) | def update(self, value, n=1):
    method value (line 31) | def value(self):
    method reset (line 34) | def reset(self):

FILE: utils/random_erasing.py
  class Cutout (line 11) | class Cutout(object):
    method __init__ (line 12) | def __init__(self, probability = 0.5, size = 64, mean=[0.4914, 0.4822,...
    method __call__ (line 17) | def __call__(self, img):
  class RandomErasing (line 38) | class RandomErasing(object):
    method __init__ (line 50) | def __init__(self, probability = 0.5, sl = 0.02, sh = 0.4, r1 = 0.3, m...
    method __call__ (line 57) | def __call__(self, img):

FILE: utils/serialization.py
  class Logger (line 11) | class Logger(object):
    method __init__ (line 17) | def __init__(self, fpath=None):
    method __del__ (line 24) | def __del__(self):
    method __enter__ (line 27) | def __enter__(self):
    method __exit__ (line 30) | def __exit__(self, *args):
    method write (line 33) | def write(self, msg):
    method flush (line 38) | def flush(self):
    method close (line 44) | def close(self):
  function mkdir_if_missing (line 50) | def mkdir_if_missing(dir_path):
  function save_checkpoint (line 58) | def save_checkpoint(state, is_best, save_dir, filename):

FILE: utils/transforms.py
  class Random2DTranslation (line 8) | class Random2DTranslation(object):
    method __init__ (line 18) | def __init__(self, height, width, p=0.5, interpolation=Image.BILINEAR):
    method __call__ (line 24) | def __call__(self, img):
  function pad_shorter (line 45) | def pad_shorter(x):
  class TrainTransform (line 52) | class TrainTransform(object):
    method __init__ (line 53) | def __init__(self, data):
    method __call__ (line 56) | def __call__(self, x):
  class TestTransform (line 88) | class TestTransform(object):
    method __init__ (line 89) | def __init__(self, data, flip=False):
    method __call__ (line 93) | def __call__(self, x=None):

FILE: utils/validation_metrics.py
  function accuracy (line 2) | def accuracy(score, target, topk=(1,)):