SYMBOL INDEX (84 symbols across 11 files)

FILE: emotic.py
  class Emotic (line 4) | class Emotic(nn.Module):
    method __init__ (line 6) | def __init__(self, num_context_features, num_body_features):
    method forward (line 18) | def forward(self, x_context, x_body):

FILE: emotic_dataset.py
  class Emotic_PreDataset (line 11) | class Emotic_PreDataset(Dataset):
    method __init__ (line 13) | def __init__(self, x_context, x_body, y_cat, y_cont, transform, contex...
    method __len__ (line 23) | def __len__(self):
    method __getitem__ (line 26) | def __getitem__(self, index):
  class Emotic_CSVDataset (line 34) | class Emotic_CSVDataset(Dataset):
    method __init__ (line 36) | def __init__(self, data_df, cat2ind, transform, context_norm, body_nor...
    method __len__ (line 45) | def __len__(self):
    method __getitem__ (line 48) | def __getitem__(self, index):
    method cat_to_one_hot (line 60) | def cat_to_one_hot(self, cat):

FILE: inference.py
  function process_images (line 11) | def process_images(context_norm, body_norm, image_context_path=None, ima...
  function infer (line 45) | def infer(context_norm, body_norm, ind2cat, ind2vad, device, thresholds,...
  function inference_emotic (line 92) | def inference_emotic(images_list, model_path, result_path, context_norm,...

FILE: loss.py
  class DiscreteLoss (line 4) | class DiscreteLoss(nn.Module):
    method __init__ (line 6) | def __init__(self, weight_type='mean', device=torch.device('cpu')):
    method forward (line 19) | def forward(self, pred, target):
    method prepare_dynamic_weights (line 26) | def prepare_dynamic_weights(self, target):
  class ContinuousLoss_L2 (line 34) | class ContinuousLoss_L2(nn.Module):
    method __init__ (line 36) | def __init__(self, margin=1):
    method forward (line 40) | def forward(self, pred, target):
  class ContinuousLoss_SL1 (line 47) | class ContinuousLoss_SL1(nn.Module):
    method __init__ (line 49) | def __init__(self, margin=1):
    method forward (line 53) | def forward(self, pred, target):

FILE: main.py
  function parse_args (line 9) | def parse_args():
  function check_paths (line 34) | def check_paths(args):

FILE: mat2py.py
  class emotic_train (line 9) | class emotic_train:
    method __init__ (line 10) | def __init__(self, filename, folder, image_size, person):
    method set_imsize (line 27) | def set_imsize(self, image_size):
    method validate_bbox (line 34) | def validate_bbox(self, bbox):
    method set_bbox (line 42) | def set_bbox(self, person_bbox):
    method set_cat (line 45) | def set_cat(self, person_cat):
    method set_cont (line 51) | def set_cont(self, person_cont):
    method check_cont (line 56) | def check_cont(self):
  class emotic_test (line 62) | class emotic_test:
    method __init__ (line 63) | def __init__(self, filename, folder, image_size, person):
    method set_imsize (line 85) | def set_imsize(self, image_size):
    method validate_bbox (line 92) | def validate_bbox(self, bbox):
    method set_bbox (line 100) | def set_bbox(self, person_bbox):
    method set_cat (line 103) | def set_cat(self, person_cat):
    method set_comb_cat (line 112) | def set_comb_cat(self, person_comb_cat):
    method set_comb_cont (line 118) | def set_comb_cont(self, person_comb_cont):
    method set_cont (line 125) | def set_cont(self, person_cont):
    method check_cont (line 134) | def check_cont(self):
  function cat_to_one_hot (line 141) | def cat_to_one_hot(y_cat):
  function prepare_data (line 152) | def prepare_data(data_mat, data_path_src, save_dir, dataset_type='train'...
  function parse_args (line 250) | def parse_args():

FILE: prepare_models.py
  function prep_models (line 8) | def prep_models(context_model='resnet18', body_model='resnet18', model_d...

FILE: test.py
  function test_scikit_ap (line 16) | def test_scikit_ap(cat_preds, cat_labels, ind2cat):
  function test_vad (line 31) | def test_vad(cont_preds, cont_labels, ind2vad):
  function get_thresholds (line 46) | def get_thresholds(cat_preds, cat_labels):
  function test_data (line 62) | def test_data(models, device, data_loader, ind2cat, ind2vad, num_images,...
  function test_emotic (line 122) | def test_emotic(result_path, model_path, ind2cat, ind2vad, context_norm,...

FILE: train.py
  function train_data (line 21) | def train_data(opt, scheduler, models, device, train_loader, val_loader,...
  function train_emotic (line 135) | def train_emotic(result_path, model_path, train_log_path, val_log_path, ...

FILE: yolo_inference.py
  function parse_args (line 13) | def parse_args():
  function get_bbox (line 26) | def get_bbox(yolo_model, device, image_context, yolo_image_size=416, con...
  function yolo_infer (line 54) | def yolo_infer(images_list, result_path, model_path, context_norm, body_...
  function yolo_video (line 101) | def yolo_video(video_file, result_path, model_path, context_norm, body_n...
  function check_paths (line 160) | def check_paths(args):

FILE: yolo_utils.py
  function to_cpu (line 10) | def to_cpu(tensor):
  function xywh2xyxy (line 13) | def xywh2xyxy(x):
  function bbox_iou (line 25) | def bbox_iou(box1, box2, x1y1x2y2=True):
  function rescale_boxes (line 57) | def rescale_boxes(boxes, current_dim, original_shape):
  function non_max_suppression (line 73) | def non_max_suppression(prediction, conf_thres=0.5, nms_thres=0.4):
  function parse_model_config (line 113) | def parse_model_config(path):
  function parse_data_config (line 133) | def parse_data_config(path):
  function create_modules (line 148) | def create_modules(module_defs):
  class Upsample (line 217) | class Upsample(nn.Module):
    method __init__ (line 220) | def __init__(self, scale_factor, mode="nearest"):
    method forward (line 225) | def forward(self, x):
  class EmptyLayer (line 229) | class EmptyLayer(nn.Module):
    method __init__ (line 232) | def __init__(self):
  class YOLOLayer (line 235) | class YOLOLayer(nn.Module):
    method __init__ (line 238) | def __init__(self, anchors, num_classes, img_dim=416):
    method compute_grid_offsets (line 252) | def compute_grid_offsets(self, grid_size, cuda=True):
    method forward (line 264) | def forward(self, x, targets=None, img_dim=None):
  class Darknet (line 362) | class Darknet(nn.Module):
    method __init__ (line 365) | def __init__(self, config_path, img_size=416):
    method forward (line 374) | def forward(self, x, targets=None):
    method load_darknet_weights (line 394) | def load_darknet_weights(self, weights_path):
    method save_darknet_weights (line 447) | def save_darknet_weights(self, path, cutoff=-1):
  function prepare_yolo (line 475) | def prepare_yolo(model_dir):