config.py(quoc14)

from easydict import EasyDict as edict
from pathlib import Path

def get_config(training = True):
    conf = edict()
    conf.data_path = Path('data')
    conf.work_path = Path('work_space/')
    conf.model_path = conf.work_path/'models'
    conf.log_path = conf.work_path/'log'
    conf.save_path = conf.work_path/'save'
    conf.input_size = [112,112]
    conf.embedding_size = 512
    conf.use_mobilfacenet = False
    conf.net_depth = 50
    conf.drop_ratio = 0.6
    conf.facebank_path = Path('/media/sda6/dataset/vectorFace/ArcFace_InsightTorch') #conf.data_path/'facebank' 
    conf.faceText_path = Path('/media/sda6/gao.tv/AI2023/faceCode/data/VTS')#conf.data_path/'facebank'
    conf.threshold = 1.0
    conf.face_limit = 10 
    #when inference, at maximum detect 10 faces in one image, my laptop is slow
    conf.min_face_size = 30 
    # the larger this value, the faster deduction, comes with tradeoff in small faces
    
    conf.represent_vector = 'mean' # 'mean' or '0'
    conf.number_image_use = 3
    conf.distance = 'euclid' #[cosine, euclid]
    
    conf.method = 'AdaFace_ir50_mtcnn'
    conf.vts_enroll = '/media/sda6/dataset/faceRecognition/vts/vector/vts_enroll/AdaFace_ir50_mtcnn'
    conf.vts_inout = '/media/sda6/dataset/faceRecognition/vts/vector/vts_inout/AdaFace_ir50_mtcnn'
    return conf