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config.py
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import os
from easydict import EasyDict as edict
import time
import torch
# init
__C = edict()
cfg = __C
#------------------------------TRAIN------------------------
__C.SEED = 3035 # random seed, for reproduction
__C.DATASET = 'AC' # dataset selection: GCC, SHHA, SHHB, UCF50, QNRF, WE, Mall, UCSD
if __C.DATASET == 'UCF50':# only for UCF50
from datasets.UCF50.setting import cfg_data
__C.VAL_INDEX = cfg_data.VAL_INDEX
if __C.DATASET == 'GCC': # only for GCC
from datasets.GCC.setting import cfg_data
__C.VAL_MODE = cfg_data.VAL_MODE
# net selection: MCNN, AlexNet, VGG, VGG_DECODER, Res50, CSRNet, SANet, CSRNet_IN, CANNet, CSRNet_Audio, CANNet_Audio
# CSRNet_Audio_Concat, CANNet_Audio_Concat, CSRNet_Audio_Guided, CANNet_Audio_Guided
__C.NET = 'CANNet'
__C.PRE_GCC = False # use the pretrained model on GCC dataset
__C.PRE_GCC_MODEL = 'path to model' # path to model
__C.RESUME = False # contine training
__C.RESUME_PATH = '../trained_models/exp/image-noise-0.2-25-denoise-audio-wo_AC_CSRNet_1e-05/all_ep_274_mae_29.8_mse_48.5.pth' #
__C.GPU_ID = [0, 1, 2, 3, 4, 5, 6, 7] # sigle gpu: [0], [1] ...; multi gpus: [0,1]
# learning rate settings
__C.LR = 1e-5 # learning rate
__C.LR_DECAY = 0.99 # decay rate
__C.LR_DECAY_START = -1 # when training epoch is more than it, the learning rate will be begin to decay
__C.NUM_EPOCH_LR_DECAY = 1 # decay frequency
__C.MAX_EPOCH = 200
# multi-task learning weights, no use for single model, such as MCNN, VGG, VGG_DECODER, Res50, CSRNet, and so on
__C.LAMBDA_1 = 1e-4 # SANet:0.001 CMTL 0.0001 other: 1e-4
# print
__C.PRINT_FREQ = 10
now = time.strftime("%m-%d_%H-%M", time.localtime())
# settings = 'image-noise(0.2, 25)-audio-wo' # image-clean/(0.3, 50)_audio-w/wo
__C.SETTINGS = 'image-clean-audio-wo' # image-clean/(0.3, 50)_audio-w/wo
__C.EXP_NAME = __C.SETTINGS + '_' + __C.DATASET + '_' + __C.NET + '_' + str(__C.LR)
if __C.DATASET == 'UCF50':
__C.EXP_NAME += '_' + str(__C.VAL_INDEX)
if __C.DATASET == 'GCC':
__C.EXP_NAME += '_' + __C.VAL_MODE
__C.EXP_PATH = '../trained_models/exp' # the path of logs, checkpoints, and current codes
#------------------------------VAL------------------------
__C.VAL_DENSE_START = 50
__C.VAL_FREQ = 10 # Before __C.VAL_DENSE_START epoches, the freq is set as __C.VAL_FREQ
#------------------------------VIS------------------------
__C.VISIBLE_NUM_IMGS = 1 # must be 1 for training images with the different sizes
#================================================================================
#================================================================================
#================================================================================