from VideoClassification.utils.Logger import Logger import math log = Logger("/tmp/runs/r3") for step in range(100): v1 = math.sin(step) v2 = math.cos(step) v3 = 2000*step log.scalar_summary('model2/v1',v1,step) log.scalar_summary('model2/v2',v2,step) log.scalar_summary('model2/v3',v3,step)
from VideoClassification.utils.toolkits import accuracy, try_to_load_state_dict from VideoClassification.utils.DataSetLoader.PictureQueue import PictureQueue, GenVariables_Spatial, \ GenVariables_Temporal ''' VGG TWO Stram 测试: 1. Spatial 输入单张图片, SGD 10个 epoch 每个迭代4000次 初始学习率0.001, 每个epoch学习率*0.1 2. Temporal 输入连续多20张光流, SGD 20个 epoch 每个迭代5000次 初始学习率0.05 每个epoch学习率*0.5 ''' ############ Config logger = Logger(Config.LOGSpace + Config.EX_ID) savepath = Config.ExWorkSpace + Config.EX_ID + '/' import os.path if os.path.isdir(savepath) == False: os.mkdir(savepath) batchsize = 86 ############ def VGG_Temporal_Net_Run(): epochs = 80 loops = 2000