import tensorflow as tf

import TensorflowUtils as utils
import read_MITSceneParsingData as scene_parsing
import datetime
import BatchDatsetReader as dataset
from six.moves import xrange

import os.path as osp

FLAGS = tf.flags.FLAGS
tf.flags.DEFINE_integer("batch_size", "2", "batch size for training")
tf.flags.DEFINE_string("logs_dir", r"E:\work\01-Myproject\imag_division\FCN.tensorflow-master\logs", "path to logs directory")
tf.flags.DEFINE_string("data_dir", r"E:\work\01-Myproject\imag_division\FCN.tensorflow-master\Data_zoo\STEM", "path to dataset")
tf.flags.DEFINE_float("learning_rate", "1e-4", "Learning rate for Adam Optimizer")
tf.flags.DEFINE_string("model_dir", r"E:\work\01-Myproject\imag_division\FCN.tensorflow-master\Model_zoo", "Path to vgg model mat")
tf.flags.DEFINE_bool('debug', "False", "Debug mode: True/ False")
tf.flags.DEFINE_string('mode', "train", "Mode train/ test/ visualize")

MODEL_URL = 'http://www.vlfeat.org/matconvnet/models/beta16/imagenet-vgg-verydeep-19.mat'

MAX_ITERATION = 100  #最大步数
NUM_OF_CLASSESS = 3  #分类数目
IMAGE_SIZE = 2048 #图像大小


