def build_FD_model(img_input):
with tf.variable_scope('FD_detection'):
mod = M.Model(img_input,[None,28*28])
mod.reshape([-1,28,28,1])
mod.convLayer(5,16,activation=M.PARAM_LRELU)
mod.maxpoolLayer(2)
mod.convLayer(5,16,activation=M.PARAM_LRELU)
mod.maxpoolLayer(2)
mod.convLayer(5,16,activation=M.PARAM_LRELU)
mod.maxpoolLayer(2)
mod.flatten()
mod.fcLayer(50,activation=M.PARAM_LRELU)
mod.fcLayer(11)
return mod.get_current_layer()
def build_model(img_input):
# can change whatever activation function
with tf.variable_scope('mnist'):
mod = M.Model(img_input,[None,28*28])
mod.reshape([-1,28,28,1])
mod.convLayer(5,16,activation=M.PARAM_LRELU)
mod.maxpoolLayer(2)
mod.convLayer(5,16,activation=M.PARAM_LRELU)
mod.maxpoolLayer(2)
mod.convLayer(5,16,activation=M.PARAM_LRELU)
mod.maxpoolLayer(2)
mod.flatten()
mod.fcLayer(50,activation=M.PARAM_LRELU)
mod.fcLayer(10)
return mod.get_current_layer()
def __init__(self):
self.model = model.Model(test_config)
# 将影像采样为小图片，并进行保存，这个集合记录小图片的地址
self.sample_image_path = []
self.size = test_config.size