aggressive_multi_head_UNET_2d.py 文件源码

def create_inputs(self, image_size):
        print("Creating input Placeholders...")
        #input image
        self.X = tf.placeholder(dtype=tf.float32, 
            shape=[None, image_size[0], image_size[1], 1],
            name="in")

        #Outputs of the different heads

        #Nodule head
        self.Y_nodule = tf.placeholder(dtype=tf.float32,
            shape=[None, image_size[0], image_size[1], 1],
            name="out_nodule")
        self.Y_nodule_weight = tf.placeholder_with_default(input=1.0,
            shape=None,
            name="nodule_weight")

        #Cancer head
        self.Y_cancer = tf.placeholder(dtype=tf.float32,
            shape=[None, 1],
            name="out_cancer")
        self.Y_cancer_weight = tf.placeholder_with_default(input=1.0,
            shape=None,
            name="cancer_weight")

        #Boolean variables to check head and mode
        self.is_training = tf.placeholder(dtype=tf.bool,
            name="is_training")
        self.is_nodule = tf.placeholder(dtype=tf.bool,
            name="is_nodule")
        self.is_cancer = tf.placeholder(dtype=tf.bool,
            name="is_cancer")

        #Probability for dropout
        self.drop_prob = tf.placeholder_with_default(input=0.0,
            shape=None,
            name="dropout_probability")

        print("Created input placeholders!")