train.py 文件源码

def __init__(self, output_dir, num_identities, batch_size=32, use_yale=False,
                 use_jaffe=False):
        """
        Constructor for a GenerateIntermediate object.

        Args:
            output_dir (str): Directory to save intermediate results in.
            num_identities (int): Number of identities in the training set.
        Args: (optional)
            batch_size (int): Batch size to use when generating images.
        """
        super(Callback, self).__init__()

        self.output_dir = output_dir
        self.num_identities = num_identities
        self.batch_size = batch_size
        self.use_yale = use_yale
        self.use_jaffe = use_jaffe

        self.parameters = dict()

        # Sweep through identities
        self.parameters['identity'] = np.eye(num_identities)

        if use_yale:
            # Use pose 0, lighting at 0deg azimuth and elevation
            self.parameters['pose'] = np.zeros((num_identities, NUM_YALE_POSES))
            self.parameters['lighting'] = np.zeros((num_identities, 4))
            for i in range(0, num_identities):
                self.parameters['pose'][i,0] = 0
                self.parameters['lighting'][i,1] = 1
                self.parameters['lighting'][i,3] = 1
        else:
            # Make all have neutral expressions, front-facing
            self.parameters['emotion'] = np.empty((num_identities, Emotion.length()))
            self.parameters['orientation'] = np.zeros((num_identities, 2))
            for i in range(0, num_identities):
                self.parameters['emotion'][i,:] = Emotion.neutral
                self.parameters['orientation'][i,1] = 1