train.py 文件源码

def load_data_into_memory(DIR, ANNO, ATTRIBUTE, normalize=True, rollaxis=True):
    if DIR[:-1] != '/': DIR += '/'
    df = parse_csv(ANNO)
    files = filter(lambda x: x in df.index.values, os.listdir(DIR))
    X, y = [], []
    for image_path in progress.bar(files):
        img = imageio.imread(DIR + image_path)
        if normalize: img = img.astype('float32') / 255.
        if rollaxis: img.shape = (1,150,130)
        else: img.shape = (150,130,1)
        X.append(img)
        mu = df[ATTRIBUTE][image_path]
        y.append(mu)
    y = np.array(y)
    y = y - min(y)
    y = np.float32(y / max(y))

    x, y = np.array(X), np.array(y)
    print 'Loaded {} images into memory'.format(len(y))
    return x, y