Function getImageData

cnn_class/cifar.py:37–67

()

def getImageData():
    N = 50000
    savedXpath = '../large_files/cifar10/train_all.npy'
    if not os.path.exists(savedXpath):
        X = np.zeros((N, 3, 32, 32))
        for i in xrange(N):
            im = Image.open("../large_files/cifar10/train/%s.png" % (i + 1))
            X[i] = image2array(im)
            if i % 1000 == 0:
                print i
        np.save(savedXpath, X.astype(np.uint8))
    else:
        X = np.load(savedXpath)
    X = X.astype(np.float32) / 255.0

    # load labels
    Y = np.zeros(N)
    df = pd.read_csv('../large_files/cifar10/trainLabels.csv')
    S = df['label'].tolist()
    idx = 0
    label2idx = {}
    i = 0
    for s in S:
        if s not in label2idx:
            label2idx[s] = idx
            idx += 1
        Y[i] = label2idx[s]
        i += 1
    print "done loading data"
    X, Y = shuffle(X, Y)
    return X[:30000], Y[:30000]


class HiddenLayer(object):