cnn.py 文件源码

def preprocess(image_shape, image_paths, labels=[]):
    features = []
    for image_path in tqdm(image_paths):
        image_data = list(Image.open(image_path).resize(image_shape[:2]).getdata())
        image_data = np.asarray(image_data).reshape(image_shape)

        features.append(image_data)

    # Normalizer
    features = np.asarray(features)
    features = features / 255.0

    if labels:
        # one hot encode
        label_binarizer = LabelBinarizer()
        labels = label_binarizer.fit_transform(labels)
        # Shuffle
        features, labels = shuffle(features, labels)

    return features, labels