data_extractor.py 文件源码

def load_letter(folder, min_num_images, image_size, pixel_depth):
        """Load the data for a single letter label."""
        image_files = os.listdir(folder)
        dataset = np.ndarray(shape=(len(image_files), image_size, image_size),
                             dtype=np.float32)
        image_index = 0
        print(folder)
        for image in os.listdir(folder):
            image_file = os.path.join(folder, image)
            try:
                image_data = (ndimage.imread(image_file).astype(float) -
                              pixel_depth / 2) / pixel_depth
                if image_data.shape != (image_size, image_size):
                    raise Exception('Unexpected image shape: %s' % str(image_data.shape))
                dataset[image_index, :, :] = image_data
                image_index += 1
            except IOError as e:
                print('Could not read:', image_file, ':', e, '- it\'s ok, skipping.')

        num_images = image_index
        dataset = dataset[0:num_images, :, :]
        if num_images < min_num_images:
            raise Exception('Many fewer images than expected: %d < %d' %
                            (num_images, min_num_images))

        print('Full dataset tensor:', dataset.shape)
        print('Mean:', np.mean(dataset))
        print('Standard deviation:', np.std(dataset))
        return dataset