def _convert_dataset_to_image_and_bboxes(self, dataset):
    '\n        @param dataset: [image_path, [[x, y, w, h, class_id], ...]]\n\n        @return image, bboxes\n            image: 0.0 ~ 1.0, Dim(1, height, width, channels)\n        '
    try:
        image = cv2.imread(dataset[0])
        image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
    except:
        return (None, None)
    (resized_image, resized_bboxes) = media.resize_image(image, target_shape=self._metanet.input_shape, ground_truth=dataset[1])
    resized_image = np.expand_dims((resized_image / 255.0), axis=0)
    return (resized_image, resized_bboxes)
@param dataset: [image_path, [[x, y, w, h, class_id], ...]]

@return image, bboxes
    image: 0.0 ~ 1.0, Dim(1, height, width, channels)
def _convert_dataset_to_image_and_bboxes(self, dataset):
    '\n        @param dataset: [image_path, [[x, y, w, h, class_id], ...]]\n\n        @return image, bboxes\n            image: 0.0 ~ 1.0, Dim(1, height, width, channels)\n        '
    try:
        image = cv2.imread(dataset[0])
        image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
    except:
        return (None, None)
    (resized_image, resized_bboxes) = media.resize_image(image, target_shape=self._metanet.input_shape, ground_truth=dataset[1])
    resized_image = np.expand_dims((resized_image / 255.0), axis=0)
    return (resized_image, resized_bboxes)