69f6cb1e25e014952b409cd906e319415c43e1d0,doc_seg/utils.py,,multiclass_to_label_image,#Any#Any#,133

Before Change

    with tf.name_scope("Label2Img"):
        classes_color_values = tf.cast(get_classes_color_from_file(classes_file), tf.int32)
        fn = lambda x: tf.py_func(multilabel_to_img, [x, classes_color_values], tf.int32, name="py_label2img")
        image_tf = tf.map_fn(fn, class_label_tensor, name="map_for_batch")
        _shape = class_label_tensor.get_shape().as_list()
        image_tf.set_shape([_shape[0], _shape[1], _shape[2], 3])
        return image_tf


def get_classes_color_from_file(classes_file: str) -> np.ndarray:

After Change

    classes_color_values, colors_labels = get_classes_color_from_file_multilabel(classes_file)

    n_classes = colors_labels.shape[1]
    c = np.zeros((2,)*n_classes+(3,), np.int32)
    for c_value, inds in zip(classes_color_values, colors_labels):
        c[tuple(inds)] = c_value

Instances