def _process_files(paths, **params_decode):
paths = [paths] if not isinstance(paths, list) else paths
import modules.data.decode_tf as decode_tf
import tensorflow as tf
# IMPROVE: accept different kinds of input data
data_list = []
for path in paths:
data_list.append(decode_tf.decode_image_file(tf.convert_to_tensor(path), **params_decode))
data_t = tf.data.Dataset.from_tensor_slices(data_list)
return data_t
def wrapper_decode_image_file(file_name_t, folder_id_t):
# NOTE: cannot use ordinary string operations here, use Tensor instead
# path = osp.join(root_path, folder_name, file_name)
folder_name_t = vocabulary_t[folder_id_t]
path_t = tf.strings.join([root_path_t, folder_name_t, file_name_t],
'/')
# Updating: consider use **decode_x in map_func
# return decode_tf.decode_image_file(
# path_t, encoding=None, colormode=colormode,
# resize_w=resize_w, resize_h=resize_h,
# normalize=normalize, preserve_aspect_ratio=preserve_aspect_ratio
# )
return decode_tf.decode_image_file(path_t, **params_decode)
def map_path_to_image(path_t):
return decode_tf.decode_image_file(path_t, **params_decode)