External functions

No library can dream of offering all the required functionality. Especially for one-off tasks, it makes no sense to develop a whole new plugin library. Hence, there are the following generic plugins that allow the user to utilize custom Python functions:

  • reader: from-pyfunc - takes a single string as input and outputs an iterable of image containers (as per specified data type)
  • filter: pyfunc-filter - takes a single image container or an iterable of them as input and outputs a single container or an iterable of them (as per specified input and output data types)
  • writer: to-pyfunc - processes a single image container or an iterable of them as per specified data type and an optional split name

In order to use such a custom function, they must be specified in the following format (option: -f/--function):


If the code below were available through module my.code, then the function specifications would be as follows:

  • reader: my.code:pyfunc_reader
  • filter: my.code:pyfunc_filter
  • writer: my.code:pyfunc_writer
from typing import Iterable
from idc.api import ImageClassificationData, make_list, flatten_list

# reader: generates image classification containers from the path   
def pyfunc_reader(path: str) -> Iterable[ImageClassificationData]:
    return [ImageClassificationData(source=path)]

# filter: simply adds a note to the meta-data
def pyfunc_filter(data):
    result = []
    for item in make_list(data):
        if not item.has_metadata():
            meta = dict()
            meta = item.get_metadata()
        meta["note"] = "filtered by a python function!"
    return flatten_list(result)

# writer: simply outputs name and meta-data and, if present, also the split
def pyfunc_writer(data: ImageClassificationData, split: str = None):
    if split is None:
        print("name: ", data.image_name, ", meta:", data.get_metadata())
        print("split:", split, ", name:", data.image_name, ", meta:", data.get_metadata())