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
):
module_name:function_name
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()
else:
meta = item.get_metadata()
meta["note"] = "filtered by a python function!"
item.set_metadata(meta)
result.append(item)
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())
else:
print("split:", split, ", name:", data.image_name, ", meta:", data.get_metadata())