Skip images that have already been converted instead of throwing an error

[ChristianHinge]

Summary

Running heudiconv twice on the exact same source data, with overwrite=False. When running the second time I get:

RuntimeError: was asked to convert into ... but destination already exists

Is this intended? I would love for heudiconv to skip everything it has already preprocessed.

Here is my heuristic script.

from __future__ import annotations

import logging
from typing import Optional
from heudiconv.utils import SeqInfo
import pandas as pd
import os
lgr = logging.getLogger("heudiconv")

def create_key(
    template: Optional[str],
    outtype: tuple[str, ...] = ("nii.gz",),
    annotation_classes: None = None,
) -> tuple[str, tuple[str, ...], None]:
    if template is None or not template:
        raise ValueError("Template must be a valid format string")
    return (template, outtype, annotation_classes)

def name_to_key(names):
    name_to_key = {}
    for name in names:
        if name is None:
            continue
        if name.startswith("pt"):
            name_to_key[name] = create_key('sub-{subject}/{session}/pet/sub-{subject}_{session}_'+name)
        elif name.startswith("ct") or name.startswith("mr"):
            name_to_key[name] = create_key('sub-{subject}/{session}/anat/sub-{subject}_{session}_'+name)
    return name_to_key

def infotodict_base(
    seqinfo: list[SeqInfo],
    conversion_f
) -> dict[tuple[str, tuple[str, ...], None], list[str]]:
    pkl = pd.read_pickle(conversion_f)
    pkl = pkl[~pd.isna(pkl.SERIES_NAME)]
    conversion = dict(zip(pkl.SeriesInstanceUID,pkl.SERIES_NAME))
    names_to_keys = name_to_key(set(conversion.values()))
    info: dict[tuple[str, tuple[str, ...], None], list[str]] = {k:[] for k in names_to_keys.values()}
    for s in seqinfo:
        series_name = conversion.get(s.series_uid,None)
        if series_name is not None:
            k = names_to_keys[series_name]
            info[k].append(s.series_id)
        
    return info

def infotodict(
    seqinfo
) -> dict[tuple[str, tuple[str, ...], None], list[str]]:
    return infotodict_base(seqinfo,"pkl_file.pkl")

Platform details:

Choose one:

• [x] Local environment - python3.11,

• [ ] Container

• Heudiconv version: 1.1.0