def postprocess(self, folder, skipJobs):
"""
Post-processing to be run after media/annotation import
When skipJobs=False, the following may run as jobs:
Transcoding of Video
Transcoding of Images
Conversion of KPF annotations into track JSON
In either case, the following may run synchronously:
Conversion of CSV annotations into track JSON
"""
user = self.getCurrentUser()
auxiliary = get_or_create_auxiliary_folder(folder, user)
if not skipJobs:
token = Token().createToken(user=user, days=1)
# transcode VIDEO if necessary
videoItems = Folder().childItems(
folder, filters={"lowerName": {
"$regex": videoRegex
}})
for item in videoItems:
convert_video.delay(
GetPathFromItemId(str(item["_id"])),
str(item["folderId"]),
auxiliary["_id"],
girder_job_title=(
"Converting {} to a web friendly format".format(
str(item["_id"]))),
girder_client_token=str(token["_id"]),
)
# transcode IMAGERY if necessary
imageItems = Folder().childItems(
folder, filters={"lowerName": {
"$regex": imageRegex
}})
safeImageItems = Folder().childItems(
folder, filters={"lowerName": {
"$regex": safeImageRegex
}})
if imageItems.count() > safeImageItems.count():
convert_images.delay(
folder["_id"],
girder_client_token=str(token["_id"]),
girder_job_title=
f"Converting {folder['_id']} to a web friendly format",
)
elif imageItems.count() > 0:
folder["meta"]["annotate"] = True
# transform KPF if necessary
ymlItems = Folder().childItems(
folder, filters={"lowerName": {
"$regex": ymlRegex
}})
if ymlItems.count() > 0:
# There might be up to 3 yamls
allFiles = [Item().childFiles(item)[0] for item in ymlItems]
saveTracks(folder,
meva_serializer.load_kpf_as_tracks(allFiles), user)
ymlItems.rewind()
for item in ymlItems:
Item().move(item, auxiliary)
Folder().save(folder)
# transform CSV if necessasry
csvItems = Folder().childItems(
folder,
filters={"lowerName": {
"$regex": csvRegex
}},
sort=[("created", pymongo.DESCENDING)],
)
if csvItems.count() >= 1:
file = Item().childFiles(csvItems.next())[0]
json_output = getTrackData(file)
saveTracks(folder, json_output, user)
csvItems.rewind()
for item in csvItems:
Item().move(item, auxiliary)
return folder
