@Eelco_Anneveldt lol - you best shut it all down now then 
Alternatively, if you don’t need images of your ex in DT, remove her and force update to all attached facial recognition systems?
Its actually more simpler than that to swap versions.
So what I did was installed the new version while the old was one running, shutdown the old version, repointed the add-on configuration for new version to the same locations as old version (see pic below), then shut down old version, turned on new version and it all worked - no need to mess with DT yaml config 
For clarity, my DT add-on config is the following:
With these settings, I can delve into the images and image folders without any issue and even setup notifications from HA to companion app and view the notification with the correct image when away from home.
If it helps at all, my DT config is:
# Double Take
# Learn more at https://github.com/jakowenko/double-take/#configuration
# "Snapshot" -- frame from frigate, saved then frigate detect an event (motion, for example)
# "Latest" -- frame from camera, on the moment then double-take trying to make an recognition (Usually, the difference between them is 1-2 seconds)
# "MQTT" -- The frame that the frigate transmitted with the event by MQTT protocol. It's usually equivalent to "snapshot", but depends on frigate settings
# If u use double-take in conjunction with frigate, the "snapshot" method will be enough
# Want either MQTT or Snapshot. MQTT does not include zone
home_assistant:
url: http://192.168.1.198:8123
token: %TOKEN_VALUE%
frigate:
url: http://192.168.1.158:5000
update_sub_labels: True
# stop the processing loop if a match is found
# if set to false all image attempts will be processed before determining the best match
stop_on_match: True
# ignore detected areas so small that face recognition would be difficult
# quadrupling the min_area of the detector is a good start
# does not apply to MQTT events
#min_area: 1600
# object labels that are allowed for facial recognition
labels:
- person
attempts:
# number of times double take will request a frigate latest.jpg for facial recognition
latest: 0
# number of times double take will request a frigate snapshot.jpg for facial recognition
snapshot: 10
# process frigate images from frigate/+/person/snapshot topics
mqtt: false
# add a delay expressed in seconds between each detection loop
# delay: 0
# only process images from specific zones
zones:
- camera: doorbell
zone: garden_doorbell
- camera: car-port
zone: driveway_carport
mqtt:
host: 192.168.1.198
username: %MQTT_USERNAME_VALUE%
password: %MQTT_PASSWORD_VALUE%
detectors:
#If you want no match then increase det_prob_threshold: 80 a little at a time and re-test your matches… it will return nothing if it fails this test. I have been creeping this value up and it has really reduced the number of images accepted and false positives from blurry movement shots etc.
#detectors:
#compreface:
# minimum required confidence that a recognized face is actually a face
# det_prob_threshold: 0.98
compreface:
url: http://192.168.1.158:8000
# recognition api key
key: %KEY_VALUE%
# number of seconds before the request times out and is aborted
timeout: 15
# minimum required confidence that a recognized face is actually a face
# value is between 0.0 and 1.0
det_prob_threshold: 0.8
# require opencv to find a face before processing with detector
opencv_face_required: false
# comma-separated slugs of face plugins
# https://github.com/exadel-inc/CompreFace/blob/e1ee791cac6cd9b1d3a9ea2cb129c78cb00a9083/docs/Face-services-and-plugins.md)
# face_plugins: mask,gender,age
# only process images from specific cameras, if omitted then all cameras will be processed
# cameras:
# - front-door
# - garage
# aiserver:
# url: http://192.168.1.158:32168
# number of seconds before the request times out and is aborted
# timeout: 15
# require opencv to find a face before processing with detector
# opencv_face_required: false
telemetry: false
detect:
match:
# save match images
save: true
# include base64 encoded string in api results and mqtt messages
# options: true, false, box
base64: false
# minimum confidence needed to consider a result a match
confidence: 85
# hours to keep match images until they are deleted
purge: 24
# minimum area in pixels to consider a result a match
min_area: 2500
#when using substream image, 3600
unknown:
# save unknown images
save: true
# include base64 encoded string in api results and mqtt messages
# options: true, false, box
base64: false
# minimum confidence needed before classifying a name as unknown
confidence: 85
# hours to keep unknown images until they are deleted
purge: 8
# minimum area in pixels to keep an unknown result
min_area: 64
With this I don’t get false positives that often and people the system doesn’t know shows up as Unknown
