{"html_url": "https://github.com/dogsheep/dogsheep-photos/issues/16#issuecomment-623807568", "issue_url": "https://api.github.com/repos/dogsheep/dogsheep-photos/issues/16", "id": 623807568, "node_id": "MDEyOklzc3VlQ29tbWVudDYyMzgwNzU2OA==", "user": {"value": 9599, "label": "simonw"}, "created_at": "2020-05-05T02:56:06Z", "updated_at": "2020-05-05T02:56:06Z", "author_association": "MEMBER", "body": "I'm pretty sure this is what I'm after. The `groups` table has what looks like identified labels in the rows with category = 2025:\r\n\r\n\"words__groups__2_528_rows_where_where_category___2025\"\r\n\r\nThen there's a `ga` table that maps groups to assets:\r\n\r\n\"words__ga__633_653_rows\"\r\n\r\nAnd an `assets` table which looks like it has one row for every one of my photos:\r\n\r\n\"words__assets__40_419_rows\"\r\n\r\nOne major challenge: these UUIDs are split into two integer numbers, `uuid_0` and `uuid_1` - but the main photos database uses regular UUIDs like this:\r\n\r\n![image](https://user-images.githubusercontent.com/9599/81031481-39164280-8e41-11ea-983b-005ced641a18.png)\r\n\r\nI need to figure out how to match up these two different UUID representations. I asked on Twitter if anyone has any ideas: https://twitter.com/simonw/status/1257500689019703296", "reactions": "{\"total_count\": 1, \"+1\": 1, \"-1\": 0, \"laugh\": 0, \"hooray\": 0, \"confused\": 0, \"heart\": 0, \"rocket\": 0, \"eyes\": 0}", "issue": {"value": 612287234, "label": "Import machine-learning detected labels (dog, llama etc) from Apple Photos"}, "performed_via_github_app": null}