Borg backup of Nextcloud Loose Previous Tagged Faces
まだ誰も着手していません。
評価
- 難易度
- 5/5
- 見積もり時間
- 1週間以上
- 初心者へのやさしさ
- 15/100
調査の方向性
The payload names no source files, tests or entry points, so the code location is not given. Start by working out how Recognize stores face clusters and person names in the Postgres database, and how its clustering job reassigns faces when it re-runs after a restore. Done would mean either a documented, tested export and restore path for those assignments, or a clear maintainer decision that the behaviour is intended. The reporter's request is a design question, so a first-timer should confirm the scope with maintainers before writing code.
索引モデルが issue の本文から書いたものです。
説明
Which version of recognize are you using?
13.1.0
Enabled Modes
Face recognition
TensorFlow mode
WASM mode
Downstream App
Memories App
Which Nextcloud version do you have installed?
35.0.1
Which Operating system do you have installed?
Windows 11 Pro + Docker Desktop 4.95.0 / 29.8.2 on WSL 3.0.3.0
Which database are you running Nextcloud on?
Postgress 18.6
Which Docker container are you using to run Nextcloud? (if applicable)
AIO
How much RAM does your server have?
64gb
What processor Architecture does your CPU have?
AMD Ryzen 9 5950X - x86-64 / AMD64
Describe the Bug
After restoring Nextcloud from a recent AIO Borg backup, the photos themselves were intact, but much of the face-recognition work was not preserved correctly. Recognize had previously grouped faces, and I had spent considerable time manually identifying and correcting those groups. After the restore, some person names survived, but many were missing, fragmented, or incorrectly reassigned.
Because the Borg backup was current, the likely issue is not stale data. The more probable explanation is that Recognize restored its database state and then re-ran face processing or clustering, which altered some of the manually curated identity assignments. In other words, the physical photos were protected, but the human-added face identification and clustering state was not reliably preserved through restore and reprocessing.
That is the gap I am trying to solve: how to back up or export the Recognize face/person metadata independently so that a future restore does not require redoing hours of manual tagging.
Expected Behavior
After restoring from a current AIO Borg backup, I expected my existing Recognize face clusters, person names, and manual corrections to remain intact. The photos themselves were restored correctly, but many face assignments were missing, fragmented, or incorrect afterward, while some survived. Since Recognize is supposed to preserve existing cluster assignments and manual edits during subsequent clustering, I would not expect a restore/reprocessing cycle to materially alter previously curated identities.
To Reproduce
- Use Nextcloud AIO with Recognize enabled and allow face detection/clustering to complete.
- Manually name several face clusters and correct some incorrect face assignments.
- Create a current AIO Borg backup after those manual changes have been made.
- Restore Nextcloud from that Borg backup.
- Start Nextcloud normally and allow Recognize/background jobs to resume processing.
- Open Memories/Recognize People view and compare the restored face groups with the pre-backup state.
Observed result: some person names and face assignments are preserved, but others are missing, split into new clusters, or incorrectly reassigned.
Expected result: the restored face clusters, person names, and manual corrections should remain consistent with the state captured in the backup.
Debug log
No response
- 主要言語
- PHP
- スター
- 701
- フォーク
- 68
- 平均マージ
- 18時間 9分
- マージ済み PR（30日）
- 1
環境構築
- Dockerfile・Docker Compose ファイルなし
- プルリクエストのテンプレートなし
- コントリビューションガイドを読む
はじめの一歩
- issue を最後まで読み、次にプロジェクトのコントリビューションガイドを読みます。
- 着手することを issue にコメントします — 二人が同じ作業をするのを防げます。
- リポジトリをフォークし、ブランチを切って変更します。
- issue 番号を参照したプルリクエストを送ります。
nextcloud/recognize のほかの issue
-
insertDeletion looks up recognize_fs_deletions by node_id alone, which no index covers — bulk removals scan the whole table per file対応中かも @marcelklehr が 20 日前に担当しました。 オープンbug
難易度 2/5 1〜3時間 初心者へのやさしさ 82/100
-
難易度 4/5 3〜5日 初心者へのやさしさ 48/100
-
enhancement
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-
enhancement
難易度 4/5 3〜5日 初心者へのやさしさ 45/100
-
Recognize maintenance routine unnecessarily redownloads Tensorflow CPU and GPU models every time再び着手できるかも @marcelklehr が 201 日前に担当しましたが、オープン中のプルリクエストはありません。 オープンbug
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