Advanced People Management UI – Completed Implementation & Walkthrough

[Muskan121622]

Hi @rahulharpal1603

I’d like to share a detailed walkthrough of the Advanced People Management UI that I’ve completed, including what existed earlier, what was missing, and what has now been fully implemented, along with UI proof through screenshots.

This work focuses on making People / Face cluster management usable, scalable, and production-ready.

Previous State (Before My Implementation)

Earlier, the People Management feature was functional but limited:

What worked:

Faces were automatically detected and grouped into clusters.

Each cluster was shown as Person xxxx.

Basic renaming of a person was supported.

Backend already had partial support for:

Renaming clusters

Merging clusters (logic only)

Ignoring clusters (data-level)

What was missing:

❌ No dedicated People Management UI

❌ No way to merge clusters from the UI

❌ No clear ignore / restore flow

❌ No confirmation or visual feedback for merges

❌ Poor discoverability of people-related actions

❌ Cluster names like Person 7154, Person 6ee4 were confusing

❌ Users had no control over wrongly detected or duplicate faces

Result:
The system worked internally, but users had very little control over people data.

What I Have Implemented (Current State)

I designed and implemented a complete Advanced People Management experience, building on top of the existing backend capabilities.

1. Merge Clusters – Visual Merge Mode

Introduced a Merge Mode.

Users can:

Select multiple person clusters

Merge them into a single person

Clear visual indicators show:

Selected clusters

Merge confirmation action

This solves the duplicate person problem, especially when AI splits the same person into multiple clusters.

3. Ignore & ♻ Restore People

Added Ignore Person action directly in the Person view.

Ignored people:

Are hidden from the main gallery

Do not appear in AI tagging results

Can be safely restored later without losing data.

This gives users full control over unwanted or irrelevant faces.

4. Enhanced Renaming Experience

Improved the renaming UI:

Inline editable input

Instant save feedback

Names persist across reloads and sessions.

Eliminates confusion caused by auto-generated IDs.

People feel like real identities, not random clusters.

Backend Work & Verification

While implementing the UI, I deeply analyzed the backend:

Confirmed backend already supports:

Merge logic

Ignore flags

Persistent renaming

Verified how ignored clusters are excluded from queries.

Added missing API wiring and safety checks.

Ensured all operations are persistent and reversible.

Testing & Documentation

Tested merge, ignore, restore, and rename flows end-to-end.

Documented the complete feature walkthrough in walkthrough.md.

Updated my task list to reflect completion of:

Research

UI implementation

Verification phase

Final Outcome

Before → Passive AI-generated clusters
After → User-controlled, production-ready People Management

This upgrade:

Improves usability

Reduces confusion

Gives users real ownership of their people data

Scales well for large photo libraries