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* Better Facial Recognition Clusters * Add information about the guide * Update docs/docs/features/facial-recognition.md Co-authored-by: Felix Bühler <Stunkymonkey@users.noreply.github.com> * PR Feedback --------- Co-authored-by: Felix Bühler <Stunkymonkey@users.noreply.github.com>
73 lines
2.3 KiB
Markdown
73 lines
2.3 KiB
Markdown
# Better Facial Recognition Clusters
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## Purpose
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This guide explains how to optimize facial recognition in systems with large image libraries. By following these steps, you'll achieve better clustering of faces, reducing the need for manual merging.
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---
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## Important Notes
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- **Best Suited For:** Large image libraries after importing a significant number of images.
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- **Warning:** This method deletes all previously assigned names.
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- **Tip:** **Always take a [backup](/docs/administration/backup-and-restore#database) before proceeding!**
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---
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## Step-by-Step Instructions
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### Objective
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To enhance face clustering and ensure the model effectively identifies faces using qualitative initial data.
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---
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### Steps
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#### 1. Adjust Machine Learning Settings
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Navigate to:
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**Admin → Administration → Settings → Machine Learning Settings**
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Make the following changes:
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- **Maximum recognition distance (Optional):**
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Lower this value, e.g., to **0.4**, if the library contains people with similar facial features.
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- **Minimum recognized faces:**
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Set this to a **high value** (e.g., 20 For libraries with a large amount of assets (~100K+), and 10 for libraries with medium amount of assets (~40K+)).
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> A high value ensures clusters only include faces that appear at least 20/`value` times in the library, improving the initial clustering process.
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---
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#### 2. Run Reset Jobs
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Go to:
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**Admin → Administration → Settings → Jobs**
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Perform the following:
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1. **FACIAL RECOGNITION → Reset**
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> These reset jobs rebuild the recognition model based on the new settings.
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---
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#### 3. Refine Recognition with Lower Thresholds
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Once the reset jobs are complete, refine the recognition as follows:
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- **Step 1:**
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Return to **Minimum recognized faces** in Machine Learning Settings and lower the value to **10** (In medium libraries we will lower the value from 10 to 5).
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> Run the job: **FACIAL RECOGNITION → MISSING Mode**
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- **Step 2:**
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Lower the value again to **3**.
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> Run the job: **FACIAL RECOGNITION → MISSING Mode**
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:::tip try different values
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For certain libraries with a larger or smaller amount of assets, other settings will be better or worse. It is recommended to try different values **before assigning names** and see which settings work best for your library.
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:::
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---
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