face-grouper 0.3.0

A CLI tool that groups photos and videos by person using offline face recognition.

face-organizer

A CLI tool that groups photos and videos by person using offline face recognition.

Installation

# Default (dlib backend, photos only)
pipx install face-grouper

# With video support
pipx install "face-grouper[video]"

# With ArcFace support (more accurate, recommended)
pipx install "face-grouper[arcface]"

# With both video + ArcFace
pipx install "face-grouper[video,arcface]"

# Upgrade (core only)
pipx upgrade face-grouper

Compile error? Install CMake first: brew install cmake (macOS), sudo apt install cmake build-essential (Linux), or Visual Studio Build Tools (Windows).

Don't have pipx? brew install pipx && pipx ensurepath (macOS) or pip install --user pipx && pipx ensurepath (Linux/Windows).

Usage

Photos (fgroup group)

# ⭐ Quick start — named clusters, flat output, include single-photo people
fgroup group ./photos --ref-dir ./refs --output ./sorted --backend arcface --mode rename --min-samples 1

# Basic grouping into person_1/, person_2/, ... subfolders
fgroup group ./photos --output ./sorted

# Pass individual files
fgroup group a.jpg b.jpg c.jpg --output ./sorted

# Disable multi-face export (legacy: one output per photo)
fgroup group ./photos --output ./sorted --no-multi-export

Originals are never modified. Supported formats: .jpg .jpeg .png .webp .bmp

Videos (fgroup video)

# Group short clips by person
fgroup video ./clips --output ./sorted

# Allow longer videos (default 15s, max 120s)
fgroup video ./clips --output ./sorted --max-duration 30

# Use ArcFace for better accuracy
fgroup video ./clips --output ./sorted --backend arcface

# Preview without copying
fgroup video ./clips --output ./sorted --dry-run

Supported formats: .mp4 .mov .avi .mkv. Requires pip install 'face-grouper[video]'.

Videos exceeding --max-duration are skipped and copied to output/skipped/. A video with multiple people is copied into each relevant person folder.

Parameters

fgroup group

Option	Default	Description
INPUTS...	(required)	Directories or image files to scan (recursive)
--output / -o	(required)	Output directory
--backend	dlib	Face recognition backend. dlib: fast, 128-D embeddings, works offline, good for frontal faces — pair with --model cnn for better accuracy. arcface: 512-D embeddings, more accurate across varied lighting/angles, but downloads around 300 MB (buffalo_l model) on first run to ~/.insightface/; --model and --upsample are ignored for this backend
--mode	group	group → person_N/ subfolders; rename → flat person_N_img_M.ext files
--eps	0.5	DBSCAN max distance between embeddings for same person. Raise to merge split clusters, lower to split merged ones. Use --debug to calibrate
--min-samples	2	Min photos to form a cluster. People below threshold go to unknown/. Set to 1 to keep solo faces
--ref-dir	none	Folder of named reference images. john.jpg → cluster named john. Multiple photos per person supported: john_1.jpg, john_2.jpg, … all map to john
--no-multi-export	false	Only use the largest face per photo. By default every detected face is exported independently — a photo with two people lands in both person folders.
--model	hog	dlib only: hog (fast) or cnn (accurate, GPU recommended)
--upsample	1	dlib only: upsample N times before detection — finds smaller faces, ~4× cost per level
--dry-run	false	Preview planned operations without copying anything
--debug	false	Print pairwise distance stats to help choose --eps

fgroup video

Option	Default	Description
INPUTS...	(required)	Directories or video files to scan (recursive)
--output / -o	(required)	Output directory
--mode	group	group → person_N/ subfolders; rename → flat person_N_vid_M.ext files
--backend	dlib	dlib or arcface — same as fgroup group
--model	hog	dlib only: hog or cnn
--upsample	1	dlib only: upsample N times before detection
--eps	0.5	DBSCAN epsilon — same as fgroup group
--min-samples	2	Min face detections to form a cluster
--ref-dir	none	Folder of named reference images — same behaviour as fgroup group
--max-duration	15.0	Max video length in seconds (1–120). Videos over this go to skipped/. Warns if > 30s
--dry-run	false	Preview planned operations without copying anything
--debug	false	Print pairwise distance stats to help choose --eps

Dev mode

git clone https://github.com/your-username/face-organizer.git
cd face-organizer

# Install with all optional extras for full local development
pip install -e ".[arcface,video]"

# Verify the CLI is wired up
fgroup --help

Changes to face_grouper/*.py take effect immediately — no reinstall needed. Only re-run pip install -e . if you change pyproject.toml (e.g. new dependency or entry point).

macOS compile error? Install CMake first: brew install cmake