AI Face Align & Crop

AI Face Align & Crop | Online Free Tool | Elysia Tools

Tool usage guide

Learn when to use this tool, what it supports, and how real users apply it.

Key facts

Category: AI Tools
Input types: file, number
Output type: file
Sample coverage: 4
API ready: Yes

Overview

This AI-powered tool detects faces in uploaded images, aligns them based on facial landmarks, and crops each face into a separate image. When multiple faces are found, they are automatically packaged into a zip file for convenient download.

When to use

When you need to extract individual faces from group photos or event pictures.
For preparing aligned face images for machine learning datasets or facial recognition systems.
To create consistent profile pictures or avatars from larger images without manual cropping.

How it works

1Upload an image file containing one or more faces.
2The AI model scans the image to detect faces, using an adjustable confidence threshold.
3Each detected face is aligned using facial landmark detection for uniform orientation.
4Faces are cropped into individual images and saved; if multiple, they are compressed into a zip file.

Use cases

Batch processing of event photos to extract attendee headshots for identification or records.
Generating training data for AI models by creating a dataset of aligned, cropped face images.
Automating the creation of individual portraits from family or team pictures for social media or profiles.

Examples

1. Extract Faces from a Team Photo

Background

A project manager has a group photo of the team and needs individual headshots for the company directory.

Problem

Manually cropping each face is tedious and often results in misaligned or inconsistent images.

How to use

Upload the team photo, set minConfidence to 0.6 to capture all faces reliably, and leave maxFaces empty to process everyone.

minConfidence: 0.6, maxFaces: (empty)

Outcome

Each team member's face is detected, aligned, and cropped into a separate image, delivered as a zip file for easy download.

2. Prepare Face Dataset for Model Training

Data Scientist

Background

A data scientist is building a facial recognition model and needs a clean set of aligned face images from raw photos.

Problem

Raw images have faces in varying poses and sizes, which can reduce model accuracy if not standardized.

How to use

Upload a batch of images, set minConfidence to 0.8 for high-quality detections, and limit maxFaces to 1 per image to focus on primary subjects.

FAQ

What image formats are supported?

The tool accepts common image formats like JPEG, PNG, and others as specified in the upload option.

How does the confidence setting affect detection?

The minimum confidence value (0-1) filters detections; higher values reduce false positives but may miss some faces.

Can I limit the number of faces processed?

Yes, use the max faces option to set a limit; leave it empty to detect all faces in the image.

What happens if no faces are detected?

The tool will return an error message or an empty result, prompting you to check the image or adjust settings.

Is the original image quality preserved in the output?

Yes, faces are cropped without compression loss, maintaining the original resolution and quality.

minConfidence: 0.8, maxFaces: 1

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Inputs

Result

Learn when to use this tool, what it supports, and how real users apply it.

Key facts

Overview

When to use

How it works

Use cases

Examples

1. Extract Faces from a Team Photo

2. Prepare Face Dataset for Model Training

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