# AI Face Expressions

Classify facial expressions per face (neutral/happy/sad/angry/fearful/disgusted/surprised)

> Canonical page: https://elysiatools.com/en/tools/ai-face-expressions

- **Category:** AI Tools

- **Keywords:** face, expressions, emotion, vision

## Overview

The AI Face Expressions tool uses vision AI to detect faces in uploaded images and classify their expressions into seven categories: neutral, happy, sad, angry, fearful, disgusted, and surprised. It returns structured JSON output for each face, enabling automated emotion analysis.

## Inputs

- **Image File** (file): Upload an image
- **Minimum Confidence (0-1)** (number): 0.5
- **Max Faces** (number): Leave empty for all

## When to use

- When you need to analyze emotional responses in photos for user research or marketing insights.
- For automating content moderation by identifying images with negative expressions like anger or fear.
- To enhance interactive applications by detecting user emotions from facial expressions in images.

## How it works

- Upload an image file containing one or more faces in supported formats like JPEG or PNG.
- The AI model processes the image to detect faces and classify each expression based on visual features.
- Optionally adjust parameters such as minimum confidence threshold or maximum number of faces to analyze.
- Receive a JSON result with expression classifications and confidence scores for each detected face.

## Use cases

- Analyzing customer emotions from photos in feedback surveys to improve product design.
- Filtering user-generated content on social platforms to flag images with negative expressions.
- Assisting in psychological studies by quantifying facial expressions from participant images.

## Frequently asked questions

### What image formats are supported?

The tool supports common image formats including JPEG, PNG, and GIF, with a maximum file size of 30MB.

### How many faces can it detect per image?

It can detect up to 100 faces per image, but you can limit this using the maxFaces option.

### What expressions does the tool recognize?

It classifies expressions into seven types: neutral, happy, sad, angry, fearful, disgusted, and surprised.

### Can I adjust detection sensitivity?

Yes, use the minConfidence parameter to set a threshold from 0.05 to 0.99, filtering out low-confidence results.

### Is the output easy to integrate?

Yes, the result is in JSON format, making it simple to parse and use in applications or data pipelines.

## Related tools

- [AI Face Landmarks](https://elysiatools.com/en/tools/ai-face-landmarks): Detect facial landmarks (68 points) and return coordinates for each face
- [AI Face Age & Gender](https://elysiatools.com/en/tools/ai-face-age-gender): Estimate age and gender for each detected face
- [AI Face Detection](https://elysiatools.com/en/tools/ai-face-detection): Detect faces in an image and return bounding box coordinates
- [AI Face Compare (1:1)](https://elysiatools.com/en/tools/ai-face-compare): Compare two images, output embedding distance and match boolean by threshold, only compare the first face in each image
- [AI Face Align & Crop](https://elysiatools.com/en/tools/ai-face-align-crop): Detect, align, and crop faces into individual images (zip when multiple)
- [AI Face Descriptors](https://elysiatools.com/en/tools/ai-face-descriptors): Generate 128D face embeddings for each detected face
- [AI Face Recognition (Gallery)](https://elysiatools.com/en/tools/ai-face-recognition): Build a gallery from labeled faces and recognize faces in a target image
- [AI Image Smart Enhance](https://elysiatools.com/en/tools/ai-image-enhance): Intelligently analyze and enhance image quality using AI vision models

## Samples

- [Hugging Face JavaScript Samples](https://elysiatools.com/en/samples/huggingface-js): Hugging Face JavaScript/TypeScript examples using Transformers.js for NLP, computer vision, and multimodal tasks in browser and Node.js
- [Hugging Face Deploy Samples](https://elysiatools.com/en/samples/huggingface-deploy): Hugging Face model deployment examples including Transformers, Diffusers, and Gradio applications with Docker and cloud deployment
- [Android Image Processing Java Samples](https://elysiatools.com/en/samples/android-image-processing-java): Android Java image processing examples including reading/saving images, scaling, and format conversion
- [Android Image Processing Kotlin Samples](https://elysiatools.com/en/samples/android-image-processing-kotlin): Android Kotlin image processing examples including reading/saving images, scaling, and format conversion

## Related content

- [AI Face Analysis: Detection, Comparison, and Recognition Workflows](https://elysiatools.com/en/hubs/ai-face-detection-recognition-workflows): Separate face detection and alignment from descriptor comparison, gallery recognition, and expression or age-gender estimation, with practical privacy and error boundaries.