😃 AI.Facial.Emotion – A .NET Library for Facial Emotion Analysis

#webdev #ai #dotnet #emotion

Ever wondered how AI can detect emotions from faces? 🤖💡

Meet AI.Facial.Emotion – a lightweight and powerful .NET library that can analyze facial emotions in real-time. Whether you're building chatbots, customer analytics, security systems, or healthcare apps, this tool makes it easy to integrate AI-powered facial analysis into your projects.

🎯 What Can It Do?

✅ Detect Emotions – Identify happiness, sadness, anger, surprise, and more.
✅ Optimized for .NET – Works with .NET 6, 7, 8, and 9.
✅ Multiple Input Formats – Accepts image URLs, Base64 strings, and file streams.

🚀 Why Use It?

✅ Fast & Efficient – AI models optimized for real-time processing.
✅ Easy Integration – Works seamlessly with ASP.NET Web API, Windows App.
✅ Privacy First – No external API calls, all processing happens locally.

📦 Installation (Super Easy!)

Just install it via NuGet:

dotnet add package AI.Facial.Emotion

📦 Mandatory ingredients

If your server runs windows operating system

dotnet add package Emgu.CV.runtime.windows

If your server runs ubuntu operating system

dotnet add package Emgu.CV.runtime.ubuntu-x64

⚡ Quick Start

1️⃣ Detect Emotion from an Image URL

var analyzer = new EmotionAnalyzer();
var result = await analyzer.AnalyzeEmotionFromUrlAsync("https://example.com/image.jpg");

Console.WriteLine($"Emotion: {result.Emotion}");

2️⃣ Detect Emotion from a Base64 Image

var base64Image = "iVBORw0KGgoAAAANSUhEUgAA...";
var result = await analyzer.AnalyzeEmotionFromBase64Async(base64Image);

Console.WriteLine($"Emotion: {result.Emotion}");

3️⃣ Detect Emotion from a File Stream

using var fileStream = File.OpenRead("image.jpg");
var result = await analyzer.AnalyzeEmotionFromStreamAsync(fileStream);

Console.WriteLine($"Emotion: {result.Emotion}");

⚡That is some results

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