Florence2 25.12.63049

Florence2 — C# Wrapper for Microsoft’s Florence-2 Vision Model

A lightweight, easy-to-use C# library that provides access to Microsoft’s Florence-2-base models for advanced image understanding tasks — including captioning, OCR, object detection, and phrase grounding.

This project gives .NET developers a clean API to run Florence-2 locally without needing Python or the original reference implementation.

📦 NuGet: https://www.nuget.org/packages/Florence2

✨ Features

• Image Captioning Generate concise or richly detailed descriptions of images.

• Optical Character Recognition (OCR) Extract text from entire images or specific regions.

• Region-based OCR Provide bounding boxes and retrieve text only from selected areas.

• Object Detection Detect and label objects with bounding boxes.

• Phrase Grounding (optional) Highlight image regions relevant to a given phrase or textual query.

• Local Model Execution Automatically downloads and loads the Florence-2-base ONNX models.

🚀 Quick Start

1. Install the package

dotnet add package Florence2

Or get it on NuGet: https://www.nuget.org/packages/Florence2

2. Example Usage

using Florence2;

// Download models if needed
var modelSource = new FlorenceModelDownloader("./models");
await modelSource.DownloadModelsAsync();

// Create model instance
var model = new Florence2Model(modelSource);

// Load an image stream
using var imgStream = File.OpenRead("car.jpg");

// Optional text for phrase grounding (may be null)
string phrase = "the red car";

// Choose a task: Captioning / OCR / ObjectDetection / PhraseGrounding / RegionOCR
var task = TaskTypes.OCR_WITH_REGION;

// Run inference
var results = model.Run(task, imgStream, textInput: phrase);

// View results
Console.WriteLine(JsonSerializer.Serialize(results, new JsonSerializerOptions() { WriteIndented = true }));

📚 Supported Tasks

📦 Model Files

Models are downloaded automatically via FlorenceModelDownloader, but you can also supply your own model directory. The library expects Florence-2-base ONNX models compatible with Microsoft’s open-source release.

🤝 Contributing

Contributions, issues, and pull requests are welcome! If you find a bug or have a feature request, feel free to open an issue.

📄 License

MIT — see the LICENSE file for details.