MLX-VLM is a package for inference and fine-tuning of Vision Language Models (VLMs) on your Mac using MLX.
A Rust library integrated with ONNXRuntime, providing a collection of Computer Vison and Vision-Language models such as YOLO, FastVLM, and more.
Unofficial repository for building Florence-2 in Microsoft Azure
This project applies a modular generative AI pipeline to perform virtual staging on empty room images. It synthesizes realistic, high-quality interior furnishings while rigorously preserving the original room’s geometry, structure, and spatial consistency.
Florence-2 for object detection in Python
Florence-2 vocabulary expansion (Medium article) + Unified Sports Perception recipe (IMVC 2026 talk)
macOS computer control CLI for AI agents & OpenClaw — control any app on your Mac using natural language labels. Powered by OmniParser v2 (YOLOv8 + Florence-2). Click, type, scroll, screenshot & automate anything.
This repository provides a powerful AI-driven solution for removing objects from videos using text prompts. By integrating SAM2, Florence2, and ProPainter, the model enables precise and seamless object removal. Simply describe the objects to remove (e.g., "man, car, cap, basket"), and the AI will handle the rest with high accuracy.
OptiCaption is an AI-powered image captioning application built with Streamlit, Hugging Face Transformers, and Microsoft's Florence-2 model. Users can upload images and instantly generate accurate, context-aware captions using state-of-the-art vision-language AI.
Sample: Object Detection over a Video Stream using Microsoft's Florence-2 Model
video TO re-engineerable object manifest
Multi-domain receipt KIE using Florence-2 + LoRA + STL
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