Count Anything

--- license: apache-2.0 library_name: pytorch tags: - computer-vision - object-counting - text-guided-counting - open-world-counting - count-anything - object-detection - zero-shot - open-vocabulary --- <h1 align="center">Count Anything</h1> <p align="center"> <strong>Text-guided object counting across domains with instance-grounded point predictions</strong> </p> <p align="center"> <a href="https://mengqi-lei.github.io/count-anything-projectpage/"><img src="https://img.shields.io/badge/Project-Page-purple" alt="Project Page"></a> <a href="https://huggingface.co/MengqiLei/count-anything"><img src="https://img.shields.io/badge/Hugging%20Face-Model-yellow" alt="Hugging Face Model"></a> <a href="https://huggingface.co/spaces/MengqiLei/count-anything-demo"><img src="https://img.shields.io/badge/Hugging%20Face-Demo-orange" alt="Hugging Face Demo"></a> <a href="https://arxiv.org/abs/2605.30846"><img src="https://img.shields.io/badge/arXiv-2605.30846-b31b1b" alt="arXiv Paper"></a> <a href="assets/paper/Count-Anything.pdf"><img src="https://img.shields.io/badge/Paper-PDF-blue" alt="Paper PDF"></a> <a href="mailto:mengqi-lei@163.com"><img src="https://img.shields.io/badge/Contact-Email-green" alt="Contact Email"></a> </p> <p align="center"> <img src="assets/readme/count_anything_poster.jpg" alt="Count Anything poster" width="100%"> </p> <p align="center"> <strong>✨Play with the demo: <a href="https://huggingface.co/spaces/MengqiLei/count-anything-demo">🔗Huggingface Demo</a></strong> </p> ## Overview This repository introduces **Count Anything**, a generalist model for text-guided object counting across domains. Given an image and a natural-language query, Count Anything returns an instance-grounded set of target points whose cardinality gives the count. This formulation unifies category-conditioned counting with interpretable spatial localization. ### Cross-domain Text-guided Counting - Study text-guided object counting across domains, where users specify the target with a category name or a natural-language query. - Construct **CLOC**, a Cross-domain Large-scale Object Counting dataset that reorganizes diverse public data sources into a unified counting benchmark. - Cover six visual domains: General Scene, Remote Sensing, Histopathology, Cellular Microscopy, Agriculture, and Microbiology. ### Dual-granularity Instance Enumeration - Adopt disc...

Source context: 0 downloads · 10 likes · Pipeline object-detection · Library pytorch · Repo MengqiLei/count-anything