---
title: TreeFormer
emoji: 🚀
colorFrom: purple
colorTo: red
sdk: gradio
sdk_version: 4.32.2
app_file: app.py
pinned: false
license: mit
---

# TreeFormer

This is the code base for IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING (TGRS 2023) paper ['TreeFormer: a Semi-Supervised Transformer-based Framework for Tree Counting from a Single High Resolution Image'](https://arxiv.org/abs/2307.06118)

<img src="sample_imgs/overview.png">

## Installation

Python ≥ 3.7.

To install the required packages, please run:


```bash
  pip install -r requirements.txt
```
    
## Dataset
Download the dataset from [google drive](https://drive.google.com/file/d/1xcjv8967VvvzcDM4aqAi7Corkb11T0i2/view?usp=drive_link).
## Evaluation
Download our trained model on [London](https://drive.google.com/file/d/14uuOF5758sxtM5EgeGcRtSln5lUXAHge/view?usp=sharing) dataset.

Modify the path to the dataset and model for evaluation in 'test.py'.

Run 'test.py'
## Acknowledgements

 - Part of codes are borrowed from [PVT](https://github.com/whai362/PVT) and [DM Count](https://github.com/cvlab-stonybrook/DM-Count). Thanks for their great work!