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---
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!
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