https://github.com/HAAClassic/TreeFormer

https://github.com/HAAClassic/TreeFormer

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• Host: GitHub
• URL: https://github.com/HAAClassic/TreeFormer
• Owner: HAAClassic
• Created: 2023-02-22T12:56:39.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2023-09-02T04:37:54.000Z (about 1 year ago)
• Last Synced: 2024-08-02T15:30:14.689Z (3 months ago)
• Language: Python
• Size: 720 KB
• Stars: 40
• Watchers: 2
• Forks: 6
• Open Issues: 1
• Metadata Files:
  • Readme: README.md

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README

        

# 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)



## 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!