A Web-based Prototype System for Deforestation Detection on High-resolution Remote Sensing Imagery with Deep Learning

1. Setup

1.1 Third-party Packages Installation

• Environment: Python 3 and above
• In order to run the OpenForestMonitor system, you should install these third-party packages:

pygis
geemap
streamlit
osgeo
onnxruntime
opencv-python
numpy
tqdm
zipfile
multiprocessing
scikit-image

• if you have Nvidia GPUs, you can install onnxruntime-gpu to accelerate computing

1.1.1 install AItool_fast library

1. cd .\Server_Side\Tool to find whl files
2. Using pip tool to install AItool_fast library
pip install AItool_fast-0.1-cp310-cp310-win_amd64.whl (the AItool_fast surpported python 3.9, python 3.10, python 3.11 in Windows 10/11 system)
3. test AItool_fast
   import AItool_fast

1.2 Deep learning model download

The deforestation model is over 150MB, you can download it from https://drive.google.com/drive/folders/1etsHlRJgT712Oq2HyQ321cFrd_ZkjacU?usp=share_link

And then, copy these models into \Server_Side\RS_change_detection_model.

2. Start Client side

To start the Client side, just use one command line:

streamlit run deforestation_Monitor.py  --server.maxUploadSize 4000

3. Start Server side

To start the Server side, also only use one command line, as follows:

python main_server.py

then, enjoy OpenForestMonitor system!

4. Citation

@article{title={A Web-based Prototype System for Deforestation Detection on High-resolution Remote Sensing Imagery with Deep Learning}, author={Zhipan Wang}, journal={2023}, year={2023} }