Skip to content

dolphinium/rescuenet-damaged-building-detection

Repository files navigation

RescueNet: A High Resolution UAV Semantic Segmentation Dataset for Natural Disaster Damage Assessment

https://www.kaggle.com/datasets/yaroslavchyrko/rescuenet

Test the model on HF Spaces working with best weights found:

https://huggingface.co/spaces/dolphinium/rescuenet-damaged-building-detection

Check experiment results @cometML platform:

https://www.comet.com/dolphinium/rescuenet-damaged-building-detection/view/new/panels

Check documentation pdf:

documentation

Model comparison table:

model_comparison_table

Technologies and frameworks used on this project:

  • Yolov5-8-10
  • CometML(For monitoring and maintaining models performance)
  • Huggingface Spaces(For hosting and deploying models)
  • Gradio(For building a web app)
  • Folium(For mapping)
  • PyEXIFTool(For extracting metadata from drone imagery)

Known Issues:

TODOS:

  • Fine-tuning the model.
  • Creating requirements.txt for the project.
  • Editing the readme for a better documentation.
  • Making the geolocations more precise.
  • Cleaning up and creating a new repository for hosting.