Bridge element segmentation from inspection videos

This is the implementation code for the paper, "A semi-supervised self-training method to develop assistive intelligence for segmenting multiclass bridge elements from inspection videos".

Getting Started

• Install the required dependencies: (for reference see how_to_install.pdf )
• Dataset: Download the initial dataset from here.
• weights: Download pre-trained resnet_50 coco weights and trained weights for bridge element segmentation from here.
• custom.py : this code is used for loading data and training the model
• Training.ipynb: loading the weight and calling the training function
• inference.ipynb: this code is used for inferencing.
• mrcnn/visualize.py : this code is used for visualizing the segmented bridge elements with mask.

Citation

If you use this repository, please cite the following paper:

@article{karim2021semi,
  title={A semi-supervised self-training method to develop assistive intelligence for segmenting multiclass bridge elements from inspection videos},
  author={Karim, Muhammad Monjurul and Qin, Ruwen and Chen, Genda and Yin, Zhaozheng},
  journal={Structural Health Monitoring},
  pages={14759217211010422},
  year={2021},
  publisher={SAGE Publications Sage UK: London, England}
}

Note that part of the codes are referred from Mask RCNN project.