We propose AdaContour, an adaptive contour descriptor that uses multiple local representations to desirably characterize complex shapes. After hierarchically encoding object shapes in a training set and constructing a contour matrix of all subdivided regions, we compute a robust low-rank robust subspace and approximate each local contour by linearly combining the shared basis vectors to represent an object.
AdaContour is able to represent shapes more accurately and robustly than other descriptors while retaining effectiveness.
conda create -n AdaContour python=3.7
conda activate AdaContour
pip install opencv-python
conda install pytorch==1.7.0 torchvision==0.8.0 torchaudio==0.7.0 cudatoolkit=11.0 -c pytorch
conda install scikit-image
For a quick understanding of how hierarchical representation works, we provide a demo script that runs AdaContour on a sample data point.
python demo.py --image_id 1
This will run the demo on the first sample data point in sample_data. The output will be saved in the output folder, which looks like this:
And it prints the following output:
=================================================================
image id = 1
solidtiy = 0.57
eccentricity = 0.78
area ratio = 0.12 (20363 / 173056)
=================================================================
depth = 0, iou = 0.78, # of centers = 1
depth = 1, iou = 0.86, # of centers = 2
depth = 2, iou = 0.92, # of centers = 4
depth = 3, iou = 0.95, # of centers = 7
depth = 4, iou = 0.97, # of centers = 12
depth = 5, iou = 0.98, # of centers = 18
Done!All results saved in output/
=================================================================
Please follow dnjs3594/Eigencontours for dataset preparation first.
For the rest of the pipeline and usage, please refer to cmds.txt.
@article{ding2024adacontour,
title={AdaContour: Adaptive Contour Descriptor with Hierarchical Representation},
author={Ding, Tianyu and Zhou, Jinxin and Chen, Tianyi and Zhu, Zhihui and Zharkov, Ilya and Liang, Luming},
journal={arXiv preprint arXiv:2404.08292},
year={2024}
}
The code is largely based on dnjs3594/Eigencontours.