KdO-Net

This repository represents the official implementation of KdO-Net.

Instructions

Requirements

The code is based on Python3 and is implemented in Tensorflow. The required libraries can be easily installed by runing

pip install -r requirements.txt

in your environment.

Training

To train the network with the following code：

cd KdO-Net
python train.py

The training data should be saved in folder data/train/trainingdata.The training generated model file is saved in ./models/ and the tensorboard log will be saved in ./KdO-Net/logs/.For more training options please see ./KdO-Net/core/config.py.

Evaluation

The source-code for the performance evaluation on the 3DMatch data set is available in the ./KdO-Net/Test/evaluate.py.Evaluate the model e.g., using

cd KdO-Net
python test.py
cd Test
python evaluate.py

test.py is used to infer the feature descriptors, run the evaluate.pyto compute the recall ,precision et. al.

Before running test.py, the preprocessed test set data needs to be saved in folder ./KdO-Net/data/3DMatch/test. For more options in runing the inference please see ./KdO-Net/core/config.py.

Demo

To carry out the demo, please run

cd KdO-Net
python demo.py

About

If you have any questions, please feel free to discuss in the issues.