Requirements
install python3.5.2,pytorch 1.1+,ninja-build:
sudo apt-get install ninja-build
Install python packages:
pip install tensorboardX scipy easydict pyyaml
Dataset
To train and eval the network, you should download Scannet, and then, you should use the code to pre-process (e.g., generate the grund truth label) the dataset. if you want to augment the dataset, install:
pip install imgaug
and then, run:
python3 aug_scannet.py
Training
To train the model(s) in the paper, run this command:
python3 train_eval.py --cfg your_yaml_path
📋Example python3 train_eval.py --cfg experiments/vgg16_scannet.yaml
Evaluation
To evaluate the model on Scannet, run:
python3 eval.py --cfg your_yaml_path
📋Example python3 eval.py --cfg experiments/vgg16_scannet.yaml
Visualization
To view the matching results, run:
python3 test.py --cfg experiments/vgg16_scannet.yaml --model_path params_last.pt --left_img test_data/000800.jpg --right_img test_data/000900.jpg --left_lines test_data/000800.txt --right_lines test_data/000900.txt
📋the pre-trained model trained on scannet will be provided when the paper is accepted. A example is:
