The official repo of the CVPR 2020 paper "VecRoad: Point-based Iterative Graph Exploration for Road Graphs Extraction"
OSM Dataset Baidu Netdisk with code: 2xoe
RP-Net Baidu NetDisk with code: 9nk4
apls-visualizer-1.0 Baidu Netdisk with code: ugbz | Google Drive
- Download OSM Dataset, RP-Net and APLS-visualizer into
data/downloads
. sh prepare_data.sh
conda could install the right version of rtree
.
pytorch>=0.4.1
rtree==0.8.3
numpy==1.16.3
pillow==6.0.0
opencv-python==4.1.0.25
networkx==2.3
shapely==1.6.4
pickle==0.7.5
scikit-image==0.15.0
pyyaml==5.1
python infer.py --config configs/default.yml
Junction Metric (Golang needed). Please refer to roadtracer for more details.
python eval/eval_junction_metric.py \
--graph_dir data/graphs/vecroad_4/graphs_junc/ \
--gt_dir data/input/graphs/ \
--save_dir data/graphs/vecroad_4/ \
--file_name graphs_junc_jf1.csv
APLS Metric (Java needed). Please refer to Spacenet Challenge for more details.
python eval/graphs2wkt.py \
--graph_dir data/graphs/vecroad_4/graphs_junc/ \
--save_dir data/graphs/vecroad_4/graphs_junc_wkt/
python eval/eval_apls_metric.py \
--apls_path eval/apls-visualizer-1.0/visualizer.jar \
--wkt_dir data/graphs/vecroad_4/graphs_junc_wkt/ \
--gt_dir data/input/graphs_test_wkt/ \
--save_dir data/graphs/vecroad_4/ \
--file_name graphs_junc_apls.csv
Pixel Metric (C++ needed). Please refer to ssai-cnn for more details.
python eval/graphs2seg.py \
--graph_dir data/graphs/vecroad_4/graphs_junc/ \
--save_dir data/graphs/vecroad_4/graphs_junc_seg/ \
--region_file data/input/regions/test_regions.txt \
--img_size 8192 \
--thickness 8
python eval/eval_pixel_metric.py \
--pred_dir data/graphs/vecroad_4/graphs_junc_seg \
--gt_dir data/input/mask_test \
--steps 1 \
--relax 3 \
--num_workers 12 \
--thresh 128 \
--crop 0
If you find this work or code is helpful in your research, please cite:
@inproceedings{VecRoad_20CVPR,
title={VecRoad: Point-based Iterative Graph Exploration for Road Graphs Extraction},
author={Yong-Qiang Tan and Shanghua Gao and Xuan-Yi Li and Ming-Ming Cheng and Bo Ren},
booktitle={IEEE CVPR},
year={2020},
}
Our source code is free for non-commercial usage. Please contact us if you want to use it for comercial usage. (yoqitan -AT- outlook -DOT- com)