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Iterative Deep Learning for Road Topology Extraction

Published at BMVC 2018.

Paper available on ArXiv:

Paper website:

Code instructions

Downloading datasets:

Download Massachusetts Roads Dataset from website:

Download DRIVE dataset (vessels from retina images) from website:

Download graph annotations for DRIVE dataset from website:

Set your work directory, create a directory inside named gt_dbs and copy there the downloaded datasets (roads dataset in a folder named MassachusettsRoads, DRIVE dataset in a folder named DRIVE and graph annotations for DRIVE in a folder named artery-vein).

Experiments for road topology extraction:

  1. Generate road patches for training the patch-level model: roads/patch/
  2. Train patch-level model: roads/patch/
  3. (Optional) Evaluate patch-level model: roads/patch/evaluation/
  4. Apply the patch-level model iteratively over the road test images: roads/iterative/
  5. (Optional) Evaluate iterative results: roads/iterative/evaluation/

Experiments for vessel topology extraction:

  1. Train patch-level model: vessels/patch/
  2. (Optional) Evaluate patch-level model: vessels/patch/evaluation/
  3. Apply the patch-level model iteratively over the retina test images: vessels/iterative/
  4. (Optional) Evaluate iterative results: vessels/iterative/evaluation/