title: Inpainting of sparse 2D LiDAR image to dense depth image
body: <p>I'm working on a classification problem (object classification for autonomous vehicle). I use a dataset from KITTI which provide LiDAR and camera data and want to use both of this data to perform the task.</p>
  <p>3D LIDAR data is projected onto the coordinate system of the RGB image resulting in a sparse LiDAR image:</p>
  <p><img src="https://web.archive.org/web/20190722023447/https://image.noelshack.com/fichiers/2019/23/3/1559749785-lidar-depth-car.png" alt="sparse" /></p>
  <p><img src="https://web.archive.org/web/20190722023452/https://image.noelshack.com/fichiers/2019/23/3/1559750098-car.png" alt="original_image" /></p>
  <p>Each pixel is encoded using depth (distance to the point : sqrt(X² + Y²), scaling between 0 and 255).</p>
  <p>In order to obtain better results for my CNN, I need a dense LiDAR image, anyone know how to do it using Python?</p>
  <p>I would like to obtain something like this</p>
  <p><img src="https://web.archive.org/web/20190722023503/https://image.noelshack.com/fichiers/2019/23/3/1559750299-dense.png" alt="goal" /></p>