Running HAMS Map Generation module#

[1]:

import os

from mapping_cli.mapper import run as mapper

File Requirements#

  1. Path to the binaries / executable named mapper_from_images

  2. Compile all the images of a map into a single folder - let’s call this folder images

  3. Generate the camera calibration file. To generate one, you can check the Camera Calibration module from the Tutorials section. Let’s call this file calib.yml

  4. Depending on the aruco markers setup on the map, add the dictionary. Typically, we use TAG16h5

  5. Marker size: Size of the printed aruco markers

Let’s add these to the variables below. If you’ve changed the names, please change the variable values in the subsequent cell

[ ]:

exec_path = 'mapper_from_images'
img_folder = "images"
calib_file = "calib.yml"
aruco_dict = "TAG16h5"
marker_size = 29.2

name = "map_example"
output_folder = "output/"

[ ]:

os.makedirs(output_folder, exist_ok=True)
mapper(exec_path, img_folder, calib_file, aruco_dict, marker_size, name, output_folder)

Visualize the Point Cloud Map#

We’ll use Open3D to visualize the generated point cloud map

[ ]:

%pip install open3d
import open3d
from open3d.web_visualizer import draw

[12]:

pcd = open3d.io.read_point_cloud("output/map_example.pcd")
draw(pcd)