start for point cloud tutorial

airo-camera-toolkit/.gitignore

@@ -1,3 +1,4 @@
 airo_camera_toolkit/image_transforms/tutorial_image.jpg
 airo_camera_toolkit/calibration/saved_calibrations
 **/calibration_20**/
+notebooks/data

airo-camera-toolkit/airo_camera_toolkit/point_clouds/conversions.py

@@ -0,0 +1,16 @@
+import numpy as np
+import open3d as o3d
+from airo_typing import ColoredPointCloudType
+
+
+def pointcloud_open3d_to_numpy(pcd: o3d.geometry.PointCloud) -> ColoredPointCloudType:
+    points = np.asarray(pcd.points).astype(np.float32)
+    colors = (np.asarray(pcd.colors) * 255).astype(np.uint8)
+    return points, colors
+
+
+def pointcloud_numpy_to_open3d(pointcloud: ColoredPointCloudType) -> o3d.geometry.PointCloud:
+    pcd = o3d.geometry.PointCloud()
+    pcd.points = o3d.utility.Vector3dVector(pointcloud[0].astype(np.float64))
+    pcd.colors = o3d.utility.Vector3dVector(pointcloud[1].astype(np.float64) / 255)
+    return pcd

airo-camera-toolkit/docs/rerun.md

@@ -11,7 +11,7 @@ rerun.log_image("zed_top", image)
 rerun.log_scalar("force_z", force[2])
 ...
 ```
-See the [example notebook](./rerun-zed-example.ipynb) for more.
+See the [example notebook](../notebooks/rerun-zed-example.ipynb) for more.
 
 > :information_source: A note on starting the Rerun viewer: you can start it by calling `rerun.spawn()` from Python. However when starting Rerun like that, [there is no way to specify a memory limit](https://www.rerun.io/docs/howto/limit-ram). This quickly becomes a problem when logging images, so we recommend starting Rerun from a terminal:
 >```