[QUESTION] Project shots over flat plane.

[Matesanz]

Hello, and thank you for the project and your efforts on this project. :slightly_smiling_face:

I would like to know if you could, please, throw some light to how to project all the images over a plane. More precisely I have some drone pictures taken at high altitude (no perspective affected) and I would like to put them all together like it can be seen in the viewer. I'm setting the use_altitude_tag to True in the config during the reconstruction.

My code so far is:

project_path = </path/to/project>
data = DataSet(project_path)

rec: Reconstruction = data.load_reconstruction()[0]
ref: TopocentricConverter = rec.reference

# Plane will be created at the mean altitude (z position) of 3D points
points = rec.get_points().values()
plane_altitude: LandmarkView = np.median([p.coordinates[2] for p in points])

for shot_id in rec.get_shots():

    shot: Shot = rec.shots[shot_id]
    cam: Camera = shot.camera
    pose: Pose = shot.pose

   # Scale

    x,y,z = pose.get_origin()
    z_scale = z - plane_altitude

   # Rotation

    # I think the main problem is here (?):
    # I ignore the Z axis because I suppose shot is "almost" facing down
    rot_matrix = pose.get_rotation_matrix()[:2,:2].T
    rot_matrix /= z_scale   # Set scale at floor level so images have correct size (is it correct?)

    # Translation

    x,y,z = ref.to_lla(x,y,z)  # Convert to GPS coordinates

    # Internal camera parameters

    K = cam.get_K()

    # Create affine to georeference image

    affine = np.eye(3)
    affine[:2,:2] = rot_matrix  # Insert rotation and scale
    affine[:2,2] = np.array((x,y))  # Insert translation

    K_inv = np.linalg.inv(K) 
    affine = affine.dot(K_inv)  # Add K to image

    ## Follows the code to insert Affine into TIF ##

Is this approximation correct? Once this is solved I would really like to help improving OpenSFM docs. Thank you in advance.

[fabianschenk]

Hi @Matesanz ,

Is the example image from the Mapillary JS viewer? If yes, why don't you just copy the "visualization" code from there? I don't really get what you want to achieve but if you just want a PCL of the images on a plane, you could try the following:

- iterate through the shots
- read the image of the each shot
- for each point in the image (x,y):
  -  unproject it a 3D point that is `altitude` or some arbitrary `z` away. `np.linalg.inv(K).dot([x,y,1])*altitude`. You now have a pcl, where each point is `altitude` away from the camera but you're still in the camera coordinate system
  - transform the 3D pcl to the world using the `shot.pose.get_cam_to_world().dot(np.hstack([pt3d,1]))`. Now you have the planar PCL in the world.

Best, Fabian

[Matesanz]

Thank you so much for the help.

I will try your algorithm out and let you know. :slightly_smiling_face:

I want to thank you (and the community) improving the docs that opensfm already has. I knew a little about the topic and still I had to struggle a bit into the code. And I think my experience will help others willing to use OpenSFM. Just let me know how to do it and I will be pleased to do it. :ok_hand:

Nice Regards.

[Matesanz]

I've seen that the depthmap stage generates a bunch of files for every image. If I load the clean version it comes with 3 different fields: plane, depth, and score.

Is plane suppose to be the x,y,z values in camera coordinates for every pixel?

I've plotted the z values and the result doesn't look like the one stored in the depth field.

z in plane	depth

@fabianschenk Could you please tell me what do they represent? Thanks in advance

[pierotofy]

A bit off-topic perhaps, but you could use a tool such as ddb geoproj to do this: https://docs.dronedb.app/commands/geoproj.html

(disclaimer: I wrote the tool).

[Matesanz]

Hello @pierotofy and thank you so much for the answer. (btw: I admire you so much for your work at ODM.)

I'll check it out :)