Marco Musy

if you have the individual images and orientations in space you can create ```python pict1 = Picture("pic1.jpg") pict1.orientation(pic1_vector) pict1.pos(pic1_position) ... ```

You can use an `Assembly` object to treat multiple objects as a single one: ```python from vedo import * pic = Picture(dataurl + "images/dog.jpg") dz = 800 x0, x1, y0,...

You can do it with `print(assem.unpack(0).bounds()) `

You should transform the `assem` obj not the pic. I suggest not to use orientation() as it's ignoring `origin()` (bug). and also there is another small bug about `obj.transform` to...

...also it's probably easier if you use `around` to define a pivoting point instead of `origin`: ```python assem.rotate_y(+90, around=cam) assem.rotate_z(-90, around=cam) assem.rotate_y(-90, around=cam) # instead of: # assem.origin(cam) # assem.rotate_y(+90)...

sorry I don't understand the question.

I think this is a problem with vtk that has been solved in vtk9.2.2, so I would try: `pip install vtk -U`

Hi, sorry for the late reply, have you tried to use `.subsample(0.01, absolute=True)` ? You cannot control a priory the exact number of output points though.

Just pushed a version with a fix for `absolute=True`: ```python from vedo import * tmsh = TetMesh(dataurl+"limb_ugrid.vtk") pts1 = Points(tmsh) print(pts1.N()) pts2 = pts1.clone().densify() # artificially increase density pts1.subsample(100, absolute=True)...

well it very much depends if you consider "closed" clouds (clouds which may define a surface) or "dense" clouds where points are scattered in the full 3d space... the the...