pyembree ray casting acceleration

Hi @mikedh and thanks for the nice work with trimesh. I am quite new with it but it really gets in hand.

My question now is related with the ray casting approach based on the pyembree acceleration. I need to ray cast quite a few rays in a 3D scene, approx. 18060108 rays and maybe even more. Imagine that I have a scene with 16676 faces and from each face center I need to cast 1083 rays (i.e. 16676x1083 = 18060108).

As you understand I want to avoid for loops and I cast all the rays at once. Also I am using the pyembree based solution, as it states to accelerate the casting procedure in comparison to normal version, as follows:

import trimesh
import numpy as np

mesh = trimesh.Trimesh(vertices=vertices, faces=faces, face_normals=normals, process=False, use_embree=True) # create mesh from given data

intersection_points, index_ray, index_tri = mesh.ray.intersects_location(origins, drays, multiple_hits=False) # where origins are my triangle centers and drays my rays direction vectors

but this seems to perform quite slow as well, even though I am using pyembree acceleration. Is this the best I can get or I am doing something wrong?

[ttsesm]

Thanks for sharing @aluo-x. In my case though using v2.17.7 instead of v2.14 did not provide any significant acceleration.

[aluo-x]

So basically, embree 2.17.7 is as far as I know the latest compatible version with the embree python package. To use it:

1. Start a conda environment without embree, pyembree, trimesh etc.
2. git clone --recursive https://github.com/conda-forge/embree-feedstock.git
3. Modify the meta.yaml file, take care to change the version and delete the sha256 (skipping that check) or fixing it to the correct one
4. cd into the recipe folder, type conda build .
5. Wait until it finishes, will appear frozen at times
6. Take note of the output path, and conda install NEW_PKG_PATH where you put in the location of the package
7. Install the pyembree package, and trimesh package. I usually install from source (git clone recursive, then python setup.py develop or conda build depending on if it has a recipe.