Another Implementation for the occlution filter

[KyriakosChris]

Hello,

I had some issues with your filter and wanted to achieve nearly 100% accuracy. Thus, I used a similar approach to yours. I wanted to get images from drones, like the VisDrone dataset. My method involved spawning cameras randomly above the map at heights between 50-80 meters. I used a function to get the bounding box of each vehicle from all camera angles and then performed ray casting. I identified the closest ray from the camera, which returned the location and type of the object. If the type was a vehicle, we were 100% certain it needed to be included.

If you have many types and may miss something, you can use distance: calculate the distance between the closest ray and the camera, compare it with the end of the ray_point (which is the vehicle or your specified type), and if they are almost equal, you should add it. Finally, by removing the vehicles based on angle and distance as you have already implemented, I was able to create a perfect simulated dataset.

If you like the idea, I can send you some code to test it yourself and maybe add it as a new function in your code. I am using carla 0.9.15 and this version worked perfectly. Here is a sample of a generated image with the annotations