The per-pixel RTSS stage gained support for two sided lighting. This is useful if you want to have a plane correctly lit from both sides or for transparency effects, as shown below:
Furthermore, PCF16 filtering support was added to the PSSM RTSS stage. This gives you softer shadows at the cost of 4x the texture lookups. The images below show crops from the ShaderSystem sample at 200% highlighting the effect
blender2ogre improved even further
Thanks to the continued work by Guillermo “sercero” Ojea Quintana, blender2ogre gained some exciting new features.
The first is support for specifying Static and Instanced geometry like this. You might wonder whether you should be using that and if yes, which variant. Therefore, he also collected the respective documentation which is available here.
The second notable feature is support for .mesh import, which might come handy if you are modding some Ogre based game or just lost the source .blend file. This feature is based on the respective code found in the Kenshi Blender Plugin (which in turn is based on the Torchlight plugin).
Then, old_man_auz chimed in and fixed some bugs when exporting to Ogre-Next, while also cleaning up the codebase and improving documentation.
Finally, yours truly added CI unit-tests, which make contributing to blender2ogre easier.
OpenAL EFX support in ogre-audiovideo
Again, contributed by sercero are some important additions to the audio part of the ogre-audiovideo project which drastically improve the useability.
The first one is that you no longer need boost to enable threading. OgreOggSound will now follow whatever Ogre is configured with.
The second one is being able to use EFX effects with openal-soft instead of the long-dead creative implementation. This enables effects like reverb or bandpass filters.
We just tagged the Ogre 13 release, making it the new current and recommended version. We would advise you to update wherever possible, to benefit from all the fixes and improvements that made their way into the new release. This release represents 2.5 years of work from various contributors when compared to the previous major 1.12 release. Compared to the last Ogre minor release (1.12.12), however we are only talking about 4 months. Here, you will mainly find bugfixes and the architectural changes that justify the version number bump.
Thanks to a contribution by Natan Fernandes there is now initial support of the Terrain Component in our C#/ Java/ Python bindings.
Python SDK as PIP package
Python programmers can now obtain a Ogre SDK directly from PyPI as they are used to with:
pip install ogre-python
Just as the MSVC and Android SDKs, it includes the assimp plugin which allows to load almost any mesh format and ImGui, so you can create a UI in a breeze. For now only Python 3.8 is covered – but on all platforms. This means you can now have a pre-compiled package for OSX and Linux too.
Thanks to some great work by Guillermo “sercero” Ojea Quintana, the blender2ogre export settings are much more user friendly now:
On top of having some context what a option might do, the exporter can now also let Ogre generate the LOD levels. This gives you the choice to
Iteratively apply blender “decimate” as in previous releases. This will generate one .mesh file per LOD level, but may result in a visually better LOD
use the Ogre MeshLOD Component. This will store all LOD levels in one .mesh file, only creating a separate index-buffer per LOD. This will greatly reduce storage compare to the above method.
But he did not stop there, blender2ogre now also exports NodeAnimationTrack based animations. To this end it follows the format introduced by EasyOgreExporter, so both exporters are compatible to each other.
To formalise this, he even extended the .scene type definition, so other exporters implementing this function can validate their output.
Needless to say, he also extended the DotScene Plugin shipped with 1.12.12 to actually load these animations.
.scene support in ogre-meshviewer
Picking up the work by Guillermo, I exteded ogre-meshviewer to load .scene file – in addition to .mesh files and whatever formats assimp knows about.
However, for now it will merely display the scene – there are no inspection tools yet.
Added Camera::setSortMode to account for rendering 2D layers instead of 3D geometry (as with 2D games)
The more notable new features will be presented in more detail in the following
Support for animated particles
Support for animating particles via Sprite-sheet textures was added. This enables a whole new class of effects with vanilla Ogre that previously required using particle-universe.
On the screenshots above, you see the Smoke demo, that was updated to showcase the new feature. However, the screenshots do not do full justice to the feature. If you are interested, it is best to download the SampleBrowser build and see the effect in action.
While at it, I fixed several bugs deep in Ogre that prevented ParticleSystems to be properly treated as shadow casters. Now you can call setCastShadows as with any other entity and things will just work (see last image).
Did you ever want to launch a Python Interpreter from your Shader or make HTTP requests per-pixel? Well, the wait is finally over – with the new TinyRenderSystem in Ogre 1.12.11 you can.
This render-system is based on the tinyrenderer project, which implements a full software-rasterizer in ~500 loc. If you are curious on how OpenGL works internally, I highly recommend taking a closer look. For Ogre this had to be doubled to about ~1350 loc, but compared to the Vulkan RenderSystem from 2.x at ~24000 loc it is still tiny (note that this is already after stripping down the v2.3 implementation).
So what do we gain by having that RenderSystem? First it is a nice stress-test for Ogre, as this is a backend implemented in Ogre itself; each Buffer uses the DefaultBuffer implementation and each Texture and RenderWindow is backed by an Ogre::Image. This makes it also a great fit for offline conversion tools, that want full access to the resources, without needing to actually access the GPU.
Next, this is really useful if you want to Unit-Test a Ogre-based application. Typically, you would need to set-up a headless rendering server (more on that below) to merely check whether your triangle is centered correctly in the frame. This is super easy now.
The screenshots on top, taken from the SampleBrowser, show you how far you can actually get with the RenderSystem. Note that there is no alpha blending, no mipmapping, no user-provided shaders and generally no advanced configuration of the rasterization. So if you are after full-featured software rasterization, you are better off with OpenGL on MESA/llvmpipe.
However, if you want to experiment with the rendering pipeline without being bound by the OpenGL API, this is the way to go. You actually can do the HTTP requests per pixel ;). Also, for creating a new RenderSystem, this is the least amount of reference code to read.
Transparent headless mode on Linux
Rendering on a remote machine over ssh just got easier! Previously ogre required a running X11 instance, which can be a hassle to come by on a machine without any monitors attached (e.g. a GPU server).
To be able to do so Ogre must be using EGL instead of GLX, to do so it must be compiled with OGRE_GLSUPPORT_USE_EGL=1. With 1.13, we will be using EGL instead of GLX by default.
Compared with the EGL support recently added in v2.2.5, the implementation is much simpler and does provide any configuration options – but on the plus side the flag above is the only switch to toggle to get it running.
As a small Christmas present, I want to show you how easy it has become to make Augmented Reality yourself thanks to Ogre and OpenCV. You should know that my other interest, besides graphics, lies with Computer Vision. The demo will not rely on proprietary solutions like ARCore or ARKit – all will be done with open-source code that you can inspect an learn from. But lets start with a teaser:
This demo can be put together in less than 50 lines of code, thanks to the OpenCV ovis module that glues Ogre and OpenCV together. Next, I will briefly walk you through the steps that are needed:
First, we have to capture some images to get by the Reality part in AR. Here, OpenCV provides us an unified API that you can use for your Webcam, Industrial Cameras or a pre-recorded video:
import cv2 as cv
imsize = (1280, 720) # the resolution to use
cap = cv.VideoCapture(0)
img = cap.read() # grab an image
then, we have to set up the most crucial part in AR: camera tracking. For this, we will use the ArUco markers – the QR-like quads that surround Sinbad. To no surprise, OpenCV comes with this vision algorithm:
adict = cv.aruco.Dictionary_get(cv.aruco.DICT_4X4_50)
# extract 2D marker-corners from image
corners, ids = cv.aruco.detectMarkers(img, adict)[:2]
# convert corners to 3D transformations [R|t]
rvecs, tvecs = cv.aruco.estimatePoseSingleMarkers(corners, 5, K, None)[:2]
If you look closely, you see that we are using a undefined variable "K" – this is the intrinsic matrix specific for your camera. If you want precise results, you should calibrate your camera to measure those. For instance using the web-service at calibdb.net, which will also just give you the parameters, if your camera is already known.
However, if you just want to continue, you can use the following values that should roughly match any webcam at 1280x720px
import numpy as np
K = np.array(((1000, 0, 640), (0, 1000, 360), (0, 0, 1.)))
So now we have the image and the according 3D transformation for the camera – only the Augmented part is missing. This is where Ogre/ ovis come into play:
# reference the 3D mesh resources
# create an Ogre window for rendering
win = cv.ovis.createWindow("OgreWindow", imsize, flags=cv.ovis.WINDOW_SCENE_AA)
# make Ogre renderings match your camera images
# create the virtual scene, consisting of Sinbad and a light
win.createEntity("figure", "Sinbad.mesh", tvec=(0, 0, 5), rot=(1.57, 0, 0))
win.createLightEntity("sun", tvec=(0, 0, 100))
# position the camera according to the first marker detected
win.setCameraPose(tvecs.ravel(), rvecs.ravel(), invert=True)
To record the results, you can use win.getScreenshot() and dump it into a cv.VideoWriter – contrary to the name, this works in real-time.
Extending the above code to use cv.aruco.GridBoard as done in the teaser video is left as an exercise for the reader as this is more on the OpenCV side.
Also, If you rather want to use ARCore on Android, there is a Sample how to use the SurfaceTexture with Ogre. Using this, you should be able to modify the hello_ar_java sample from the arcore-sdk to use Ogre.