Now one no longer needs to match the sensor dimensions with the render dimensions manually.
IMPORTANT NOTE: if you were using AUTO before with mismathing sensor aspect ratio (comparing to the render dimensions)
this will change your render! We can doversion this, but apart from Tube project I don't know if anyone else
is using this yet (part due to this bug and the only recently fixed 3dview preview aspect ratio).
That should help more artists to take advantage of this fantastic Blender feature.
It still helps to know the parameters of kwnown cameras/lens though.
For example:
Nikon DX2S with a 10.5mm fisheye can be set with:
Render resolution: 4288 x 2848
Sensor 23.7 x 15.70 (15.70 can be ommitted if AUTO is used as fit method)
Note: some cameras render different sizes according to the recording mode.
For example, a Red Scarlet in 5k (@12 fps) can render a full circular fisheye with a sigma 4.5 lens.
The same camera in the 30fps recording mode renders 4k in a cropped circular image.
So it's not only the resolution that changes, but the actual sensor been used.
So just keep in mind that the more information you have from the camera/lens you want to emulate the better.
Bug found at/patch written as a follow up of the BlenderPRO2012, patch reviewed by Brecht Van Lommel
Linking happens fine, but blender crashes on startup -- crash with familiar
backtrace happens with i18n disabled (in that case it's something to do with OIIO).
This commit makes BKE_image_acquire_ibuf referencing result, which means once
some area requested for image buffer, it'll be guaranteed this buffer wouldn't
be freed by image signal.
To de-reference buffer BKE_image_release_ibuf should now always be used.
To make referencing working correct we can not rely on result of
image_get_ibuf_threadsafe called outside from thread lock. This is so because
we need to guarantee getting image buffer from list of loaded buffers and it's
referencing happens atomic. Without lock here it is possible that between call
of image_get_ibuf_threadsafe and referencing the buffer IMA_SIGNAL_FREE would
be called. Image signal handling too is blocking now to prevent such a
situation.
Threads are locking by spinlock, which are faster than mutexes. There were some
slowdown reports in the past about render slowdown when using OSX on Xeon CPU.
It shouldn't happen with spin locks, but more tests on different hardware would
be really welcome. So far can not see speed regressions on own computers.
This commit also removes BKE_image_get_ibuf, because it was not so intuitive
when get_ibuf and acquire_ibuf should be used.
Thanks to Ton and Brecht for discussion/review :)
Initial support of OSL builds using SCons build system. Only tested on Linux now.
No changes to configuration files themselves -- for now check how it's configured
for linux buildbot (it was already horror to make all this changes and verify them,
changes to linux-config.py could easily be done later).
Currently WITH_BF_STATICOSL and WITH_BF_STATICLLVM are more like rudiments because
linking against oslexec requires special trick with --whole-archive. We woul either
need to find a way dealing with this oslexec less hackish or drop STATICOSL and
STATICLLVM flags. Will keep dropping this flags for until we have "final" build
rules for OSL.
Still can not make 32bit linux rendering with OSL -- blender simply crashes when
starting rendering. So for time being this issues are solving disabled OSL for
32bit build slaves.
This commit adds a small and simplistic C wrapper around boost's locale library as intern/locale, and heavily simplifies/reduces Blender's own i18n code (under blenfont/ dir). And it adds back UI translation on windows' official builds (with msvc)!
Note to platform maintainers: iconv and gettext (libintl) can now be removed from precompiled libs (not gettext binaries, under windows, of course ;) ).
Note to MinGW32/64 users: boost_locale lib has not yet been uploaded for those build env, please disable WITH_INTERNATIONAL for now (hopefully will be fixed very soon, have contacted psy-fy).
problem is that the curved interpolation is not constant speed which leads to
mismatches. Turns out this is really hard to solve and implement efficiently, so
curved motion blur is disabled for now, until I can find a solution.
compute_device_list is using static vector of device information which
had pointers (identifier and name) to values from device information
structures. That structures are also stored in static vector and being
refreshed every 5 seconds.
The issue is, as soon as device information is being updated, pointers
in vector from compute_device_list became incorrect.
Seems it was the reason of issues with sudden switching from CUDA to
OpenCL on my desktop and from CUDA to CPU on my laptop, It was also
seems to be making persistent images behaves instable.
Made it so device identifier and name are copied from device info
to structures used by RNA (CCLDeviceInfo).
Alternative could be avoid cacheing CCLDeviceInfo and always use actual
list of device information by RNA. It shouldn't be so much slow.
