This is the version history, or change log, for all the released versions of NNSuperResolution (latest official release at the top).
v3.2.1 – Sept 2022
- Fixed a regression where the overscan handling stopped working in sequence mode, but
- instead resulted in a crash. This was working in v3.0.0, but broke in the optimization release v3.2.0. It’s now fully corrected and working as it should again.
v3.2.0 – May 2022
- Speed optimizations overall. According to our own internal testing, sequence mode is
- now about 30% faster to render.
- Added an option for processing in mixed precision. This is using a bit less VRAM, and is
- a quite a lot faster on some GPU architectures that are supporting it (RTX).
- Added an option for choosing what CUDA device ID to process on. This means you can
- pick what GPU to use if you got a workstation with multiple GPUs installed.
- Disabled initial heuristics to fix a slow down issue on certain GPU architectures that
- happened on the first processing frame.
- Optimized the build of the neural network processing backend library. The plugin binary
- (shared library) is now a bit smaller and faster to load.
- Built the neural network processing backend with MKLDNN support, resulting in a vast
- improvement in rendering speed when using CPU only. According to our own testing it’s
- sometimes even less than 25% of the render time of v3.0.0 (in sequence mode).
- Updated the NVIDIA cuDNN library to v8.0.5 for the CUDA10.1 build. This means we are
- fully matching what Nuke13.x is built against, which means our plugin can co-exists
- together with CopyCat nodes as well as other AIR nodes by Foundry.
- Built the neural network processing backend with PTX support, which means that GPUs
- with compute capability 8.0 and 8.6, i.e. Ampere cards, can now use the CUDA10.1 build if needed (see above). The only downside is that they have to JIT compile the CUDA kernels the first time they run the plugin. Please see the documentation for more information about setting the CUDA_CACHE_MAXSIZE environment variable.
- Internal checking that the bounding box doesn’t change between frames in sequence mode (it’s not supported having animated bboxes). Now it’s throwing an error instead of crashing.
- Bug fixes to the “frame range knobs” handling and the “reset frame range” button
- Better render status logging for what layer is processing to the terminal
- Better error reporting to the terminal
- Added support for Nuke13.2
v3.0.0 – November 2021
- Totally retrained all sequence mode networks from scratch with a higher neural network
- capacity, to improve the overall upscale results.
- Trained all the 2x versions of the networks, for both still and sequence mode. Added the
- scale knob to control the upscale factor.
- Added the details knob to control the blend between the PSNR and GAN networks.
- Renamed the sequence type option “Plates (legacy) [RGB]” to “Plates (Vimeo) [RGB]”.
- Fixed the handling of formats to support upscaling of anamorphic formats.
v2.5.0 – June 2021
- Totally retrained plate (RGB) solution with sharper and more detailed results. • CG (RGBA) upscale option available (beta).
- Nuke Indie support (requires the latest version of Nuke12.2 or Nuke13.0).
v2.0.1 – March 2021
- Bug fix to the progress bar that didn’t show the right thing when processing the preroll in
- sequence mode using several image patches.
- Bug fix to a crash that happened when switching between GPU and CPU mode in the
- same Nuke session.
v2.0.0 – March 2021
- Release of sequence mode.
- Support for additional layers, i.e. if you got multiple layers and render them through with
- a Write node set to “channels: all” the plugin will run the upscale separately on each layer. Please note that there is no alpha channel (4th layer channel) support yet in this version.
- Renamed the status label from “Inference runs” to “Image patches” to be more clear to end users and also make sense in sequence mode.
- Fixed a bug relating to processing images using multiple scanline compression.
v1.0.0 – December 2020
- Initial release (still mode)