oidn/CHANGELOG.md at master · OpenImageDenoise/oidn

Version History

Changes in v1.4.3:

Fixed hardcoded library paths in installed macOS binaries
Disabled VTune profiling support of oneDNN kernels by default, can be enabled using CMake options if required (DNNL_ENABLE_JIT_PROFILING and DNNL_ENABLE_ITT_TASKS)
Upgraded to oneTBB 2021.5.0 in the official binaries

Changes in v1.4.2:

Added support for 16-bit half-precision floating-point images
Added oidnGetBufferData and oidnGetBufferSize functions
Fixed performance issue on x86 hybrid architecture CPUs (e.g. Alder Lake)
Fixed build error when using OpenImageIO 2.3 or later
Upgraded to oneTBB 2021.4.0 in the official binaries

Changes in v1.4.1:

Fixed crash when in-place denoising images with certain unusual resolutions
Fixed compile error when building for Apple Silicon using some unofficial builds of ISPC

Changes in v1.4.0:

Improved fine detail preservation
Added the cleanAux filter parameter for further improving quality when the auxiliary feature (albedo, normal) images are noise-free
Added support for denoising auxiliary feature images, which can be used together with the new cleanAux parameter for improving quality when the auxiliary images are noisy (recommended for final frame denoising)
Normals are expected to be in the [-1, 1] range (but still do not have to be normalized)
Added the oidnUpdateFilterData function which must be called when the contents of an opaque data parameter bound to a filter (e.g. weights) has been changed after committing the filter
Added the oidnRemoveFilterImage and oidnRemoveFilterData functions for removing previously set image and opaque data parameters of filters
Reduced the overhead of oidnCommitFilter to zero in some cases (e.g. when changing already set image buffers/pointers or the inputScale parameter)
Reduced filter memory consumption by about 35%
Reduced total memory consumption significantly when using multiple filters that belong to the same device
Reduced the default maximum memory consumption to 3000 MB
Added the OIDN_FILTER_RT and OIDN_FILTER_RTLIGHTMAP CMake options for excluding the trained filter weights from the build to significantly decrease its size
Fixed detection of static TBB builds on Windows
Fixed compile error when using future glibc versions
Added oidnBenchmark option for setting custom resolutions
Upgraded to oneTBB 2021.2.0 in the official binaries

Changes in v1.3.0:

Improved denoising quality
- Improved sharpness of fine details / less blurriness
- Fewer noisy artifacts
Slightly improved performance and lowered memory consumption
Added directional (e.g. spherical harmonics) lightmap denoising to the RTLightmap filter
Added inputScale filter parameter which generalizes the existing (and thus now deprecated) hdrScale parameter for non-HDR images
Added native support for Apple Silicon and the BNNS library on macOS (currently requires rebuilding from source)
Added OIDN_NEURAL_RUNTIME CMake option for setting the neural network runtime library
Reduced the size of the library binary
Fixed compile error on some older macOS versions
Upgraded release builds to use oneTBB 2021.1.1
Removed tbbmalloc dependency
Appended the library version to the name of the directory containing the installed CMake files
Training:
- Faster training performance
- Added mixed precision training (enabled by default)
- Added efficient data-parallel training on multiple GPUs
- Enabled preprocessing datasets multiple times with possibly different options
- Minor bugfixes

Changes in v1.2.4:

Added OIDN_API_NAMESPACE CMake option that allows to put all API functions inside a user-defined namespace
Fixed bug when TBB_USE_GLIBCXX_VERSION is defined
Fixed compile error when using an old compiler which does not support OpenMP SIMD
Added compatibility with oneTBB 2021
Export only necessary symbols on Linux and macOS

Changes in v1.2.3:

Fixed incorrect detection of AVX-512 on macOS (sometimes causing a crash)
Fixed inconsistent performance and costly initialization for AVX-512
Fixed JIT'ed AVX-512 kernels not showing up correctly in VTune

Changes in v1.2.2:

Fixed unhandled exception when canceling filter execution from the progress monitor callback function

Changes in v1.2.1:

Fixed tiling artifacts when in-place denoising (using one of the input images as the output) high-resolution (> 1080p) images
Fixed ghosting/color bleeding artifacts in black regions when using albedo/normal buffers
Fixed error when building as a static library (OIDN_STATIC_LIB option)
Fixed compile error for ISPC 1.13 and later
Fixed minor TBB detection issues
Fixed crash on pre-SSE4 CPUs when using some recent compilers (e.g. GCC 10)
Link C/C++ runtime library dynamically on Windows too by default
Renamed example apps (oidnDenoise, oidnTest)
Added benchmark app (oidnBenchmark)
Fixed random data augmentation seeding in training
Fixed training warning with PyTorch 1.5 and later

Changes in v1.2.0:

Added neural network training code
Added support for specifying user-trained models at runtime
Slightly improved denoising quality (e.g. less ringing artifacts, less blurriness in some cases)
Improved denoising speed by about 7-38% (mostly depending on the compiler)
Added OIDN_STATIC_RUNTIME CMake option (for Windows only)
Added support for OpenImageIO to the example apps (disabled by default)
Added check for minimum supported TBB version
Find debug versions of TBB
Added testing

Changes in v1.1.0:

Added RTLightmap filter optimized for lightmaps
Added hdrScale filter parameter for manually specifying the mapping of HDR color values to luminance levels

Changes in v1.0.0:

Improved denoising quality
- More details preserved
- Less artifacts (e.g. noisy spots, color bleeding with albedo/normal)
Added maxMemoryMB filter parameter for limiting the maximum memory consumption regardless of the image resolution, potentially at the cost of lower denoising speed. This is internally implemented by denoising the image in tiles
Significantly reduced memory consumption (but slightly lower performance) for high resolutions (> 2K) by default: limited to about 6 GB
Added alignment and overlap filter parameters that can be queried for manual tiled denoising
Added verbose device parameter for setting the verbosity of the console output, and disabled all console output by default
Fixed crash for zero-sized images

Changes in v0.9.0:

Reduced memory consumption by about 38%
Added support for progress monitor callback functions
Enabled fully concurrent execution when using multiple devices
Clamp LDR input and output colors to 1
Fixed issue where some memory allocation errors were not reported

Changes in v0.8.2:

Fixed wrong HDR output when the input contains infinities/NaNs
Fixed wrong output when multiple filters were executed concurrently on separate devices with AVX-512 support. Currently the filter executions are serialized as a temporary workaround, and a full fix will be included in a future release.
Added OIDN_STATIC_LIB CMake option for building as a static library (requires CMake 3.13.0 or later)
Fixed CMake error when adding the library with add_subdirectory() to a project

Changes in v0.8.1:

Fixed wrong path to TBB in the generated CMake configs
Fixed wrong rpath in the binaries
Fixed compile error on some macOS systems
Fixed minor compile issues with Visual Studio
Lowered the CPU requirement to SSE4.1
Minor example update

Changes in v0.8.0:

Initial beta release