In addition to various minor changes, the following was changed for the different versions of FLIP:

Version 1.7 (commit ?)

• Fixed memory leaks in the C++/CUDA/Python versions of FLIP.
• HDR-FLIP: Fixed crashes that followed from the reference's median being 0.
  • Automatic start and stop exposures in HDR-FLIP are computed using statistics of the reference image. For the stop exposure, we use the median luminance of the reference. When that is 0, we used to get undefined behavior or a crash. Version 1.7 fixes this by clamping the median to have a minimum value of FLT_EPSILON.

Version 1.6 (commit 7967578)

• Flipped the ꟻ in ꟻLIP. The entire name (FLIP) should now be readable on all devices.
• Published Python version of FLIP to PyPI (URL: https://pypi.org/project/flip-evaluator/).
  • The Python version of FLIP (tool and API) is now installed by pip install flip-evaluator.
  • The distribution has been tested on Windows, Linux (Ubuntu 24.04), and OS X ($\ge$ 10.15). Wheels are built for each (and various CPython versions $\ge$ 3.8) using cibuildwheel. Note that FLIP's output might differ slightly between the different operative systems. The references used for src/tests/test.py are made for Windows. While the mean tests (means compared up to six decimal points) pass on each mentioned operative system, not all error map pixels are identical.
  • After installation, the tool can be run directly in a shell by flip --reference reference.{png|exr} --test test.{png|exr}.
  • After installation, the FLIP API is available in Python by import flip_evaluator as flip.
• Python version is now built using scikit instead of setuptools, and uses nanobind instead of pybind11.
• Directory structure in the FLIP repository has been slightly altered to accomodate the Python version being published to PyPI.
• Updated Python/C++/CUDA test script.
• Various significant bugfixes.

Version 1.5 (commit -)

• Skipped version 1.5 due to PyPI-related mistake. Version 1.6 is the same as version 1.5 was supposed to be.

Version 1.4 (commits 6265f80 to 0349494)

• Changed the Python version of FLIP so that it leverages the C++ code through pybind11.
  • Results (only evaluation, not including file load/save, etc; measured on an AMD Ryzen Threadripper 3970X 32-Core Processor, 3693 MHz, with 32 Cores and 64 Logical Processors):
    • 20-47x faster for LDR/HDR CPU.
    • Timings for 1920x1080 images:
      • Python/LDR: 77 ms
      • Python/HDR: 1007 ms
  • NOTE: The Python version can currently not run the CUDA version of FLIP (see issue #22).
  • NOTE: The Python tool now uses the C++ tool. Compared to before, you will need to change _ to - when calling flip.py (e.g., python flip.py -r reference.exr -t test.exr --start_exposure 3 is now python flip.py -r reference.exr -t test.exr --start-exposure 3; see python flip.py -h).
• The Python version of FLIP can now be installed using pip (run pip install -r requirements.txt . from the python folder).
• The code for the C++/CUDA tool is now in FLIPToolHelpers.h.
• NOTE: The fourth evaluate() function in FLIP.h now takes two additional arguments: computeMeanError and meanError. Furthermore, its list of arguments has been partly reordered.
• NOTE: The median computation (used for automatic start and stop expsoure computations in HDR-FLIP) in the C++/CUDA code has been changed, sometimes causing a minor change in results but always resulting in a significant speedup. The tests have been updated following this change.
  • Timings for 1920x1080 images (only evaluation, not including file load/save, etc, but measured with another GPU and including more code than the numbers presented in the v1.2 update, so the numbers are not directly comparable; measured on an AMD Ryzen Threadripper 3970X 32-Core Processor, 3693 MHz, with 32 Cores and 64 Logical Processors and an NVIDIA RTX 4090 GPU):
    • CPP/LDR: 86 ms
    • CPP/HDR: 1179 ms
    • CUDA/LDR: 8 ms
    • CUDA/HDR: 131 ms
• Added check for OpenMP for CMake build.
• Overlapped histograms are now available in the C++ tool code. These are created when one reference and two test images are input, together with the --histogram flag.
• Text file output are now available in the C++ tool code. These are created when the --textfile flag is input.
• The Python and C++ tests now use the same targets.

Version 1.3 (commit a00bc7d)

• Changed to CUDA 12.3.
• Rewrote C++ code so that FLIP is in a single header (both CPP/CUDA).
• Rewrote FLIP-tool.cpp to use many more local functions to make the code easier to read.
• Some of the tests/correct_*.png images have been update due to minor changes in output that occurred as part of switching to CUDA 12.3 and changing the order of some transforms.

Version 1.2 (commit dde1eca)

• Changed to CUDA 11.5 (was done after v1.1, but before v1.2).
• Adds tests for C++ and CUDA in the tests-directory. Additionally, the Python and PyTorch tests were moved to that directory.
• Performance optimizations for C++ and CUDA implementations:
  • Uses separable filters.
  • Merges several functions/kernels into fewer.
  • Uses OpenMP for the CPU.
  • Results (not including file load/save):
    • 111-124x faster for LDR/HDR CPU (measured on an AMD Ryzen Threadripper 3970X 32-Core Processor, 3693 MHz, with 32 Cores and 64 Logical Processors).
    • 2.4-2.8x faster LDR/HDR CUDA (measured on an AMD Ryzen Threadripper 3970X 32-Core Processor, 3693 MHz, with 32 Cores and 64 Logical Processors, together with an NVIDIA RTX 3090).
    • Timings for 1920x1080 images:
      • CPP/LDR: 63 ms
      • CPP/HDR: 1050 ms
      • CUDA/LDR: 13 ms
      • CUDA/HDR: 136 ms

Version 1.1 (commit 4ed59e9)

• NVIDIA Source Code License changed to a BSD 3-Clause License
• Precision updates:
  • Constants use nine decimal digits (a float32 number has the same bit representation if stored with nine or more decimals in NumPy and C++)
  • Increased accuracy in the XYZ2CIELab transform and its inverse in C++ and CUDA
  • Changed reference_illuminant to a float32 array in Python (reducing LDR-FLIP runtime by almost 30% for a 1080p image)
• Magma and Viridis are indexed into using round instead of floor
• Introduced the constant 1.0 / referenceIlluminant to avoid unnecessary divisions during color transforms
• Updated the Python reference error maps based on the changes above
• Updated the PyTorch test script based on the changes above
• Expected CUDA version updated from 11.2 to 11.3
• Removed erroneous abs() from the XYZ2CIELab transform in C++ and CUDA
• Added "Acknowledgements" section to the main README file
• A cross platform CMake build was added recently (commit 6bdbbaa)

Version 1.0

• Initial release