Update to FLIP v1.4

[pandersson94]

• Changed the Python version of ꟻLIP so that it leverages the C++ code through pybind11.
  • Results (only evaluation, not including file load/save, etc):
    • 19-34x faster for LDR/HDR CPU (measured on an AMD Ryzen Threadripper 3970X 32-Core Processor, 3693 MHz, with 32 Cores and 64 Logical Processors).
    • Timings for 1920x1080 images:
      • Python/LDR: 81 ms
      • Python/HDR: 1370 ms
  • NOTE: The Python version can currently not run the CUDA version of ꟻLIP (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 ꟻLIP 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.
• 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.

[inversepixel]

For absolute numbers, e.g., 91 ms, it would be nice if you could add what kind of CPU etc you used. Otherwise, it does not mean much.

[pandersson94]

Pushed update to performance numbers, including information about the CPU used. This information was also added to the performance numbers stated for the FLIP 1.2 update.