minor refactoring

added more tests

minor

fixed warnings

minor

minor

minor

fixed comment

Implemented a learning-based color balance algorithm, which typically provides
noticeably better quality than grayworld, while being several times slower.
Added a python script for training this algorithm, as well as the benchmarking script
for objective quality evaluation.

Also made some modifications to the grayworld algorithm implementation, including the
16 bit image support and overall acceleration by about 1.7 times (for 8 bit images).

Moving more Caffe loaders to sparate file

Adding OCL version of col2im()
Polymorphic Deconvolution forward() implementation
Fixed OCL gemm problem

Paillou Filter

comment : english tab and assert  Mat(instead of new)

InputArray and ptr<Type>()

Outputarrays

OutputArray as argument

Update doc

Replaced internal variational refinement implementation inside DeepFlow
with a new optimized one, which provides about the same quality while
being 4-6 times faster.

Added variational refinement as a separate class (based on implementation
inside DeepFlow, but significantly accelerated, about 4-6 times faster),
accelerated the main dense inverse search algorithm. Added several new
features including patch mean normalization for increased robustness to
illumination changes and spatial propagation, which often helps to recover
from errors introduced by the coarse-to-fine scheme. Expanded the
documentation, added new accuracy and perf tests. Refactored some of
the already existing optical flow accuracy tests.

LSTM bug is caused by different behaviour of std::tanh() and hand-
crafted
tanh() via std::exp().