Also, small fix inside inside Python types conversion was added

# Conflicts:
#	modules/dnn/samples/fcn_semsegm.cpp
#	modules/dnn/src/caffe/caffe.proto
#	modules/dnn/src/caffe/compiled/caffe.tar.gz
#	modules/dnn/src/layers/crop_layer.cpp
#	modules/dnn/src/layers/crop_layer.hpp
#	modules/dnn/src/layers/eltwise_layer.cpp
#	modules/dnn/src/layers/eltwise_layer.hpp

# Conflicts:
#	modules/dnn/include/opencv2/dnn/blob.hpp
#	modules/dnn/src/init.cpp
#	modules/dnn/src/layers/concat_layer.cpp
#	modules/dnn/src/layers/convolution_layer.cpp
#	modules/dnn/src/layers/convolution_layer.hpp
#	modules/dnn/src/layers/layers_common.cpp
#	modules/dnn/src/layers/layers_common.hpp
#	modules/dnn/src/layers/op_im2col.hpp
#	modules/dnn/src/layers/pooling_layer.cpp
#	modules/dnn/src/layers/pooling_layer.hpp

Added an option to pass an initial approximation of optical flow in
DISOpticalFlow. Added a python sample that demonstrates the use of this
feature for temporal propagation of flow vectors.

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