Opencv 3.3.0 released information

As a big fan of OPENCV 3.3.0 There is what is new!

Some my notes about new released. Based on changelog and released notes.

Deep neural network module is now accelerated with improved performance also moved into the main repository branch under opencv/modules/dnn. This module is also no more available in contrib branch. There was improved loading models from Troch and TensorFlow and many performance improvements.

Support of

Caffe 1
TensorFlow
Torch/PyTorch

Interesting is available layer types list

AbsVal
AveragePooling
BatchNormalization
Concatenation
Convolution (including dilated convolution)
Crop
Deconvolution, a.k.a. transposed convolution or full convolution
DetectionOutput (SSD-specific layer)
Dropout
Eltwise (+, *, max)
Flatten
FullyConnected
LRN
LSTM
MaxPooling
MaxUnpooling
MVN
NormalizeBBox (SSD-specific layer)
Padding
Permute
Power
PReLU (including ChannelPReLU with channel-specific slopes)
PriorBox (SSD-specific layer)
ReLU
RNN
Scale
Shift
Sigmoid
Slice
Softmax
Split
TanH

And even more

Advanced core performance AVX, AVX2, SSE and NEON
New Python and C++ samples DNN C++ and Python api

Another mainly performance improvements is 15% speed according to IPPICV from 2015.12 to 2017.2 version upgrade

Opencv C++ 11 ready

I am interesting about news C++ 11 support. This should speed up development a bit. Tested on fedora distribution and Opencv should be build with -DENABLE_CXX11=ON. I will try on windows. I do not expect any problem. Build Opencv 3.3 with Visual Studio 2017 and CXX11 support.
Examples like

parallel_for_

And dummy auto containers :)

auto A = Mat_<double>({0, -1, 0, -1, 5, -1, 0, -1, 0}).reshape(1, 3);

Opencv hardware-accelerated video encoding/decoding

This is big in my eyes. Continue doing this.. Encoding and decoding of raw H.264 and MPEG1/2 video streams is supported, media containers are not supported yet.

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