* enabled convolution & activation fusion
* a few more optimizations:
+ optimized the common case when the indices of max pooling layer are not used. in this case we use the more efficient branch that computes just maximums over the aperture.
+ optimized the convolution + activation fusion when the activation is relu, which is another common case
+ convolution can now be fused with batch norm. It's the zero-cost fusion. If the batch norm is followed by relu, all three (conv + batchnorm + relu) are fused together. this modification seriously improved ENet performance
* hopefully fixed warnings on Windows
* first commit
* first commit
* adjust code layout
* round mean value
* add missed header
* remove useless header
* remove useless header
* first commit
* first commit
* first commit
* Encapsule function averageHash by class
* remove export macro
* encapsulate phash algo by class
* first commit
* fix bugs of createHash and fillBlcoks
* 1 : add create function
2 : add overload functions
* implement get set functions
* fix bug--destination depth should be CV_32F
* first commit
* first commit
* 1 : fix bug--forgot '"'
2 : forgot to include iostream
* fix warnings
* remove tab
* remove trailing white space
* remove trailing white space
* remove trailing white space
* remove trailing white space
* remove trailing white space
* remove trailing white space
* first commit
* remove trailing white space
* remove trailing white space
* remove trailing white space
* reduce redundance operation
* add explanation of img_hash
* remove useless comments
* remove trailing space
* first commit
* fix missed symbol
* add new defgroup and change all defgroup to ihash
* fix namespace confliction
* change namespace from ihash to img_hash
* change ihash to img_hash
* change include guard
* forbid implicit conversion
* first commit
* 1 : declare function findFeatureVector
2 : forward declare test class--RavialVarHashTester as friend
* first commit
* replace auto with explicit type
* export some symbols, for initialization and testing
* remove trailing white space
* add namespace cv
* fix type cast warning and define default constrcutor/destructor
* declare and define RadialVarHashTester in namespace
* remove default constructor/destructor
* exports functions findFeatures and destructor
* remove trailing white space
* fix bug--wrong definition of destructor
* remove trailing white space
* implement findFeatureVector
* add test case for findFeatureVector
* 1 : fix bug--forgot to allocate space for input
2 : fix bug--compare the results of pixPerLine with wrong matrix
* remove trailing space
* implement hashCalculate
* add test case for hashCalculate
* remove trailing white space
* avoid hiding parameter
* refine codes and keep the original range
* adjust expected hash value since the range of hash change
* add comment
* reduce scope
* remove trailing white space
* adjust format
* add new function compare
* implement compute functions
* use array as buffer of cv::Mat, avoid memory allocation
* remove trailing whitespace
* 1 : implement cross-correlation rather than using matchTemplate since the
results of matchTemplate are weird
2 : remove gamma param, although the paper said PHash apply gamma
correction on the image, but the codes do not do that(I think it is a bug
of PHash)
3 : create function can specify sigma and numOfAngleLine
4 : Use blurImg to replace normalizeImg
5 : remove useless parameters which related to gamma correction
* add example of radial variance hash
* use buffer to avoid memory allocation and use enum to specify hash size
* remove useless header
* fix bug--constructor only accept two params
* add comments
* transpose projection matrix, friendlier for cache hit
* use pointer to access projection value
* function able to specify sigma and numOfAngleLine
* add get/set functions
* implement image hash algo--block mean hash
* include block mean hash and add comments
* remove trailing whitespace
* fix warning--compare with sign and unsigned value
* implement destructor and change mode type to size_t
* add example of block mean hash
* compress the bits of hash
* function--blockMeanHash able to set mode
* fix type cast warning and style
* change expected result to bool
* compress the hash value from 16 bytes to 8 bytes
* update comments
* compress hash from 16 bytes to 8 bytes
* use peak value of cross correlation as comparison result
* add limit header
* first commit
* add group and header file of color moment hash
* should not use auto, it is c++11 feature
* support python binding
* implement destructor of AverageHash
* support python binding
* support python binding
* support python binding
* change type to inputArray and outputArray, easier for python binding
* all algorithms support input type CV_8UC4,CV_8UC3 and CV_8UC1
* Provide better instructions
* Make it more pleasant to read
* Add information of speed comparsion
* remove trailing white space
* remove useless blank line
* refine comments of example
* fix link error
* refine title
* 1 : implement function "getDefaultName"
2 : adjust style
* Update README.md
1 : Fix wrong branch
2 : Add another solution to download img_hash
* img_hash: refactored interfaces to use pImpl
* remove trailing white space
* img_hash: use type-safe pImpl
* change name, easier to find the source file
* 1 : narrow scope of ImgHashImpl
2 : use static cast to replace dynamic cast because class hierarchy of
img_hash is very straightforward
* should not declare ImgHashImpl api in the header file of ImgHashBase, this increase chance of breaking ABI
* should not declare ImgHashImpl api in the header file of ImgHashBase, this increase chance of breaking ABI
* fix warning, because unelaborated friend declaration is a C++11 extension
* first commit
* fix bug, except of windows, other platforms cannot access private member.
pimpl only accessable by the class itself, therefore I think declare
everything as public is quite safe
* first commit comparison and computation charts
* update chart link
* some further optimizations and cleanups in dnn:
+ got rid of dnn::gemm; it's not perf critical anymore (perhaps)
+ embedded col2im functionality into convolution_layer.cpp, since it's not used anywhere else
+ parallel max pooling. even better performance can be achieved if we knew that max indices are not needed (and they are not needed in most networks)
+ somewhat optimized deconvolution layer: optimized bias addition (merged it with col2im), optimized col2im slightly.
+ hopefully fixed incorrect memory access in fully-connected layer; restored aligned memory reads (they should work fine now)
* hopefully fixed regressions in ENet performance
* fixed some typos in deconvolution; added SIMD optimization for the max pooling layer
* fixed warnings in SIMD-less build configuration
* rewritten the following layers to be [much] more efficient: convolution, fully connected, activations (relu, tanh, ...), LRN. Use optional AVX optimization for the first two.
* eliminated trailing whitespaces
The while loop in member function buildPyramid in deepflow.cpp terminated as a result of the break statement and never as a result of the termination criteria because the "i" variable in the while loop was never incremented.
Changed the while loop into a for loop
Changed the while loop into a for loop in the member function buildPyramid in deepFlow.cpp
removed trailing whitespace
Incremental commit.
Theory updated.
Theory finished.
Inpainting in progress.
Inpainting done plus minor fix in kernel computation.
Tutorials done.
Documentation done.
Whitespace fix.
Update.
Conversion to jpg.
Documentation links fixed.
berak
sghoshcvc
Maksim Shabunin
Justin Hotchkiss Palermo
Alexander Alekhin
Aleksandr Rybnikov
dkurt
Vadim Pisarevsky
Tham
Vladislav Sovrasov
Diego
Alexander Alekhin
Jcrist99
Yuriy Obukh
Natsuki Kawai
Anup Parikh
abratchik
Woody Chow
Pavel Vlasanek
catree