[GSoC] High Level API and Samples for Scene Text Detection and Recognition
* APIs and samples for scene text detection and recognition
* update APIs and tutorial for Text Detection and Recognition
* API updates:
(1) put decodeType into struct Voc
(2) optimize the post-processing of DB
* sample update:
(1) add transformation into scene_text_spotting.cpp
(2) modify text_detection.cpp with API update
* update tutorial
* simplify text recognition API
update tutorial
* update impl usage in recognize() and detect()
* dnn: refactoring public API of TextRecognitionModel/TextDetectionModel
* update provided models
update opencv.bib
* dnn: adjust text rectangle angle
* remove points ordering operation in model.cpp
* update gts of DB test in test_model.cpp
* dnn: ensure to keep text rectangle angle
- avoid 90/180 degree turns
* dnn(text): use quadrangle result in TextDetectionModel API
* dnn: update Text Detection API
(1) keep points' order consistent with (bl, tl, tr, br) in unclip
(2) update contourScore with boundingRect
* Implement ASIFT in C++
* '>>' should be '> >' within a nested template
* add a sample for asift usage
* bugfix empty keypoints cause crash
* simpler initialization for mask
* suppress the number of lines
* correct tex document
* type casting
* add descriptorsize for asift
* smaller testdata for asift
* more smaller test data
* add OpenCV short license header
Add URLs, harmonise formatting, and fix parse error in bibliography (#13228)
* Fixed parse error in bibliography
* Removed extra curly braces
* harmonized whitespace
* changed organisation -> publisher where appropriate. Organisation is intended as the author's organisation, not the publishing.
* harmonized capitalisation and whitespace
* Add links to about 1/3 of references
* add new chessboard detector
The chessboar detector is based on the paper.
Accurate Detection and Localization of Checkerboard Corners for
Calibration Alexander Duda, Udo Frese
British Machine Vision Conference, o.A., 2018.
It utilizes point symmetry of checkerboard corners in combination with a
localized Radon transform approximated by box filters to achieve high
performance even on large images. Here, tests have shown that the
ability to localize checkerboard corners is close to the theoretical
limit of 1/100 of a pixel while being considerably less sensitive
to image noise than standard methods.
* chessboard: add reference to bibtex file
* chessboard: add dependency to opencv_flann
* fix: test chesscorners. It is valid to return an empty list
In case no chessboard was detected it should be valid for the detector
to return an empty list.
For simplifcation, it should be allowed to return any number of corners
if they are flagged as not found.
* fix: opencv.bib remove empty lines
* fix: doc findChessboardCorners replace cvSize with cv::Size
* chessboard tests: factor out logic selecting detector
* chessboard: add unit test for findChessboardCorners2
This is includes a new chessboard generator which supports subpix
corners with high accuracy by wrapping an optimal chessboard using
wrapPerspective.
* fix: chessboard unit test - overwrite of default parameter flag of findCirclesGrid
* chessboard: remove trailing whitespace
* chessboard: fix debug drawing
* chessboard: fix some issues during code review
* chessboard: normalize asymmetric chessboard
* chessboard: fix float double warning
* remove trailing whitespace
* chessboards: fix compiler warnings
* chessboards: fix compiler warnings
* checkerboard: some performance improvements
* chessboard: remove NULL macros for language bindinges from internal headers
* chessboard: shorten license terms
* chessboard: remove unused internal method
* chessboard: set helper functions to static
* chessboard: fix normalizePoints1D using unshifted points
* chessboard: remove wrongly copied text
* chessboard: use CV_CheckTypeEQ macro
* chessboard: comment all NaN checks
* chessboard: use consistent color conversion
* chessboard: use CheckChannelEQ macro
* chessboard: assume gray color image for internal methods
* chessboard: use std::swap
* chessboard: use Mat.dataend
* chessboard: fix compiler warnings
* chessboard: replace some checks witch CV_CHECK macro
* chessboard: fix comparison function for partial sort
* chessboard: small cleanup
* chessboard: use short license header
* chessboard: rename findChessboard2 to findChessboardSB
* chessboard: fix type in unit test
In this tutorial you will learn:
- what is a degradation image model
- what is a PSF of an out-of-focus image
- how to restore a blurred image
- what is the Wiener filter
* Simulated Annealing for ANN_MLP training method
* EXPECT_LT
* just to test new data
* manage RNG
* Try again
* Just run buildbot with new data
* try to understand
* Test layer
* New data- new test
* Force RNG in backprop
* Use Impl to avoid virtual method
* reset all weights
* try to solve ABI
* retry
* ABI solved?
* till problem with dynamic_cast
* Something is wrong
* Solved?
* disable backprop test
* remove ANN_MLP_ANNEALImpl
* Disable weight in varmap
* Add example for SimulatedAnnealing
Adds fitEllipseDirect to imgproc: The Direct least square (Direct) method by Fitzgibbon1999.
New Tests are included for the methods.
fitEllipseAMS Tests
fitEllipseDirect Tests
Comparative examples are added to fitEllipse.cpp in Samples.
New p3p algorithm (accepted by CVPR 2017) (#8301)
* add p3p source code
* indent 4
* update publication info
* fix filename
* interface done
* plug in done, test needed
* debugging
* for test
* a working version
* clean p3p code
* test
* test
* fix warning, blank line
* apply patch from @catree
* add reference info
* namespace, indent 4
* static solveQuartic
* put small functions to anonymous namespace
catree
Victor
Stefano Allegretti
Andreas Franek
Federico Bolelli
Alexander Alekhin
Wenqing Zhang
kadi soheib
Yosshi999
Alexander Smorkalov
Jan Lebert
Alexander Alekhin
Matthias Winkelmann
Karpushin Vladislav
Alexander Duda
LaurentBerger
Jasper Shemilt
Tong Ke
Vladislav Sovrasov
Marina Noskova
joao.faro
Thomas Dunker
Maksim Shabunin
cbalint13
Alexey Polovinkin