- 18 Aug, 2015 1 commit
-
-
Vladimir authored
-
- 17 Aug, 2015 1 commit
-
-
Vladimir authored
-
- 16 Aug, 2015 1 commit
-
-
Vladimir authored
-
- 15 Aug, 2015 19 commits
-
-
Vladimir authored
-
Vladimir authored
-
Vladimir authored
-
Vladimir authored
Merge branch 'TLD_Multi_Tracking_Support' of https://github.com/Auron-X/opencv_contrib into TLD_Multi_Tracking_Support
-
Vladimir authored
-
Vladimir authored
-
Vladimir authored
-
Vladimir authored
-
Vladimir authored
-
Vladimir authored
-
Vladimir authored
-
Vladimir authored
-
Vladimir authored
-
Vladimir authored
-
-
Vladimir authored
-
Vladimir authored
1. Multi-tracker classes (multiTracker.cpp) 2. Multi-tracker example (multiTracker_test.cpp) 3. Fixed a rare bug (OpenCL runtime error)
-
-
-
- 10 Aug, 2015 8 commits
- 08 Aug, 2015 3 commits
- 06 Aug, 2015 1 commit
-
-
Maksim Shabunin authored
-
- 05 Aug, 2015 1 commit
-
-
Vadim Pisarevsky authored
-
- 03 Aug, 2015 4 commits
-
-
Lluis Gomez-Bigorda authored
-
Lluis Gomez-Bigorda authored
-
Lluis Gomez-Bigorda authored
-
Lluis Gomez-Bigorda authored
Adds example on segmented word recognition. Shows the use of the OCRHMMDecoder with the NM and CNN default classifiers.
-
- 01 Aug, 2015 1 commit
-
-
lluis authored
Overload the run() method in BaseOCR class in order to adapt to different classifier callbacks. The original run() method accepts only one Mat input image, this is expected to be a binarzed image with black and white text and works both with the OCRTesseract class and the OCRHMMDecoder class when the character classifier callback works with binary images (e.g. NM). The new run() method accepts two Mat input parameters. One for the gray scale (or color) source image and the other for a binary mask where each connected component corresponds to a pre-segmented character in the input image. This way the OCRHMMDecoder is able to work with character classifiers that operate in grey scale (or color) images (e.g. a CNN).
-