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You're fast at converting those examples.

JHPJHP wrote:cv_mov_houghcircles.pb: finds circles in grayscale image frames using the Hough transform on a movie file

Quite impressive again that it can detect this circular object while it is moving around.

Hi wilbert,

Here are the last of the Windows examples modified to work in OSX. Thank you very much for your invaluable support throughout this process
- most of the following legacy examples have been demonstrated in previously posted examples using newer OpenCV functions

Updated the OSX interface:
- converted 8 examples
-- le_cam_extractSURF.pb: detects keypoints and computes SURF (Speeded-Up Robust Features) descriptors on the webcam interface
-- le_extractSURF.pb: detects keypoints and computes SURF (Speeded-Up Robust Features) descriptors
-- le_fitellipse_1.pb: creates a sequence of points, bounding them in an ellipse of the minimal area
-- le_mov_bgcodebookmodel.pb: using an average difference learning method, foreground moving objects of a certain size are tracked
-- le_mov_bgstatmodel_1.pb: using a background/foreground detection algorithm, foreground objects are highlighted/removed
-- le_mov_bgstatmodel_2.pb: using a Gaussian mixture-based background/foreground detection algorithm, foreground objects are highlighted
-- le_mov_gaussianbgmodel.pb: using a Gaussian background model, foreground moving objects of a certain size are tracked
-- le_pyrsegmentation.pb: implementing image segmentation by pyramids, a cartoon effect is achieved

NB*: Fixed an OSX OpenCV Function declaration that improved performance from the stitching examples.

JHPJHP wrote:Here are the last of the Windows examples modified to work in OSX.

Thanks for all you did JHPJHP.
It's nice to have this lib available on OSX.

JHPJHP wrote:-- le_pyrsegmentation.pb: implementing image segmentation by pyramids, a cartoon effect is achieved

Great effect

Hi wilbert,

You're most welcome.

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Updated the OSX interfaces:
- rebuilt all libraries (modified 1 dylib)
-- libopencv_imgproc.2.4.13.dylib
- fixed 1 example
-- cv_minarea_2.pb: finds the minimal area of a point set wrapping it in a triangle and a circle

libopencv_imgproc.2.4.13.dylib / cv_minarea_2.pb
- copied the legacy C++ source file from a previous OpenCV build, into the current source folder
- modified the C++ source file to include a C-Interface to the C++ function
- added various header references pointing to the C-Interface function
- fixed reported version problems when trying to compile

JHPJHP wrote:libopencv_imgproc.2.4.13.dylib / cv_minarea_2.pb
- copied the legacy C++ source file from a previous OpenCV build, into the current source folder
- modified the C++ source file to include a C-Interface to the C++ function
- added various header references pointing to the C-Interface function
- fixed reported version problems when trying to compile

Thanks for keeping it up to date

Hi, JHPJHP!

One more time about OpenCV+Tesseract OCR.
The example how to get confidence level in the Tesseract OCR: http://rgho.st/8yCH8cCjL (90 days)

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Update: liblept168.lib http://rgho.st/8ZPfh2cBK
Thanks, JHPJHP!

P.S. JHPJHP, I think you've already added this library in your package

Hi AAT,

Thank you for another great addition to the OCR Tesseract examples.

AAT wrote:P.S. JHPJHP, I think you've already added this library in your package

I replaced the binaries with files from an older prebuilt download that contained both 32 and 64 bit versions.

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Updated the Windows interfaces:
- added 1 example (contributed by AAT)
-- cv_OCR_confidence.pb: using Tesseract OCR (Optical Character Recognition) an image is translated to text displaying its confidence-level in stages

NB*: The 64bit Windows interface has been updated to support all 5 Tesseract examples.

Updated (Windows and OSX interfaces):
- added 1 example
-- cv_stippling.pb: stippling is the creation of a pattern simulating varying degrees of shading by using small dots
--- based on script found here

This was one of those examples that took longer then expected due to the conversion between Processing, PureBasic, and OpenCV :: Enjoy

NB*: Images may show varying degrees of detail based on size, color, and settings.

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Updated the example cv_stippling.pb: added the option to toggle between color and black dots.

That looks very nice

Hi wilbert,

Thank you for the comment. I knew if I was hear from anyone it would be you

Updated: cv_stippling.pb
- optimized various parts of the code, modified settings to better illustrate stippling and the repulsion field algorithm

JHPJHP wrote:optimized various parts of the code, modified settings, to better illustrate stippling and the repulsion field algorithm

It works fine on OSX

Updated (all interfaces):
- replaced 1 file
-- references/highgui.mht with references/highgui.pdf
- updated 1 example
-- cv_stippling.pb: optimized performance, added an option to reset stippling
- added 1 example
-- cv_cam_stippling.pb: stippling is the creation of a pattern simulating varying degrees of shading by using small dots

cv_stippling.pb
- to best demonstrate the repulsion field algorithm, press the [ C KEY ] switching to black dots, then press [ ENTER ] to reset stippling

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Updated:
- updated 2 examples
-- cv_stippling.pb: optimized the repulsion field algorithm
-- cv_cam_stippling.pb: optimized the repulsion field algorithm, added the option to toggle between stippling and webcam

Thanks for all your hard work

Hi wilbert,

You're most welcome

An alternate Stippling technique popular for its attention to detail is the Weighted Voronoi Stippling method, incorporating varying dot sizes to enhance results...

Updated
- updated 2 examples
-- cv_cam_stippling.pb: applied a couple small code improvements
-- cv_stippling.pb: switched from a static dot size to varying dot sizes based on color
- added 1 example
-- cv_repulsion_field.pb: each particle tries to find an optimum placement by pushing itself away from its neighbors

JHPJHP wrote:-- cv_stippling.pb: switched from a static dot size to varying dot sizes based on color
- added 1 example
-- cv_repulsion_field.pb: each particle tries to find an optimum placement by pushing itself away from its neighbors

I like the varying dot sizes better
The repulsion field example also looks nice.