imageprocessing | image processing algorithms like canny , histogram
kandi X-RAY | imageprocessing Summary
kandi X-RAY | imageprocessing Summary
imageprocessing is a C++ library. imageprocessing has no bugs, it has a Strong Copyleft License and it has low support. However imageprocessing has 1 vulnerabilities. You can download it from GitHub.
set of image processing algorithms like canny, histogram equalization, graph segmentation, etc with simple qt-based interface. some algorithms are very common and written exactly according to wikipedia. some details made up. graph based segmentation algorithms are based on gradient vector flow is based on dct based on vp8 spec: webmproject.org. interface is made from qt widgets and layouts, no xml-resources. all algorithms are packed by themes in classes (gvf and simple gradient, for example, in same class "gradients") each class has some slots for updating different coefficients like "update_xxx(const qstring&)" and for applying image processing "apply_xxx()". also each image processing class has a pointer to source image "qimage *srcimage" and rpcessed image "qimage *dstimage". these qimages must be created outside of processing classes and their pointers must be told to constructors of image processing classes (done in main.cpp → int main(argc argv)). class "image_interface" holds pointers to qimages(that contain original and processed pictures) and qlabels(widgets that will display corresponding qimages on updatesrcimage/updatedstimage calls);. each apply_xxx() method(slot) takes data from *srcimage processes it and puts into *dstimage. it also emits signals: image_ready() → when finished; print_message(const qstring&) → some messages to put them in graphical widgets instead of std streams print_progress(const int) → progress with 0 - the very start and 100 -
set of image processing algorithms like canny, histogram equalization, graph segmentation, etc with simple qt-based interface. some algorithms are very common and written exactly according to wikipedia. some details made up. graph based segmentation algorithms are based on gradient vector flow is based on dct based on vp8 spec: webmproject.org. interface is made from qt widgets and layouts, no xml-resources. all algorithms are packed by themes in classes (gvf and simple gradient, for example, in same class "gradients") each class has some slots for updating different coefficients like "update_xxx(const qstring&)" and for applying image processing "apply_xxx()". also each image processing class has a pointer to source image "qimage *srcimage" and rpcessed image "qimage *dstimage". these qimages must be created outside of processing classes and their pointers must be told to constructors of image processing classes (done in main.cpp → int main(argc argv)). class "image_interface" holds pointers to qimages(that contain original and processed pictures) and qlabels(widgets that will display corresponding qimages on updatesrcimage/updatedstimage calls);. each apply_xxx() method(slot) takes data from *srcimage processes it and puts into *dstimage. it also emits signals: image_ready() → when finished; print_message(const qstring&) → some messages to put them in graphical widgets instead of std streams print_progress(const int) → progress with 0 - the very start and 100 -
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imageprocessing has a low active ecosystem.
It has 1 star(s) with 0 fork(s). There are 2 watchers for this library.
It had no major release in the last 6 months.
imageprocessing has no issues reported. There are no pull requests.
It has a neutral sentiment in the developer community.
The latest version of imageprocessing is current.
Quality
imageprocessing has no bugs reported.
Security
imageprocessing has 1 vulnerability issues reported (0 critical, 1 high, 0 medium, 0 low).
License
imageprocessing is licensed under the GPL-3.0 License. This license is Strong Copyleft.
Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.
Reuse
imageprocessing releases are not available. You will need to build from source code and install.
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of imageprocessing
imageprocessing Key Features
No Key Features are available at this moment for imageprocessing.
imageprocessing Examples and Code Snippets
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Vulnerabilities
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Install imageprocessing
You can download it from GitHub.
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