photo
library
Functions
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colorChange(InputArray src, InputArray mask, {double redMul = 1.0, double greenMul = 1.0, double blueMul = 1.0})
→ Mat
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ColorChange mix two differently colored versions of an image seamlessly.
For further details, please see:
https://docs.opencv.org/master/df/da0/group__photo__clone.html#ga6684f35dc669ff6196a7c340dc73b98e
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colorChangeAsync(InputArray src, InputArray mask, {double redMul = 1.0, double greenMul = 1.0, double blueMul = 1.0})
→ Future<Mat>
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detailEnhance(InputArray src, {double sigmaS = 10, double sigmaR = 0.15})
→ Mat
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DetailEnhance filter enhances the details of a particular image
For further details, please see:
https://docs.opencv.org/4.x/df/dac/group__photo__render.html#ga0de660cb6f371a464a74c7b651415975
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detailEnhanceAsync(InputArray src, {double sigmaS = 10, double sigmaR = 0.15})
→ Future<Mat>
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edgePreservingFilter(InputArray src, {int flags = 1, double sigmaS = 60, double sigmaR = 0.4})
→ Mat
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EdgePreservingFilter filtering is the fundamental operation in image and video processing.
Edge-preserving smoothing filters are used in many different applications.
For further details, please see:
https://docs.opencv.org/4.x/df/dac/group__photo__render.html#gafaee2977597029bc8e35da6e67bd31f7
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edgePreservingFilterAsync(InputArray src, {int flags = 1, double sigmaS = 60, double sigmaR = 0.4})
→ Future<Mat>
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fastNlMeansDenoising(InputArray src, {double h = 3, int templateWindowSize = 7, int searchWindowSize = 21})
→ Mat
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FastNlMeansDenoising performs image denoising using Non-local Means Denoising algorithm
http://www.ipol.im/pub/algo/bcm_non_local_means_denoising/
For further details, please see:
https://docs.opencv.org/4.x/d1/d79/group__photo__denoise.html#ga4c6b0031f56ea3f98f768881279ffe93
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fastNlMeansDenoisingAsync(InputArray src, {double h = 3, int templateWindowSize = 7, int searchWindowSize = 21})
→ Future<Mat>
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fastNlMeansDenoisingColored(InputArray src, {double h = 3, double hColor = 3, int templateWindowSize = 7, int searchWindowSize = 21})
→ Mat
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FastNlMeansDenoisingColored is a modification of fastNlMeansDenoising function for colored images.
For further details, please see:
https://docs.opencv.org/4.x/d1/d79/group__photo__denoise.html#ga21abc1c8b0e15f78cd3eff672cb6c476
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fastNlMeansDenoisingColoredAsync(InputArray src, {double h = 3, double hColor = 3, int templateWindowSize = 7, int searchWindowSize = 21})
→ Future<Mat>
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fastNlMeansDenoisingColoredMulti(VecMat srcImgs, int imgToDenoiseIndex, int temporalWindowSize, {double h = 3, double hColor = 3, int templateWindowSize = 7, int searchWindowSize = 21})
→ Mat
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FastNlMeansDenoisingColoredMulti denoises the selected images.
For further details, please see:
https://docs.opencv.org/master/d1/d79/group__photo__denoise.html#gaa501e71f52fb2dc17ff8ca5e7d2d3619
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fastNlMeansDenoisingColoredMultiAsync(VecMat srcImgs, int imgToDenoiseIndex, int temporalWindowSize, {double h = 3, double hColor = 3, int templateWindowSize = 7, int searchWindowSize = 21})
→ Future<Mat>
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illuminationChange(InputArray src, InputArray mask, {double alpha = 0.2, double beta = 0.4})
→ Mat
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IlluminationChange modifies locally the apparent illumination of an image.
For further details, please see:
https://docs.opencv.org/master/df/da0/group__photo__clone.html#gac5025767cf2febd8029d474278e886c7
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illuminationChangeAsync(InputArray src, InputArray mask, {double alpha = 0.2, double beta = 0.4})
→ Future<Mat>
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inpaint(InputArray src, InputArray inpaintMask, double inpaintRadius, int flags)
→ Mat
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Inpaint reconstructs the selected image area from the pixel near the area boundary.
The function may be used to remove dust and scratches from a scanned photo, or to
remove undesirable objects from still images or video.
For further details, please see:
https://docs.opencv.org/4.x/d7/d8b/group__photo__inpaint.html#gaedd30dfa0214fec4c88138b51d678085
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inpaintAsync(InputArray src, InputArray inpaintMask, double inpaintRadius, int flags)
→ Future<Mat>
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pencilSketch(InputArray src, {double sigmaS = 60, double sigmaR = 0.07, double shadeFactor = 0.02})
→ (Mat, Mat)
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PencilSketch pencil-like non-photorealistic line drawing.
For further details, please see:
https://docs.opencv.org/4.x/df/dac/group__photo__render.html#gae5930dd822c713b36f8529b21ddebd0c
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pencilSketchAsync(InputArray src, {double sigmaS = 60, double sigmaR = 0.07, double shadeFactor = 0.02})
→ Future<(Mat, Mat)>
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seamlessClone(InputArray src, InputArray dst, InputArray mask, Point p, int flags)
→ Mat
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SeamlessClone blend two image by Poisson Blending.
For further details, please see:
https://docs.opencv.org/master/df/da0/group__photo__clone.html#ga2bf426e4c93a6b1f21705513dfeca49d
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seamlessCloneAsync(InputArray src, InputArray dst, InputArray mask, Point p, int flags)
→ Future<Mat>
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stylization(InputArray src, {double sigmaS = 60, double sigmaR = 0.45})
→ Mat
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Stylization aims to produce digital imagery with a wide variety of effects
not focused on photorealism. Edge-aware filters are ideal for stylization,
as they can abstract regions of low contrast while preserving, or enhancing,
high-contrast features.
For further details, please see:
https://docs.opencv.org/4.x/df/dac/group__photo__render.html#gacb0f7324017df153d7b5d095aed53206
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stylizationAsync(InputArray src, {double sigmaS = 60, double sigmaR = 0.45})
→ Future<Mat>
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textureFlattening(InputArray src, InputArray mask, {double lowThreshold = 30, double highThreshold = 45, int kernelSize = 3})
→ Mat
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TextureFlattening washes out the texture of the selected region, giving its contents a flat aspect.
For further details, please see:
https://docs.opencv.org/master/df/da0/group__photo__clone.html#gad55df6aa53797365fa7cc23959a54004
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textureFlatteningAsync(InputArray src, InputArray mask, {double lowThreshold = 30, double highThreshold = 45, int kernelSize = 3})
→ Future<Mat>
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