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Xflow image processing operator list
Converts an input color image to grayscale image.
s = 0.2126 * r + 0.7152 * g + 0.0722 * b
Signature
output = xflow.grayscale(input)
@param texture input color image @return texture output grayscale image
Complements colors of an input image.
output = 255 - input (channel-wise)
Signature
output = xflow.complement(input)
@param texture input input color image @return texture output color complement of the input image
Dims an input image by a ratio.
output = ratio * input (channel-wise)
Signature
output = xflow.dim(input, ratio)
@param texture input input image @param float ratio dimming ratio (positive) @return texture output dimmed image
Thresholds an input grayscale image by a given threshold value.
output = (input > threshold) ? 255 : 0
Signature
output = xflow.threshold(input, threshold)
@param texture input input grayscale image @param int threshod threshold value [0,255] @return texture output thresholded grayscale image
Slices an input image for colors of interest within an RGB sphere of a given radius centered at a given color. All other colors would become white.
Signature
output = xflow.sliceColor(input, color, radius)
@param texture input input image @param int color key color (color of interest) @param float radius radius of the sphere centered at key color (positive) @return texture output color sliced output image
Multiplies a 4x4 float color weight matrix to an input image.
output = weights * input (matrix multiplication)
Signature
output = xflow.mulColorMatrix(input, weights)
@param texture input input image @param float weights 4x4 color weight matrix @return texture output output image with the new color tone
Creates a 4x4 saturate weight matrix according to a saturation degree (weight) to be used with xflow.mulColorMatrix. Weights are based on SVG filter effects.
Signature
output = xflow.createSaturateMatrix(weight)
@param float weight weight value @return float output a 4x4 saturate weight matrix
Masks first image with second image according to a weight value.
output = input1 + weight * input2 (channel-wise)
Signature
output = xflow.mask(input1, input2, weight)
@param texture input1 first input image @param texture input2 second input image @param texture weight masking weight @return texture output input1 masked with input2 result
Returns channel-wise magnitude (Euclidean norm) of two input images in a new image.
output = sqrt(input1^2 + input2^2) (channel-wise)
Signature
output = xflow.getChannelMagnitude(input1, input2)
@param texture input1 first input image @param texture input2 second input image @return texture output channel-wise magnitude of first and second input images