Görüntü işleme hızla popülerleşen ve gittikçe daha fazla üzerine projeler geliştirilen ve hatta hayatımızda kullandığımız araç gereçlerde kullanılan bir alan olmaya başladı. Bu durumda bir sürü insan bu konu üzerine bir şeyler yapmak istiyor fakat daha kurulum aşamasında veya kaynak yetersizliğinden dolayı bu ilgilerinden vazgeçiyorlar. Bu sorun için önerebileceğim bir çözüm var. SimpleCV!
SimpleCV'nin opencv ve matlab ile karşılaştırıldığı makaleye buradan ulaşabilirsiniz.
http://simplecv.org/download/
SimpleCV görüntü işlemeyle alakalı paketlerin bir arada toplandığı bir python paketler bütünüdür. yukarıdaki linkten kurulum dosyasını indirip sadece bir kaç tık ile kurabilirsiniz.
SimpleCV ile yüklediğimiz paketler ise şöyle:
Görüldüğü gibi Python'un bile yüklü olmasına gerek yok ihtiyacımız olan tüm paketler bir kaç tık ile yükleniyor. Aşağıda basit bir SimpleCV kodu bulunmakta aynı zamanda aşağıdaki linklerden dökümantasyona ve örneklere bakabilirsiniz.
http://simplecv.readthedocs.io/en/latest/
http://examples.simplecv.org/en/latest/
from SimpleCV import Camera
# Initialize the camera
cam = Camera()
# Loop to continuously get images
while True:
# Get Image from camera
img = cam.getImage()
# Make image black and white
img = img.binarize()
# Draw the text "Hello World" on image
img.drawText("Hello World!")
# Show the image
img.show()SimpleCV fonksiyonları ve kullanımları:
Description
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SimpleCV
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Reading an image
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Image(’lenna.png’)
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Converting the image to RGB colorspace
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img.toRGB()
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Converting the image to BGR colorspace
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img.toBGR()
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Converting the image to HLS colorspace
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img.toHLS()
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Converting the image to HSV colorspace
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img.toHSV()
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Converting the image to XYZ colorspace
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img.toXYZ()
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Converting the image to GRAY colorspace
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img.toGray()
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Create a new, empty OpenCV bitmap
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img.getEmpty(channels)
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Full copy of the image
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img.copy()
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Resize the image
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img.resize(x,y)
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Invert image
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img.invert()
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Horizontally mirror an image
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img.flipHorizontal()
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Vertically mirror an image
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img.flipVertical()
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Stretch filter on a greyscale image
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img.stretch(thresh low, thresh high)
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Binary threshold
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img.binarize(thresh, maxv,
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of the image
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blocksize, p)
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Mean color of the image
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img.meanColor()
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Finds the FeatureSet strongest corners first
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img.findCorners(maxnum, minquality, mindistance)
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Blobs are continuous light regions
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img.findBlobs(threshval, minsize, maxsize, threshblocksize, threshconstant)
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Finding the location of a known object
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findHaarFeatures(self, cascade,
scale factor, min neighbors, use canny)
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Uploading the Image to Imgur or Flickr
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img.upload(dest,api key, api secret,verbose)
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Smooth the image
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img.smooth(algorithm name, aperature, sigma, spatial sigma, grayscale)
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Draw a circle on the Image
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img.drawCircle(ctr, rad, color, thickness)
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Draw a line
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img.drawLine(pt1, pt2, color, thickness)
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Size of image
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img.size()
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Split the image into a series of image chunks
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img.split(cols, rows)
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Images of R,G,B channels are recombined into a single image
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img.mergeChannels(r,b,g)
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Apply a color correction curve in HSL space
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img.applyHLSCurve(hCurve, lCurve, sCurve)
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Apply a color correction curve in RGB space
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img.applyRGBCurve(rCurve, gCurve, bCurve)
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Applies Intensity to
all three color channels
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img.applyIntensityCurve(curve)
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Returns Image of the string
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img.toString()
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Split the channels
of an image into RGB
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img.splitChannels(grayscale)
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Returns image representing the distance of each pixel from a given color tuple
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img.colorDistance(color)
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Apply morphological erosion to a image
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img.erode(iterations)
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Apply morphological dilation to a image
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img.dilate(iterations)
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Histogram equalization on the image
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img.equalize()
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Applies erosion operation followed by a morphological dilation
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img.morphOpen()
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The difference between the morphological dilation and
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img.morphGradient()
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the morphological gradient
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1D histogram(numpy array) of intensity for pixels
in the image
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img.histogram(numbins)
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The histogram of the hue channel for the image
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img.hueHistogram(bins)
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Returns the peak hue values histogram of hues
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img.huePeaks(bins)
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Add two images
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img. add (other)
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Subtract two images Or two images
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img. sub (other) img. or (other)
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Image division operation taking two images as input
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img. div (other)
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Raises every array element in image array to a power
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img. pow (other)
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Finds 2d and 1d
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barcodes in the image
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img.findBarcode(zxing path)
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Finds line segments
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img.findLines(threshold, minlinelength,
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in the image
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maxlinegap, cannyth1, cannyth2)
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Finds a chessboard
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img.findChessboard(dimensions, subpixel)
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within that image
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Canny edge detection method
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img.edges(t1, t2)
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function rotates an image
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around a specific point
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img.rotate(angle, fixed, point, scale)
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by the given angle
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return a shear-ed image
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from the cornerpoints
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img.shear(cornerpoints)
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Function for warp
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performs an affine rotation
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img.transformPerspective(rotMatrix)
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Returns the RGB value for
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a particular image pixel
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img.getPixel(x, y)
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Returns a single row of RGB values from the image
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img.getHorzScanline(row)
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Returns a single column of gray values from the image
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getVertScanlineGray(column)
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Returns a single row of gray values from the image
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getHorzScanlineGray(row)
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Crops the image based on parameters
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img.crop(x , y, w, h, centered)
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Returns the selected region.
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img.regionSelect(x1, y1, x2, y2 )
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Clears out the entire image
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img.clear()
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Draws the string on the image at the specified coordinates.
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img.drawText(text , x , y , color, fontsize)
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Draw a rectangle on the image
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img.drawRectangle(x,y,w,h,color,width,alpha)
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Shows the current image
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img.show(type)
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Push a new drawing layer onto the back of the layer stack
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img.addDrawingLayer(layer)
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Insert a new layer into the
layer stack at the specified index
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img.insertDrawingLayer(layer, index)
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Remove a layer from the layer stack based on the layer’s index
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img.removeDrawingLayer(index)
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Return a drawing layer based on the index
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img.getDrawingLayer(index)
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Returns the gray value for a particular image pixel
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img.getGrayPixel( x, y)
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Returns a single column of RGB values from the image
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img.getVertScanline(column)
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Remove all of the drawing layers
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img.clearLayers()
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Return the array of DrawingLayer objects
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img.layers()
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Return all DrawingLayer objects as a single DrawingLayer.
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img.mergedLayers()
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Render all of the layers onto the current image
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img.applyLayers(indicies)
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automatically adjust image size to match the display size
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img.adaptiveScale(resolution,fit=True)
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Combine two images as a side by side images
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img1.sideBySide(img2, side, scale)
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Generate a binary mask of the image based on a range of rgb values
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createBinaryMask(self,color1,color2)
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Make the canvas larger but keep the image the same size
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img.embiggen(size, color, pos)
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The white areas of the mask will be kept and the black areas removed
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img.applyBinaryMask(mask,bg color)
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Generate a grayscale or binary mask image based either on a hue or an RGB triplet
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img.createAlphaMask(hue, hue lb,hue ub)
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Apply a function to every pixel and return the result
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img.applyPixelFunction(theFunc)
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Calculate the integral image and return it as a numpy array
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img.integralImage(tilted)
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Convolution performs a shape change on an image.
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img.convolve(,kernel,center)
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Function searches an image for a template image
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img.findTemplate(template image, threshold, method)
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Return any text it can find using OCR on the image
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img.readText()
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extract perfect circles from the image
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img.findCircle(canny,thresh,distance)
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Attempts to perform automatic white balancing
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img.whiteBalance(method)
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Apply a LUT (look up table) to the pixels in a image
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img.applyLUT(rLUT,bLUT,gLUT)
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Finds keypoints in an image and returns them as the raw keypoints
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img. getRawKeypoints(thresh,flavor, highQuality, forceReset)
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Method does a fast local approximate nearest neighbors (FLANN) calculation between two sets of feature vectors
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img. getFLANNMatches(sd,td
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Calculates keypoints for both images, determines the keypoint correspondences
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img.drawKeypointMatches(template, thresh, minDist,width)
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Match a template image with another image using SURF keypoints.
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img.findKeypointMatch(template, quality,minDist,minMatch)
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This method finds keypoints in an image and returns them as a feature set
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img.findKeypoints(min quality, flavor,highQuality)
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Returns the colors in the palette of the image
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img.getPalette(bins,hue)
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Takes in the palette from another image and attempts to apply it to this image
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img.rePalette(palette,hue)
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returns the visual representation (swatches) of the palette
in an image
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img.drawPaletteColors(size,horizontal,bins,hue)
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The method then goes through and replaces each pixel with the centroid of the clutsters found by k-means
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img.palettize(bins,hue)
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Palettization and behaves similar to the fndBlobs
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img.findBlobsFromPalette(palette selection, minsize, maxsize)
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Method uses the color palette to generate a binary image
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img.binarizeFromPalette(palette selection)
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Returns the RAW DFT transform of an image
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img.rawDFTImage(grayscale)
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Method applies a simple band pass DFT filter
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img.bandPassFilter(xCutoffLow, xCutoffHigh, yCutoffLow, yCutoffHigh,grayscale)
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Skeletonization of the image
smartThreshold uses a method
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img.skeletonize(radius)
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graph cut, to automagically
generate a grayscale mask image
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img.smartThreshold(mask, rect)
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It takes a image converts it
to grayscale, and applies a threshold
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img.smartFindBlobs(mask,rect,thresh level)
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This method is same as Paint bucket tool in image
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img.floodFill(points,tolerance,color,
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manipulation program
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lower,upper,fixed range)
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Returns Image where the values similar to the seed pixel have
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img.floodFillToMask(points,tolerance,
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been replaced by the input color
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color,lower,upper,fixed range,mask)
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A featureset of blobs form the Mask Image
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img.findBlobsFromMask(mask,threshold, minsize, maxsize )
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Returns the log value of the magnitude image of the DFT transform
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img.getDFTLogMagnitude(grayscale)
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Apply an arbitrary filter to the DFT of an image
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img.applyDFTFilter(flt,grayscale)
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Applies a high pass DFT filter
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img.highPassFilter(xCutoff,yCutoff,grayscale)
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Applies a low pass DFT filter
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img.lowPassFilter(xCutoff,yCutoff,grayscale)
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Method performs an inverse discrete Fourier transform
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InverseDFT(raw dft image)
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DFT is applied on image using gaussian lowpass filter
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img.applyUnsharpMask(boost,dia,grayscale)
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Performs an optical flow calculation and attempts to find motion between two subsequent frames
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img.findMotion(previous frame, window, method, aggregate)
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Creates a butterworth filter of 64x64 pixels, resizes it
to fit the image
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img.applyButterworthFilter(dia, order,highpass,grayscale)
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Creates a gaussian filter of 64x64 pixels, resizes it to fit image
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img.applyGaussianFilter(dia, highpass, grayscale)
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Etiketler: Görüntü İşleme, SimpleCV