Hi wilbert,
wilbert wrote:Good to see you are supporting Linux as well now.
Without your previous patience and support during the OSX conversion, the Linux interface may not have happened. Thank you for your positive comments.
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Updated the
Main Linux Interface with an additional 50 examples:
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cv_convexitydefects.pb: calculates the contour areas, finding the convex hull of point sets to convexity defects
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cv_copymakeborder.pb: show various border styles on a loaded image
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cv_cornerharris_1.pb: calculates a feature map for corner detection using the Harris edge detector
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cv_cornerharris_2.pb: calculates a feature map for corner detection using the Harris edge detector
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cv_cvtcolor.pb: converts an image from one color space to another
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cv_DCT.pb: performs a discrete cosine transform of a 1D array, first displaying its power spectrum then incrementally reducing noise
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cv_detect_hand.pb: contour extraction and calculation is used to determine finger locations
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cv_DFT.pb: performs a discrete Fourier transform of a 1D floating-point array, displaying its power spectrum
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cv_distortion_1.pb: distort a color image by manipulating pixel locations
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cv_distortion_2.pb: distort a grayscale image by manipulating pixel locations
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cv_disttransform_1.pb: calculates the distance to the closest zero pixel for each pixel of the source image
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cv_disttransform_2.pb: calculates the distance to the closest zero pixel for each pixel in the image
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cv_doodle.pb: utilizing OpenCV's mouse callback, adds the ability to doodle on the loaded image
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cv_draw_spiral.pb: draw a circular or square spiral
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cv_drawing.pb: a demonstration of OpenCV's drawing and text output functions
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cv_emboss_2.pb: apply a raised or pressed embossed style effects to an image
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cv_emboss_3.pb: using an extended Sobel operator an embossed effect is achieved
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cv_encode_decode.pb: encode / decode a 4 channel image where the black areas have been converted to transparency
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cv_enhance_detail.pb: enhance the details of an image
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cv_enhance_edges.pb: enhance the edges of an image in 2 stages using various filters
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cv_find_license_plate.pb: license plate recognition
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cv_find_shapes.pb: approximates a polygonal curve(s) with the specified precision
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cv_find_speed_sign.pb: speed sign recognition
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cv_find_squares.pb: find squares in an image
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cv_fisheye.pb: standard fisheye lens effect derived from mathematical equations
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cv_fitellipse_1.pb: creates a sequence of points, bounding them in an ellipse of the minimal area
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cv_fitellipse_2.pb: calculates the contour areas
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cv_flip.pb: flips a 2D array around vertical, horizontal, or both axes
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cv_floodfill.pb: demonstration of the FloodFill function, filling a connected component with a given color
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cv_folding.pb: transform an image to show a folding effect at a defined cycle
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cv_mov_runningavg_2.pb: calculates the weighted sum of the input image and the accumulator, so that the new image becomes a running average of a frame sequence
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cv_parametric_curve.pb: Parametric Curve: A curve defined as a function of independent variables
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cv_pb_font.pb: draw text using PureBasic commands with any font onto an OpenCV generated image
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cv_setimageROI.pb: simulates zooming a section of a resized image by loading the Region Of Interest (ROI) for a given rectangle from the original image
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cv_siemens_star.pb: Siemens Star: A pattern used to test the resolution of optical instruments, printers and displays
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cv_smooth_edges_1.pb: smooth the edges of an image using a normalized convolution filter
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cv_smooth_edges_2.pb: smooth the edges of an image using a recursive filter
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cv_solve_maze.pb: maze game / solve a maze using a morphological transformation
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cv_spider_web_1.pb: draw a Spider Web sketch from a color image
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cv_spider_web_2.pb: draw a Spider Web sketch from a gray-scale image
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cv_warpaffine.pb: calculates an affine transform from three pairs of corresponding points
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cv_warpperspective_1.pb: calculates a perspective transform from four pairs of corresponding points
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cv_warpperspective_2.pb: calculates a perspective transform from four pairs of corresponding points
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cv_water_ripples.pb: creates the illusion of water ripples on a background image
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cv_watershed.pb: performs a marker-based image segmentation using the watershed algorithm
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le_fitellipse_1.pb: creates a sequence of points, bounding them in an ellipse of the minimal area
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le_fitellipse_2.pb: calculates the contour areas
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le_minarearect_1.pb: creates a sequence of points, bounding them in a rectangle of the minimal area
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le_minarearect_2.pb: calculates the contour areas
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le_pyrsegmentation.pb: implementing image segmentation by pyramids, a cartoon effect is achieved