小明编程每过几天就去看看OpenCV.org的更新，今天突然发现了一个有趣的东西。http://opencv.org/mastering-opencv-with-practical-computer-vision-projects.html。弄OpenCV的人出版了一个Mastering OpenCV with Practical Computer Vision Projects的书，也就是用OpenCV开发的一切有意思的项目。
使用OpenCV开发机器视觉项目
有以下9个章节
Chapters:
- Ch1) Cartoonifier and Skin Changer for Android, by Shervin Emami.
- Ch2) Marker-based Augmented Reality on iPhone or iPad, by Khvedchenia Ievgen.
- Ch3) Marker-less Augmented Reality, by Khvedchenia Ievgen.
- Ch4) Exploring Structure from Motion using OpenCV, by Roy Shilkrot.
- Ch5) Number Plate Recognition using SVM and Neural Networks, by David Escrivá.
- Ch6) Non-rigid Face Tracking, by Jason Saragih.
- Ch7) 3D Head Pose Estimation using AAM and POSIT, by Daniel Lélis Baggio.
- Ch8) Face Recognition using Eigenfaces or Fisherfaces, by Shervin Emami.
- Ch9) Developing Fluid Wall using the Microsoft Kinect, by Naureen Mahmood.
- Per-chapter Requirements:
- Ch1: webcam (for desktop app), or Android development system (for Android app).
- Ch2: iOS development system (to build an iOS app).
- Ch3: OpenGL built into OpenCV.
- Ch4: PCL (http://pointclouds.org/) and SSBA (http://www.inf.ethz.ch/personal/chzach/opensource.html).
- Ch5: nothing.
- Ch6: nothing, but requires training data for execution.
- Ch7: nothing.
- Ch8: webcam.
- Ch9: Kinect depth sensor.
Screenshots:
- Ch1) Cartoonifier and Skin Changer for Android:
- Ch2) Marker-based Augmented Reality on iPhone or iPad:
- Ch3) Marker-less Augmented Reality:
- Ch4) Exploring Structure from Motion using OpenCV:
- Ch5) Number Plate Recognition using SVM and Neural Networks:
- Ch6) Non-rigid Face Tracking:
- Ch7) 3D Head Pose Estimation using AAM and POSIT:
- Ch8) Face Recognition using Eigenfaces or Fisherfaces:
- Ch9) Developing Fluid Wall using the Microsoft Kinect:
看看，他们确实涵盖了当今最热门的一些机器视觉相关项目，其中包括我喜欢的Kinect，甚至我熟悉的人脸识别、人脸跟踪、人脸朝向估计等等(这么多关于人脸的！)，还包括虚拟现实之类技术，有时间也得看看。这本书可以买纸质版也可以买电子版，购买地址 PacktPub。好吧，估计一般人是买不到的，国外的书果然不便宜，$44.99
不过书中配套的项目源码倒是都有的！https://github.com/MasteringOpenCV/code
第一个项目：卡通画和肤色变化初探
我在windows上尝试编译了第一个例子(他既有android平台的代码也给出了PC平台的)。以下是截图：
第一张和第四张图片都是卡通图，第2张是evil状态的，所以有点惨不忍睹吧，第三张是素描。具体算法我还未去细读，给出下载第一个项目的VS2010地址。通过debug可以编译出可用的exe，而release尽然无法检测到摄像头以致exe无法运行，编译时注意。
给出主要的卡通画函数实现代码：
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/***************************************************************************** * cartoon.cpp * Create a cartoon-like or painting-like image filter. ****************************************************************************** * by Shervin Emami, 5th Dec 2012 (shervin.emami@gmail.com) * http://www.shervinemami.info/ ****************************************************************************** * Ch1 of the book "Mastering OpenCV with Practical Computer Vision Projects" * Copyright Packt Publishing 2012. * http://www.packtpub.com/cool-projects-with-opencv/book *****************************************************************************/ #include "cartoon.h" #include "ImageUtils.h" // Handy functions for debugging OpenCV images, by Shervin Emami. // Convert the given photo into a cartoon-like or painting-like image. // Set sketchMode to true if you want a line drawing instead of a painting. // Set alienMode to true if you want alien skin instead of human. // Set evilMode to true if you want an "evil" character instead of a "good" character. // Set debugType to 1 to show where skin color is taken from, and 2 to show the skin mask in a new window (for desktop). void cartoonifyImage(Mat srcColor, Mat dst, bool sketchMode, bool alienMode, bool evilMode, int debugType) { // Convert from BGR color to Grayscale Mat srcGray; cvtColor(srcColor, srcGray, CV_BGR2GRAY); // Remove the pixel noise with a good Median filter, before we start detecting edges. medianBlur(srcGray, srcGray, 7); Size size = srcColor.size(); Mat mask = Mat(size, CV_8U); Mat edges = Mat(size, CV_8U); if (!evilMode) { // Generate a nice edge mask, similar to a pencil line drawing. Laplacian(srcGray, edges, CV_8U, 5); threshold(edges, mask, 80, 255, THRESH_BINARY_INV); // Mobile cameras usually have lots of noise, so remove small // dots of black noise from the black & white edge mask. removePepperNoise(mask); } else { // Evil mode, making everything look like a scary bad guy. // (Where "srcGray" is the original grayscale image plus a medianBlur of size 7x7). Mat edges2; Scharr(srcGray, edges, CV_8U, 1, 0); Scharr(srcGray, edges2, CV_8U, 1, 0, -1); edges += edges2; threshold(edges, mask, 12, 255, THRESH_BINARY_INV); medianBlur(mask, mask, 3); } //imshow("edges", edges); //imshow("mask", mask); // For sketch mode, we just need the mask! if (sketchMode) { // The output image has 3 channels, not a single channel. cvtColor(mask, dst, CV_GRAY2BGR); return; } // Do the bilateral filtering at a shrunken scale, since it // runs so slowly but doesn't need full resolution for a good effect. Size smallSize; smallSize.width = size.width/2; smallSize.height = size.height/2; Mat smallImg = Mat(smallSize, CV_8UC3); resize(srcColor, smallImg, smallSize, 0,0, INTER_LINEAR); // Perform many iterations of weak bilateral filtering, to enhance the edges // while blurring the flat regions, like a cartoon. Mat tmp = Mat(smallSize, CV_8UC3); int repetitions = 7; // Repetitions for strong cartoon effect. for (int i=0; i<repetitions; i++) { int size = 9; // Filter size. Has a large effect on speed. double sigmaColor = 9; // Filter color strength. double sigmaSpace = 7; // Positional strength. Effects speed. bilateralFilter(smallImg, tmp, size, sigmaColor, sigmaSpace); bilateralFilter(tmp, smallImg, size, sigmaColor, sigmaSpace); } if (alienMode) { // Apply an "alien" filter, when given a shrunken image and the full-res edge mask. // Detects the color of the pixels in the middle of the image, then changes the color of that region to green. changeFacialSkinColor(smallImg, edges, debugType); } // Go back to the original scale. resize(smallImg, srcColor, size, 0,0, INTER_LINEAR); // Clear the output image to black, so that the cartoon line drawings will be black (ie: not drawn). memset((char*)dst.data, 0, dst.step * dst.rows); // Use the blurry cartoon image, except for the strong edges that we will leave black. srcColor.copyTo(dst, mask); } // Apply an "alien" filter, when given a shrunken BGR image and the full-res edge mask. // Detects the color of the pixels in the middle of the image, then changes the color of that region to green. void changeFacialSkinColor(Mat smallImgBGR, Mat bigEdges, int debugType) { // Convert to Y'CrCb color-space, since it is better for skin detection and color adjustment. Mat yuv = Mat(smallImgBGR.size(), CV_8UC3); cvtColor(smallImgBGR, yuv, CV_BGR2YCrCb); // The floodFill mask has to be 2 pixels wider and 2 pixels taller than the small image. // The edge mask is the full src image size, so we will shrink it to the small size, // storing into the floodFill mask data. int sw = smallImgBGR.cols; int sh = smallImgBGR.rows; Mat maskPlusBorder = Mat::zeros(sh+2, sw+2, CV_8U); Mat mask = maskPlusBorder(Rect(1,1,sw,sh)); // mask is a ROI in maskPlusBorder. resize(bigEdges, mask, smallImgBGR.size()); // Make the mask values just 0 or 255, to remove weak edges. threshold(mask, mask, 80, 255, THRESH_BINARY); // Connect the edges together, if there was a pixel gap between them. dilate(mask, mask, Mat()); erode(mask, mask, Mat()); //imshow("constraints for floodFill", mask); // YCrCb Skin detector and color changer using multiple flood fills into a mask. // Apply flood fill on many points around the face, to cover different shades & colors of the face. // Note that these values are dependent on the face outline, drawn in drawFaceStickFigure(). int const NUM_SKIN_POINTS = 6; Point skinPts[NUM_SKIN_POINTS]; skinPts[0] = Point(sw/2, sh/2 - sh/6); skinPts[1] = Point(sw/2 - sw/11, sh/2 - sh/6); skinPts[2] = Point(sw/2 + sw/11, sh/2 - sh/6); skinPts[3] = Point(sw/2, sh/2 + sh/16); skinPts[4] = Point(sw/2 - sw/9, sh/2 + sh/16); skinPts[5] = Point(sw/2 + sw/9, sh/2 + sh/16); // Skin might be fairly dark, or slightly less colorful. // Skin might be very bright, or slightly more colorful but not much more blue. const int LOWER_Y = 60; const int UPPER_Y = 80; const int LOWER_Cr = 25; const int UPPER_Cr = 15; const int LOWER_Cb = 20; const int UPPER_Cb = 15; Scalar lowerDiff = Scalar(LOWER_Y, LOWER_Cr, LOWER_Cb); Scalar upperDiff = Scalar(UPPER_Y, UPPER_Cr, UPPER_Cb); // Instead of drawing into the "yuv" image, just draw 1's into the "maskPlusBorder" image, so we can apply it later. // The "maskPlusBorder" is initialized with the edges, because floodFill() will not go across non-zero mask pixels. Mat edgeMask = mask.clone(); // Keep an duplicate copy of the edge mask. for (int i=0; i<NUM_SKIN_POINTS; i++) { // Use the floodFill() mode that stores to an external mask, instead of the input image. const int flags = 4 | FLOODFILL_FIXED_RANGE | FLOODFILL_MASK_ONLY; floodFill(yuv, maskPlusBorder, skinPts[i], Scalar(), NULL, lowerDiff, upperDiff, flags); if (debugType >= 1) circle(smallImgBGR, skinPts[i], 5, CV_RGB(0, 0, 255), 1, CV_AA); } if (debugType >= 2) imshow("flood mask", mask*120); // Draw the edges as white and the skin region as grey. // After the flood fill, "mask" contains both edges and skin pixels, whereas // "edgeMask" just contains edges. So to get just the skin pixels, we can remove the edges from it. mask -= edgeMask; // "mask" now just contains 1's in the skin pixels and 0's for non-skin pixels. // Change the color of the skin pixels in the given BGR image. int Red = 0; int Green = 70; int Blue = 0; add(smallImgBGR, Scalar(Blue, Green, Red), smallImgBGR, mask); } // Remove black dots (upto 4x4 in size) of noise from a pure black & white image. // ie: The input image should be mostly white (255) and just contains some black (0) noise // in addition to the black (0) edges. void removePepperNoise(Mat &mask) { // For simplicity, ignore the top & bottom row border. for (int y=2; y<mask.rows-2; y++) { // Get access to each of the 5 rows near this pixel. uchar *pThis = mask.ptr(y); uchar *pUp1 = mask.ptr(y-1); uchar *pUp2 = mask.ptr(y-2); uchar *pDown1 = mask.ptr(y+1); uchar *pDown2 = mask.ptr(y+2); // For simplicity, ignore the left & right row border. pThis += 2; pUp1 += 2; pUp2 += 2; pDown1 += 2; pDown2 += 2; for (int x=2; x<mask.cols-2; x++) { uchar v = *pThis; // Get the current pixel value (either 0 or 255). // If the current pixel is black, but all the pixels on the 2-pixel-radius-border are white // (ie: it is a small island of black pixels, surrounded by white), then delete that island. if (v == 0) { bool allAbove = *(pUp2 - 2) && *(pUp2 - 1) && *(pUp2) && *(pUp2 + 1) && *(pUp2 + 2); bool allLeft = *(pUp1 - 2) && *(pThis - 2) && *(pDown1 - 2); bool allBelow = *(pDown2 - 2) && *(pDown2 - 1) && *(pDown2) && *(pDown2 + 1) && *(pDown2 + 2); bool allRight = *(pUp1 + 2) && *(pThis + 2) && *(pDown1 + 2); bool surroundings = allAbove && allLeft && allBelow && allRight; if (surroundings == true) { // Fill the whole 5x5 block as white. Since we know the 5x5 borders // are already white, just need to fill the 3x3 inner region. *(pUp1 - 1) = 255; *(pUp1 + 0) = 255; *(pUp1 + 1) = 255; *(pThis - 1) = 255; *(pThis + 0) = 255; *(pThis + 1) = 255; *(pDown1 - 1) = 255; *(pDown1 + 0) = 255; *(pDown1 + 1) = 255; } // Since we just covered the whole 5x5 block with white, we know the next 2 pixels // won't be black, so skip the next 2 pixels on the right. pThis += 2; pUp1 += 2; pUp2 += 2; pDown1 += 2; pDown2 += 2; } // Move to the next pixel. pThis++; pUp1++; pUp2++; pDown1++; pDown2++; } } } // Draw an anti-aliased face outline, so the user knows where to put their face. // Note that the skin detector for "alien" mode uses points around the face based on the face // dimensions shown by this function. void drawFaceStickFigure(Mat dst) { Size size = dst.size(); int sw = size.width; int sh = size.height; // Draw the face onto a color image with black background. Mat faceOutline = Mat::zeros(size, CV_8UC3); Scalar color = CV_RGB(255,255,0); // Yellow int thickness = 4; // Use 70% of the screen height as the face height. int faceH = sh/2 * 70/100; // "faceH" is actually half the face height (ie: radius of the ellipse). // Scale the width to be the same nice shape for any screen width (based on screen height). int faceW = faceH * 72/100; // Use a face with an aspect ratio of 0.72 // Draw the face outline. ellipse(faceOutline, Point(sw/2, sh/2), Size(faceW, faceH), 0, 0, 360, color, thickness, CV_AA); // Draw the eye outlines, as 2 half ellipses. int eyeW = faceW * 23/100; int eyeH = faceH * 11/100; int eyeX = faceW * 48/100; int eyeY = faceH * 13/100; // Set the angle and shift for the eye half ellipses. int eyeA = 15; // angle in degrees. int eyeYshift = 11; // Draw the top of the right eye. ellipse(faceOutline, Point(sw/2 - eyeX, sh/2 - eyeY), Size(eyeW, eyeH), 0, 180+eyeA, 360-eyeA, color, thickness, CV_AA); // Draw the bottom of the right eye. ellipse(faceOutline, Point(sw/2 - eyeX, sh/2 - eyeY - eyeYshift), Size(eyeW, eyeH), 0, 0+eyeA, 180-eyeA, color, thickness, CV_AA); // Draw the top of the left eye. ellipse(faceOutline, Point(sw/2 + eyeX, sh/2 - eyeY), Size(eyeW, eyeH), 0, 180+eyeA, 360-eyeA, color, thickness, CV_AA); // Draw the bottom of the left eye. ellipse(faceOutline, Point(sw/2 + eyeX, sh/2 - eyeY - eyeYshift), Size(eyeW, eyeH), 0, 0+eyeA, 180-eyeA, color, thickness, CV_AA); // Draw the bottom lip of the mouth. int mouthY = faceH * 53/100; int mouthW = faceW * 45/100; int mouthH = faceH * 6/100; ellipse(faceOutline, Point(sw/2, sh/2 + mouthY), Size(mouthW, mouthH), 0, 0, 180, color, thickness, CV_AA); // Draw anti-aliased text. int fontFace = FONT_HERSHEY_COMPLEX; float fontScale = 1.0f; int fontThickness = 2; putText(faceOutline, "Put your face here", Point(sw * 23/100, sh * 10/100), fontFace, fontScale, color, fontThickness, CV_AA); //imshow("faceOutline", faceOutline); // Overlay the outline with alpha blending. addWeighted(dst, 1.0, faceOutline, 0.7, 0, dst, CV_8UC3); } |
这些项目有趣，并且十分实用，很可能进而在其基础上开发更多十分有趣的项目。希望更多的人来研读这些代码，并作分享。
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