在MacOS中使用OpenCV开发
2020-08-10 本文已影响0人
跨端开发
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OpenCV是一个跨平台计算机视觉和机器学习软件库，可以运行在Linux、Windows、Android和Mac OS操作系统上。它轻量级而且高效——由一系列 C 函数和少量 C++ 类构成，同时提供了Python、Ruby、MATLAB等语言的接口，实现了图像处理和计算机视觉方面的很多通用算法。
最近使用Flutter开发一个OpenCV的APP，调试时需同时显示多个窗口，以显示不同输出目标，手机屏幕比较小，显示多个视图时就显得困难，即使能显示，也因为窗口太小，不好分辨目标输出内容。于是想在MacOS下先调试好，再把算法copy到iOS、Android下面。
在网上搜索了很多教程，大部分已经年代久远已经不能正常安装好。我目前使用MacOS 10.15 安装 OpenCV 4.0.1 (iOS pod库最新是4.0.1)，通过Cmake编译出farmework，可直接导入到Mac项目，使用上较导入动态库方便许多，减去了配置Search Paths的麻烦。
Demo已经开源：OpenCVSampleForMacOS ,请君自取
环境配置
1.首先需要安装Mac安装包管理器brew或MacPorts （已安装跳过此步骤）
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install.sh)"
2.再安装Cmake，使用它编译C++
brew install cmake
or
port install cmake
3.下载opencv.zip
使用浏览器到OpenCV GitHub下载页面https://github.com/opencv/opencv/releases下载你需要使用的OpenCV版本，我目前使用的是4.0.1
编译framework
1、解压OpenCV.zip
2、使用终端cd到OpenCV解压目录(e.g.)
cd ~/Desktop/opencv-4.0.1/
3、使用Python脚本编译opencv2.framework
python platforms/osx/build_framework.py frameworks
我的Mac编译时出现报错，我把build_framework.py中的MACOSX_DEPLOYMENT_TARGET改为10.13就编译成功了！有可能是默认的10.9会处理有关32位的问题。
build_framework.py位于解压文件目录的platforms/osx/下
修改后文件如下：
#!/usr/bin/env python
"""
The script builds OpenCV.framework for OSX.
"""
from __future__ import print_function
import os, os.path, sys, argparse, traceback, multiprocessing
# import common code
sys.path.insert(0, os.path.abspath(os.path.abspath(os.path.dirname(__file__))+'/../ios'))
from build_framework import Builder
class OSXBuilder(Builder):
def getToolchain(self, arch, target):
return None
def getBuildCommand(self, archs, target):
buildcmd = [
"xcodebuild",
"MACOSX_DEPLOYMENT_TARGET=10.13",
"ARCHS=%s" % archs[0],
"-sdk", target.lower(),
"-configuration", "Release",
"-parallelizeTargets",
"-jobs", str(multiprocessing.cpu_count())
]
return buildcmd
def getInfoPlist(self, builddirs):
return os.path.join(builddirs[0], "osx", "Info.plist")
if __name__ == "__main__":
folder = os.path.abspath(os.path.join(os.path.dirname(sys.argv[0]), "../.."))
parser = argparse.ArgumentParser(description='The script builds OpenCV.framework for OSX.')
parser.add_argument('out', metavar='OUTDIR', help='folder to put built framework')
parser.add_argument('--opencv', metavar='DIR', default=folder, help='folder with opencv repository (default is "../.." relative to script location)')
parser.add_argument('--contrib', metavar='DIR', default=None, help='folder with opencv_contrib repository (default is "None" - build only main framework)')
parser.add_argument('--without', metavar='MODULE', default=[], action='append', help='OpenCV modules to exclude from the framework')
parser.add_argument('--enable_nonfree', default=False, dest='enablenonfree', action='store_true', help='enable non-free modules (disabled by default)')
args = parser.parse_args()
b = OSXBuilder(args.opencv, args.contrib, False, False, args.without, args.enablenonfree,
[
(["x86_64"], "MacOSX")
])
b.build(args.out)
创建Mac项目，导入OpenCV
打开Xcode->File -> New Project，选择APP。
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输入项目名称OpenCVSample，Language选择Swift,User Innterface选择XIB
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在APPdelegate中配置window和contentViewController。
APPdelegate.swift
var mainWindowController: NSWindowController!
lazy var window: NSWindow = {
let w = NSWindow(contentRect: NSMakeRect(0, 0, 1007 , 641), styleMask: [.titled, .resizable, .miniaturizable, .closable, .fullSizeContentView], backing: .buffered, defer: false)
w.center()
w.backgroundColor = NSColor(calibratedRed: 0, green: 0, blue: 0, alpha: 1)
w.minSize = NSMakeSize(320, 240)
return w
}()
func applicationDidFinishLaunching(_ aNotification: Notification) {
// Insert code here to initialize your application
mainWindowController = NSWindowController(window: window)
mainWindowController.showWindow(nil)
mainWindowController.window?.makeKeyAndOrderFront(nil)
NSApplication.shared.mainWindow?.title = "OpenCV Sample"
let scanViewCtrl = ScanViewController()
window.contentViewController = scanViewCtrl
}
将MainMenu.xib中的默认window删除，删除后如下图所示：
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测试OpenCV
创建opencv视频处理桥接文件
CVCamera.h
@interface CVCamera : NSObject
- (id) initWithController: (NSViewController<CVCameraDelegate>*)c andCameraImageView: (NSImageView*)iv processImage: (NSImageView *)processIv;
- (void)start;
- (void)stop;
@end
CVCamera.mm
#import <opencv2/opencv.hpp>
#include "CVCamera.h"
using namespace cv;
using namespace std;
@interface CVCamera ()
@end
@implementation CVCamera
{
NSViewController<CVCameraDelegate> * delegate;
NSImageView * cameraimageView;
NSImageView * processimageView;
VideoCapture cap;
cv::Mat gtpl;
int cameraIndex;
NSTimer *timer;
}
- (id) initWithController: (NSViewController<CVCameraDelegate>*)c andCameraImageView: (NSImageView*)iv processImage:(NSImageView *)processIv
{
delegate = c;
cameraimageView = iv;
processimageView = processIv;
cameraIndex = -1;
timer = [NSTimer timerWithTimeInterval:30/1000.0 target:self selector:@selector(show_camera) userInfo:nil repeats:true];
[[NSRunLoop mainRunLoop] addTimer:timer forMode:NSRunLoopCommonModes];
return self;
}
- (void)processImage:(cv::Mat &)img {
cv::Mat gimg;
// Convert incoming img to greyscale to match template
cv::cvtColor(img, gimg, COLOR_BGR2GRAY);
// 5*5滤波
cv::Mat blurred;
cv::blur(gimg, blurred, cv::Size(5, 5));
imshow("blurred", blurred);
// 自适应二值化方法
cv::Mat adaptiveThreshold;
cv::adaptiveThreshold(blurred, adaptiveThreshold, 255, cv::ADAPTIVE_THRESH_MEAN_C, cv::THRESH_BINARY, 15, 5);
// canny边缘检测
cv::Mat edges;
cv::Canny(adaptiveThreshold, edges, 10, 100);
// 从边缘图中寻找轮廓
std::vector<std::vector<cv::Point>> contours;
findContours(edges, contours, cv::RETR_EXTERNAL, cv::CHAIN_APPROX_SIMPLE);
double maxArea = 0;
vector<cv::Point> approx;
vector<cv::Point> docCnt;
vector<cv::Point> maxAreaContour;
for (size_t i = 0; i < contours.size(); i++)
{
double area = contourArea(contours[i]);
if (area > maxArea) {
maxArea = area;
maxAreaContour = contours[i];
}
}
// approximate contour with accuracy proportional
// to the contour perimeter
approxPolyDP(maxAreaContour, approx, arcLength(maxAreaContour, true)*0.02, true);
// Note: absolute value of an area is used because
// area may be positive or negative - in accordance with the
// contour orientation
if (approx.size() == 4 &&
isContourConvex(Mat(approx)))
{
docCnt = approx;
std::vector<std::vector<cv::Point>> showContours(1);
showContours[0] = docCnt;
drawContours(img, showContours, -1, Scalar(208, 19, 29), 2);
}
}
- (void)start
{
[self openCamera];
}
- (void)stop
{
// videoCap.close();
}
- (void)openCamera {
VideoCapture capture = VideoCapture(0);
if (capture.isOpened()) {
self->cap = capture;
self->cameraIndex = 0;
} else {
VideoCapture capture_usb = VideoCapture(1);
if (capture_usb.isOpened()) {
self->cap = capture_usb;
self->cameraIndex = 1;
} else {
printf("未找到摄像头,请检查设备连接");
return;
}
}
self->cap.set(3, 1400);
self->cap.set(4, 1050);
[self->timer setFireDate:[NSDate distantPast]];
;
}
- (void)show_camera {
if (self->cap.isOpened()) {
Mat frame;
self->cap.read(frame);
NSImage *image = MatToNSImage(frame);
self->cameraimageView.image = image;
// processImage
Mat processFrame = frame.clone();
[self processImage:processFrame];
NSImage *processimage = MatToNSImage(processFrame);
self->processimageView.image = processimage;
}
// if (self.recongnitioned) {
// self.recognition()
// }
}
/// Converts an NSImage to Mat.
static void NSImageToMat(NSImage *image, cv::Mat &mat) {
// Create a pixel buffer.
NSBitmapImageRep *bitmapImageRep = [NSBitmapImageRep imageRepWithData:image.TIFFRepresentation];
NSInteger width = bitmapImageRep.pixelsWide;
NSInteger height = bitmapImageRep.pixelsHigh;
CGImageRef imageRef = bitmapImageRep.CGImage;
cv::Mat mat8uc4 = cv::Mat((int)height, (int)width, CV_8UC4);
CGColorSpaceRef colorSpace = CGColorSpaceCreateDeviceRGB();
CGContextRef contextRef = CGBitmapContextCreate(mat8uc4.data, mat8uc4.cols, mat8uc4.rows, 8, mat8uc4.step, colorSpace, kCGImageAlphaPremultipliedLast | kCGBitmapByteOrderDefault);
CGContextDrawImage(contextRef, CGRectMake(0, 0, width, height), imageRef);
CGContextRelease(contextRef);
CGColorSpaceRelease(colorSpace);
// Draw all pixels to the buffer.
cv::Mat mat8uc3 = cv::Mat((int)width, (int)height, CV_8UC3);
cv::cvtColor(mat8uc4, mat8uc3, cv::COLOR_RGBA2BGR);
mat = mat8uc3;
}
/// Converts a Mat to NSImage.
static NSImage *MatToNSImage(cv::Mat &mat) {
// Create a pixel buffer.
assert(mat.elemSize() == 1 || mat.elemSize() == 3);
cv::Mat matrgb;
if (mat.elemSize() == 1) {
cv::cvtColor(mat, matrgb, cv::COLOR_GRAY2RGB);
} else if (mat.elemSize() == 3) {
cv::cvtColor(mat, matrgb, cv::COLOR_BGR2RGB);
}
// Change a image format.
NSData *data = [NSData dataWithBytes:matrgb.data length:(matrgb.elemSize() * matrgb.total())];
CGColorSpaceRef colorSpace;
if (matrgb.elemSize() == 1) {
colorSpace = CGColorSpaceCreateDeviceGray();
} else {
colorSpace = CGColorSpaceCreateDeviceRGB();
}
CGDataProviderRef provider = CGDataProviderCreateWithCFData((__bridge CFDataRef)data);
CGImageRef imageRef = CGImageCreate(matrgb.cols, matrgb.rows, 8, 8 * matrgb.elemSize(), matrgb.step.p[0], colorSpace, kCGImageAlphaNone|kCGBitmapByteOrderDefault, provider, NULL, false, kCGRenderingIntentDefault);
NSBitmapImageRep *bitmapImageRep = [[NSBitmapImageRep alloc] initWithCGImage:imageRef];
NSImage *image = [NSImage new];
[image addRepresentation:bitmapImageRep];
CGImageRelease(imageRef);
CGDataProviderRelease(provider);
CGColorSpaceRelease(colorSpace);
return image;
}
+ (NSImage *)cvtColorBGR2GRAY:(NSImage *)image {
cv::Mat bgrMat;
NSImageToMat(image, bgrMat);
cv::Mat grayMat;
cv::cvtColor(bgrMat, grayMat, cv::COLOR_BGR2GRAY);
NSImage *grayImage = MatToNSImage(grayMat);
return grayImage;
}
@end
项目中使用swift语言开发，需要创建桥接文件OpenCVSampleForMacOS-Bridging-Header.h，并且在配置中设置桥接文件。
OpenCVSampleForMacOS-Bridging-Header.h
#ifndef OpenCVSampleForMacOS_Bridging_Header_h
#define OpenCVSampleForMacOS_Bridging_Header_h
#import "CVCamera.h"
#endif /* OpenCVSampleForMacOS_Bridging_Header_h */
创建一个展示视频内容的ScanViewController：
import Foundation
class ScanViewController: NSViewController, CVCameraDelegate {
lazy var previewImageView: NSImageView = {
let imgView = NSImageView(frame: NSRect(x: 10, y: 10, width: 480, height: 320))
return imgView
}()
lazy var processImageView: NSImageView = {
let imgView = NSImageView(frame: NSRect(x: 520, y: 10, width: 480, height: 320))
return imgView
}()
lazy var label: NSTextField = {
let v = NSTextField(labelWithString: "Press the button")
v.translatesAutoresizingMaskIntoConstraints = false
return v
}()
lazy var button: NSButton = {
let v = NSButton(frame: .zero)
v.translatesAutoresizingMaskIntoConstraints = false
return v
}()
var camera: CVCamera!
override func loadView() {
// 设置 ViewController 大小同 mainWindow
guard let windowRect = NSApplication.shared.windows.first?.frame else { return }
view = NSView(frame: windowRect)
}
override func viewDidLoad() {
super.viewDidLoad()
view.addSubview(label)
view.addSubview(button)
view.addSubview(previewImageView)
view.addSubview(processImageView)
camera = CVCamera(controller: self, andCameraImageView: previewImageView, processImage:processImageView);
NSLayoutConstraint.activate([
label.centerXAnchor.constraint(equalTo: view.centerXAnchor),
label.centerYAnchor.constraint(equalTo: view.centerYAnchor, constant: -20),
button.centerXAnchor.constraint(equalTo: view.centerXAnchor),
button.topAnchor.constraint(equalTo: label.bottomAnchor, constant: 20),
button.heightAnchor.constraint(equalToConstant: 30),
button.widthAnchor.constraint(equalToConstant: 100)
])
button.title = "开始"
button.target = self
button.action = #selector(onClickme)
}
func matchedItem() {
}
@objc func onClickme(_ sender: NSButton) {
label.textColor = .red
label.stringValue = "👌!"
camera.start()
}
}
结果
Command+R 运行结果如下所示：
通过openCV识别出最大边框并且进行显示。
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