前段時間的一個週末,一個女生讓我幫她換一下他的證件照背景,我又沒帶電腦。我又很差意思拒接,怎麼辦呢?應用商店下載一個證件照換背景的APP,瞬間換完,我正準備保存時,跳出來一個支付框,若是你要保存,支付2元錢,出於面子,我只好掏了2塊錢,保存了。因而我就想,這種技術活,還給別人付錢,本身來擼吧.我是一個專職Android開發,那麼就用Android來擼吧.html
先來了解一下Android裏原生API對圖片操做,通常有兩種方式,java
這兩種操做我都寫了對應的文章,能夠快速查看python
今天的主題是在Android裏使用OpenCv來操做圖片,並實現兩個不一樣的效果,換證件照背景和污點修復.c++
代碼已經託管在Github上,和上兩篇文章代碼地址同樣,分支with-photo-changecolorgit
Github ,若是你喜歡,歡迎star 謝謝github
原生的API對圖片的操做有限,而且一些顏色空間轉化麻煩,效率低,那咱們使用一個專業的圖片操做庫來操做圖片,會變得容易些.算法
OpenCv有不少語言版本,固然底層是c/c++,他支持Android/IOS,Windows,Mac等,咱們直接選擇Android版本. 那麼來搭建一下環境,有兩步網絡
集成完成後,進行OpenCV SDK接入成功測試app
private void initLoaderOpenCV() {
boolean success = OpenCVLoader.initDebug();
if (!success) {
Log.d(TAG, "初始化失敗");
}
}
public void gray(View view) {
Mat src = new Mat();
Mat dst = new Mat();
Utils.bitmapToMat(bitmap, src);
Imgproc.cvtColor(src, dst, Imgproc.COLOR_BGRA2GRAY);
Bitmap resultBitmap = getResultBitmap();
Utils.matToBitmap(dst, resultBitmap);
src.release();
dst.release();
showCompare(resultBitmap);
}
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若是接入沒問題,就能夠愉快的使用OpenCV了,是否是很簡單. ide
換證件照算法,直接使用了一個c++ 版本算法的,翻譯爲Android的. c++文章地址
主要步驟:
Android 代碼以下:
private void startDetail() {
Mat image = new Mat();
Utils.bitmapToMat(bitmap, image);
Mat hsvImg = new Mat();
Imgproc.cvtColor(image, hsvImg, Imgproc.COLOR_BGR2HSV);
List<Mat> list = new ArrayList<>();
Core.split(hsvImg, list);
Mat roiH = list.get(0).submat(new Rect(0, 0, 20, 20));
Mat roiS = list.get(1).submat(new Rect(0, 0, 20, 20));
Log.i(TAG,"start sum bg");
int SumH = 0;
int SumS = 0;
byte[] h = new byte[1];
byte[] s = new byte[1];
//取一塊藍色背景,計算出它的平均色調和平均飽和度
for (int i = 0; i < 20; i++) {
for (int j = 0; j < 20; j++) {
roiH.get(j, i, h);
roiS.get(j, i, s);
SumH = h[0] + SumH;
SumS = s[0] + SumS;
}
}
int avgH, avgS;//藍底的平均色調和平均飽和度
avgH = SumH / 400;
avgS = SumS / 400;
Log.i(TAG,"depth="+list.get(0).depth());
Log.i(TAG,"start sum detail all photo");
//遍歷整個圖像
int nl = hsvImg.height();
int nc = hsvImg.width();
// byte[] changeColor = new byte[]{127};
byte[] hArray = new byte[nl * nc];
byte[] sArray = new byte[nl * nc];
byte[] vArray = new byte[nl * nc];
list.get(0).get(0,0,hArray);
list.get(1).get(0,0,sArray);
// list.get(2).get(0,0,vArray);
int row,index;
for (int j = 0; j < nl; j++) {
row = j * nc;
for (int i = 0; i < nc; i++) {
index = row + i;
if(hArray[index] <= (avgH + 20) && hArray[index] >= (avgH - 20)
&& sArray[index] <= (avgS + 150)
&& sArray[index] >= (avgS -150)
){
hArray[index] = 127;
// sArray[index] = 0;
// vArray[index] = (byte) 255;
}
}
}
list.get(0).put(0,0,hArray);
list.get(1).put(0,0,sArray);
// list.get(2).put(0,0,vArray);
Log.i(TAG,"merge photo");
Core.merge(list,hsvImg);
Imgproc.cvtColor(hsvImg,image, Imgproc.COLOR_HSV2BGR);
Bitmap resultBitmap = getResultBitmap();
Utils.matToBitmap(image,resultBitmap);
Message obtain = Message.obtain();
obtain.obj = resultBitmap;
handler.sendMessage(obtain);
}
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Mat 爲OpenCV中圖像的保存,很相似Android裏的Bitmap,他和Bitmap轉化須要藉助OpenCv的Utils進行,OpenCV的核心API能夠查看官網,此處主要使用了Imgproc
先來講一下污點修復的算法,一篇論文提到的 《An ImageInpainting Technique Based On the Fast Marching Method》
能夠簡單理解爲p點爲待修復區域,ε爲修復半徑,把ε的值區域的值計算出來,用於修復P點,直到修復整個Ω區域.
詳細能夠查看論文:論文地址
OpenCV 裏面已經實現了此算法,具體方法以下:
//OpenCV Photo.java
/** * Restores the selected region in an image using the region neighborhood. * * @param src Input 8-bit, 16-bit unsigned or 32-bit float 1-channel or 8-bit 3-channel image. * @param inpaintMask Inpainting mask, 8-bit 1-channel image. Non-zero pixels indicate the area that * needs to be inpainted. * @param dst Output image with the same size and type as src . * @param inpaintRadius Radius of a circular neighborhood of each point inpainted that is considered * by the algorithm. * @param flags Inpainting method that could be cv::INPAINT_NS or cv::INPAINT_TELEA * * The function reconstructs the selected image area from the pixel near the area boundary. The * function may be used to remove dust and scratches from a scanned photo, or to remove undesirable * objects from still images or video. See <http://en.wikipedia.org/wiki/Inpainting> for more details. * * <b>Note:</b> * <ul> * <li> * An example using the inpainting technique can be found at * opencv_source_code/samples/cpp/inpaint.cpp * </li> * <li> * (Python) An example using the inpainting technique can be found at * opencv_source_code/samples/python/inpaint.py * </li> * </ul> */
public static void inpaint(Mat src, Mat inpaintMask, Mat dst, double inpaintRadius, int flags) {
inpaint_0(src.nativeObj, inpaintMask.nativeObj, dst.nativeObj, inpaintRadius, flags);
}
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其中上面提到的原理算法爲,INPAINT_TELEA.
來一張實際的圖操做修復一下,以下:
private void startInpaint() {
bitmap = BitmapUtils.getBitmapByAssetsNameRGB(this,"test.png");
Mat desc = new Mat(bitmap.getHeight(),bitmap.getWidth(),CvType.CV_8UC3);
//轉化爲mat對象
Utils.bitmapToMat(bitmap, desc,true);
//轉化爲3通道圖像
Mat src = new Mat();
Imgproc.cvtColor(desc,src,Imgproc.COLOR_RGBA2RGB);
//灰度圖像
Mat srcGray = new Mat();
Imgproc.cvtColor(src, srcGray, Imgproc.COLOR_RGB2GRAY);
//中值濾波去燥
Imgproc.medianBlur(srcGray,srcGray,3);
//獲取污點的二值化圖像
Mat srcThresh = new Mat();
Imgproc.threshold(srcGray,srcThresh,242,255,Imgproc.THRESH_BINARY);
Log.i("test","srcThresh channels:"+srcThresh.channels() + ",type:"+ CvType.typeToString(CvType.depth(srcThresh.type())));
Log.i("test","src channels:"+src.channels() + ",type:"+ CvType.typeToString(CvType.depth(src.type())));
// Bitmap resultBitmap = getResultBitmap();
// Utils.matToBitmap(srcThresh, resultBitmap);
//修復圖像
Mat inpaintResult = new Mat();
Photo.inpaint(src,srcThresh,inpaintResult,3,Photo.INPAINT_TELEA);
//把結果轉化爲bitmap 用於顯示
Bitmap resultBitmap = getResultBitmap();
Utils.matToBitmap(inpaintResult, resultBitmap);
Message obtain = Message.obtain();
obtain.obj = resultBitmap;
handler.sendMessage(obtain);
}
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圖片來源:www.cnblogs.com/hellowooorl…
本篇文章,主要介紹了OpenCV怎麼快速使用,並結合了兩個實際的例子,來進一步說明藉助OpenCV裏的API,能夠實現不少不錯的效果.
文中圖片來源網絡,若又侵權,請聯繫做者,馬上刪除!
本篇文章的兩個例子代碼地址:github ,若是你喜歡迎star,後續關於圖片的操做,都會在此庫裏更新.
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