Android-YUV图像转换算法和检测工具
作者:互联网
1. 格式说明
在安卓开发的一些场景,比如操作相机输出、视频编解码中会用到YUV图像格式。YUV中最常用的是YUV420格式,YUV420就是每4个Y分量共用一个U分量和一个V分量。
YUV420分为4种:
- I420: YYYYYYYY UU VV
- YV12:YYYYYYYY VV UU
- NV12:YYYYYYYY UVUV
- NV21:YYYYYYYY VUVU
I420和YV12属于YUV420P,也就是U和V分开放置,不同的是I420是先放U,YV12是先放V;
NV12和NV21属于YUV420SP,也就是U和V交替放置,不同的是NV12是UV交替,NV21是VU交替。
这4种格式和名称是我总结了国内外很多篇资料得出来的,并且经过了算法检验,应该比较准确。国内部分资料可能有描述错误。
由于YUV420命名和格式有些乱(包括官方资料),对于新手来说,在做图像处理时,很容易弄错,导致输出的图像错乱。
我决定做一个能识别YUV420图像格式的工具。
当未知格式(是YUV420,但具体格式不确定)的图像数据输入时,它同时以I420、YV12、NV12和NV21这4种格式去解析图像,并实时显示。其中只有一种是显示正确的,另外三种都会有颜色异常。
此外再加上方向旋转(上图中的Rotate)和宽高交换(上图中的Flip)功能。
2. 数据来源
数据来源于安卓相机,分为Camera1和Camera2。Camera1是旧的API,标记为Deprecated,功能较简单,官方推荐用Camera2 API。Camera2功能更强大,使用起来也复杂一点。
它们的使用方法可参考官方Demo:
- Camera1官方Demo镜像
https://github.com/appium/android-apidemos/blob/master/app/src/main/java/io/appium/android/apis/graphics/CameraPreview.java - Camera2官方Demo
https://github.com/googlesamples/android-Camera2Basic
Camera1获取输出的图像数据方法如下:
// 1. 创建Camera.Parameters并设置预览图像格式
Camera.Parameters parameters = mCamera.getParameters();
parameters.setPreviewSize(mPreviewSize.width, mPreviewSize.height);
parameters.setPreviewFormat(ImageFormat.YV12);
requestLayout();
mCamera.setParameters(parameters);
// 2. 设置预览图像回调
mCamera = Camera.open();
mCamera.setPreviewCallback(this);
// 3. 处理回调图像的byte[]数据
@Override
public void onPreviewFrame(byte[] data, Camera camera) {
...
}
Camera2获取输出的图像数据方法如下:
// 1. 创建ImageReader并设置图像格式
mImageReader = ImageReader.newInstance(640, 480,
ImageFormat.YUV_420_888, /*maxImages*/2);
mImageReader.setOnImageAvailableListener(
mOnImageAvailableListener, mBackgroundHandler);
// 2. 从ImageReader中取得getSurface()并传给mCameraDevice
mPreviewRequestBuilder.addTarget(mImageReader.getSurface());
// Here, we create a CameraCaptureSession for camera preview.
mCameraDevice.createCaptureSession(Arrays.asList(surface, mImageReader.getSurface()),
new CameraCaptureSession.StateCallback() {
// 3. 在ImageReader的OnImageAvailableListener回调中获取Image数据
private final ImageReader.OnImageAvailableListener mOnImageAvailableListener
= new ImageReader.OnImageAvailableListener() {
@Override
public void onImageAvailable(ImageReader reader) {
handleImage(reader);
}
};
3. 格式转换算法
为了简单起见,我的工具中使用4个ImageView来展示图像。不用担心图像是静止的,由于不停刷新,图像是实时运动的。原始图像需要转成Bitmap才能在ImageView中显示。
YUV420转Bitmap算法:
public static Bitmap nv12ToBitmap(byte[] data, int w, int h) {
return spToBitmap(data, w, h, 0, 1);
}
public static Bitmap nv21ToBitmap(byte[] data, int w, int h) {
return spToBitmap(data, w, h, 1, 0);
}
private static Bitmap spToBitmap(byte[] data, int w, int h, int uOff, int vOff) {
int plane = w * h;
int[] colors = new int[plane];
int yPos = 0, uvPos = plane;
for(int j = 0; j < h; j++) {
for(int i = 0; i < w; i++) {
// YUV byte to RGB int
final int y1 = data[yPos] & 0xff;
final int u = (data[uvPos + uOff] & 0xff) - 128;
final int v = (data[uvPos + vOff] & 0xff) - 128;
final int y1192 = 1192 * y1;
int r = (y1192 + 1634 * v);
int g = (y1192 - 833 * v - 400 * u);
int b = (y1192 + 2066 * u);
r = (r < 0) ? 0 : ((r > 262143) ? 262143 : r);
g = (g < 0) ? 0 : ((g > 262143) ? 262143 : g);
b = (b < 0) ? 0 : ((b > 262143) ? 262143 : b);
colors[yPos] = ((r << 6) & 0xff0000) |
((g >> 2) & 0xff00) |
((b >> 10) & 0xff);
if((yPos++ & 1) == 1) uvPos += 2;
}
if((j & 1) == 0) uvPos -= w;
}
return Bitmap.createBitmap(colors, w, h, Bitmap.Config.RGB_565);
}
public static Bitmap i420ToBitmap(byte[] data, int w, int h) {
return pToBitmap(data, w, h, true);
}
public static Bitmap yv12ToBitmap(byte[] data, int w, int h) {
return pToBitmap(data, w, h, false);
}
private static Bitmap pToBitmap(byte[] data, int w, int h, boolean uv) {
int plane = w * h;
int[] colors = new int[plane];
int off = plane >> 2;
int yPos = 0, uPos = plane + (uv ? 0 : off), vPos = plane + (uv ? off : 0);
for(int j = 0; j < h; j++) {
for(int i = 0; i < w; i++) {
// YUV byte to RGB int
final int y1 = data[yPos] & 0xff;
final int u = (data[uPos] & 0xff) - 128;
final int v = (data[vPos] & 0xff) - 128;
final int y1192 = 1192 * y1;
int r = (y1192 + 1634 * v);
int g = (y1192 - 833 * v - 400 * u);
int b = (y1192 + 2066 * u);
r = (r < 0) ? 0 : ((r > 262143) ? 262143 : r);
g = (g < 0) ? 0 : ((g > 262143) ? 262143 : g);
b = (b < 0) ? 0 : ((b > 262143) ? 262143 : b);
colors[yPos] = ((r << 6) & 0xff0000) |
((g >> 2) & 0xff00) |
((b >> 10) & 0xff);
if((yPos++ & 1) == 1) {
uPos++;
vPos++;
}
}
if((j & 1) == 0) {
uPos -= (w >> 1);
vPos -= (w >> 1);
}
}
return Bitmap.createBitmap(colors, w, h, Bitmap.Config.RGB_565);
}
这是第一种方法,是Intel提供的。https://software.intel.com/en-us/android/articles/trusted-tools-in-the-new-android-world-optimization-techniques-from-intel-sse-intrinsics-to
另一种YUV420转Bitmap算法:
public static Bitmap nv21ToBitmap(byte[] data, int w, int h) {
final YuvImage image = new YuvImage(data, ImageFormat.NV21, w, h, null);
ByteArrayOutputStream os = new ByteArrayOutputStream(data.length);
if (image.compressToJpeg(new Rect(0, 0, w, h), 100, os)) {
byte[] tmp = os.toByteArray();
return BitmapFactory.decodeByteArray(tmp, 0, tmp.length);
}
return null;
}
这种方法是利用安卓提供的YuvImage类将NV21格式转换成Bitmap。虽然这是官方的,但是转换效率比较低,比第一种方法慢一倍,而且只支持NV21格式,所以不推荐使用。
Camera2的图像数据回调中提供的是ImageReader,需要从ImageReader中获取Image.Plane[],再转换成byte[]数据。方法如下:
/**
* 从ImageReader中获取byte[]数据
*/
public static byte[] getBytesFromImageReader(ImageReader imageReader) {
try (Image image = imageReader.acquireNextImage()) {
final Image.Plane[] planes = image.getPlanes();
int len = 0;
for (Image.Plane plane : planes) {
len += plane.getBuffer().remaining();
}
byte[] bytes = new byte[len];
int off = 0;
for (Image.Plane plane : planes) {
ByteBuffer buffer = plane.getBuffer();
int remain = buffer.remaining();
buffer.get(bytes, off, remain);
off += remain;
}
return bytes;
} catch (Exception e) {
e.printStackTrace();
}
return null;
}
4. 旋转算法
// NV21或NV12顺时针旋转90度
public static void rotateSP90(byte[] src, byte[] dest, int w, int h) {
int pos = 0;
int k = 0;
for (int i = 0; i <= w - 1; i++) {
for (int j = h - 1; j >= 0; j--) {
dest[k++] = src[j * w + i];
}
}
pos = w * h;
for (int i = 0; i <= w - 2; i += 2) {
for (int j = h / 2 - 1; j >= 0; j--) {
dest[k++] = src[pos + j * w + i];
dest[k++] = src[pos + j * w + i + 1];
}
}
}
// NV21或NV12顺时针旋转270度
public static void rotateSP270(byte[] src, byte[] dest, int w, int h) {
int pos = 0;
int k = 0;
for (int i = w - 1; i >= 0; i--) {
for (int j = 0; j <= h - 1; j++) {
dest[k++] = src[j * w + i];
}
}
pos = w * h;
for (int i = w - 2; i >= 0; i -= 2) {
for (int j = 0; j <= h / 2 - 1; j++) {
dest[k++] = src[pos + j * w + i];
dest[k++] = src[pos + j * w + i + 1];
}
}
}
// NV21或NV12顺时针旋转180度
public static void rotateSP180(byte[] src, byte[] dest, int w, int h) {
int pos = 0;
int k = w * h - 1;
while (k >= 0) {
dest[pos++] = src[k--];
}
k = src.length - 2;
while (pos < dest.length) {
dest[pos++] = src[k];
dest[pos++] = src[k + 1];
k -= 2;
}
}
// I420或YV12顺时针旋转90度
public static void rotateP90(byte[] src, byte[] dest, int w, int h) {
int pos = 0;
//旋转Y
int k = 0;
for (int i = 0; i < w; i++) {
for (int j = h - 1; j >= 0; j--) {
dest[k++] = src[j * w + i];
}
}
//旋转U
pos = w * h;
for (int i = 0; i < w / 2; i++) {
for (int j = h / 2 - 1; j >= 0; j--) {
dest[k++] = src[pos + j * w / 2 + i];
}
}
//旋转V
pos = w * h * 5 / 4;
for (int i = 0; i < w / 2; i++) {
for (int j = h / 2 - 1; j >= 0; j--) {
dest[k++] = src[pos + j * w / 2 + i];
}
}
}
// I420或YV12顺时针旋转270度
public static void rotateP270(byte[] src, byte[] dest, int w, int h) {
int pos = 0;
//旋转Y
int k = 0;
for (int i = w - 1; i >= 0; i--) {
for (int j = 0; j < h; j++) {
dest[k++] = src[j * w + i];
}
}
//旋转U
pos = w * h;
for (int i = w / 2 - 1; i >= 0; i--) {
for (int j = 0; j < h / 2; j++) {
dest[k++] = src[pos + j * w / 2 + i];
}
}
//旋转V
pos = w * h * 5 / 4;
for (int i = w / 2 - 1; i >= 0; i--) {
for (int j = 0; j < h / 2; j++) {
dest[k++] = src[pos + j * w / 2 + i];
}
}
}
// I420或YV12顺时针旋转180度
public static void rotateP180(byte[] src, byte[] dest, int w, int h) {
int pos = 0;
int k = w * h - 1;
while (k >= 0) {
dest[pos++] = src[k--];
}
k = w * h * 5 / 4;
while (k >= w * h) {
dest[pos++] = src[k--];
}
k = src.length - 1;
while (pos < dest.length) {
dest[pos++] = src[k--];
}
}
注意,如果旋转角度是90或270度,那么旋转后图像宽高就交换了。
5. 检测工具
有了数据来源和算法,封装一个检测工具用来展示就简单了。检测工具YUVDetectView继承自FrameLayout,里面放4个ImageView。
public class YUVDetectView extends FrameLayout {
ImageView[] ivs;
CheckBox cb;
boolean isFlip = false;
boolean isShowing = false;
int rotation = 0;
public YUVDetectView(@NonNull Context context) {
this(context, null);
}
public YUVDetectView(@NonNull Context context, @Nullable AttributeSet attrs) {
this(context, attrs, 0);
}
public YUVDetectView(@NonNull Context context, @Nullable AttributeSet attrs, int defStyleAttr) {
super(context, attrs, defStyleAttr);
inflate(context, R.layout.view_yuv_detect, this);
ivs = new ImageView[]{
findViewById(R.id.iv1), // I420
findViewById(R.id.iv2), // YV12
findViewById(R.id.iv3), // NV12
findViewById(R.id.iv4), // NV21
};
cb = findViewById(R.id.cb);
cb.setOnCheckedChangeListener(new CompoundButton.OnCheckedChangeListener() {
@Override
public void onCheckedChanged(CompoundButton buttonView, boolean isChecked) {
isFlip = isChecked;
}
});
View btn = findViewById(R.id.btn);
btn.setOnClickListener(new OnClickListener() {
@Override
public void onClick(View v) {
rotation = (rotation + 90) % 360;
}
});
}
public void input(final ImageReader imageReader) {
final int w = isFlip ? imageReader.getHeight() : imageReader.getWidth();
final int h = isFlip ? imageReader.getWidth() : imageReader.getHeight();
final byte[] bytes = YUVTools.getBytesFromImageReader(imageReader);
if(bytes != null) {
displayImage(bytes, w, h);
}
}
public void inputAsync(final byte[] data, int width, int height) {
final int w = isFlip ? height : width;
final int h = isFlip ? width : height;
if (isShowing) return;
isShowing = true;
new Thread() {
@Override
public void run() {
displayImage(data, w, h);
isShowing = false;
}
}.start();
}
private void displayImage(byte[] data, int w, int h) {
long time = System.currentTimeMillis();
byte[] rotated = rotation == 0 ? data : new byte[data.length];
int rw = rotation % 180 == 0 ? w : h, rh = rotation % 180 == 0 ? h : w; // rotated
YUVTools.rotateP(data, rotated, w, h, rotation);
final Bitmap b0 = YUVTools.i420ToBitmap(rotated, rw, rh);
YUVTools.rotateP(data, rotated, w, h, rotation);
final Bitmap b1 = YUVTools.yv12ToBitmap(rotated, rw, rh);
YUVTools.rotateSP(data, rotated, w, h, rotation);
final Bitmap b2 = YUVTools.nv12ToBitmap(rotated, rw, rh);
YUVTools.rotateSP(data, rotated, w, h, rotation);
final Bitmap b3 = YUVTools.nv21ToBitmap(rotated, rw, rh);
time = System.currentTimeMillis() - time;
Log.d("YUVDetectView", "convert time: " + time);
post(new Runnable() {
@Override
public void run() {
if (b0 != null) ivs[0].setImageBitmap(b0);
if (b1 != null) ivs[1].setImageBitmap(b1);
if (b2 != null) ivs[2].setImageBitmap(b2);
if (b3 != null) ivs[3].setImageBitmap(b3);
}
});
}d
}
Github地址
https://github.com/rome753/android-YuvTools
标签:int,public,pos,YUV,++,Android,data,byte,检测工具 来源: https://www.cnblogs.com/rome753/p/16491470.html