标签：android-camera2 android portrait rotation front-camera
注意：我的帖子中的所有信息仅适用于Samsung Galaxy S7设备.我不知道模拟器和其他设备的行为方式.
在onImageAvailable中,我将每个图像连续转换为NV21字节数组,并将其转发到期望原始NV21格式的API.
这是我初始化图像阅读器和接收图像的方法：
private void openCamera() {
...
mImageReader = ImageReader.newInstance(WIDTH, HEIGHT,
ImageFormat.YUV_420_888, 1); // only 1 for best performance
mImageReader.setOnImageAvailableListener(
mOnImageAvailableListener, mBackgroundHandler);
...
}
private final ImageReader.OnImageAvailableListener mOnImageAvailableListener
= new ImageReader.OnImageAvailableListener() {
@Override
public void onImageAvailable(ImageReader reader) {
Image image = reader.acquireLatestImage();
if (image != null) {
byte[] data = convertYUV420ToNV21_ALL_PLANES(image); // this image is turned 90 deg using front cam in portrait mode
byte[] data_rotated = rotateNV21_working(data, WIDTH, HEIGHT, 270);
ForwardToAPI(data_rotated); // image data is being forwarded to api and received later on
image.close();
}
}
};
将图像转换为原始NV21(from here)的功能,工作正常,在纵向模式下使用前凸轮时,图像(由于android？)转动90度：
(根据Alex Cohn的评论,我对其进行了修改)
private byte[] convertYUV420ToNV21_ALL_PLANES(Image imgYUV420) {
byte[] rez;
ByteBuffer buffer0 = imgYUV420.getPlanes()[0].getBuffer();
ByteBuffer buffer1 = imgYUV420.getPlanes()[1].getBuffer();
ByteBuffer buffer2 = imgYUV420.getPlanes()[2].getBuffer();
// actually here should be something like each second byte
// however I simply get the last byte of buffer 2 and the entire buffer 1
int buffer0_size = buffer0.remaining();
int buffer1_size = buffer1.remaining(); // / 2 + 1;
int buffer2_size = 1;//buffer2.remaining(); // / 2 + 1;
byte[] buffer0_byte = new byte[buffer0_size];
byte[] buffer1_byte = new byte[buffer1_size];
byte[] buffer2_byte = new byte[buffer2_size];
buffer0.get(buffer0_byte, 0, buffer0_size);
buffer1.get(buffer1_byte, 0, buffer1_size);
buffer2.get(buffer2_byte, buffer2_size-1, buffer2_size);
ByteArrayOutputStream outputStream = new ByteArrayOutputStream();
try {
// swap 1 and 2 as blue and red colors are swapped
outputStream.write(buffer0_byte);
outputStream.write(buffer2_byte);
outputStream.write(buffer1_byte);
} catch (IOException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
rez = outputStream.toByteArray();
return rez;
}
因此需要轮换“数据”.使用此功能(from here),我得到一个奇怪的3次隔行扫描图片错误：
public static byte[] rotateNV21(byte[] input, int width, int height, int rotation) {
byte[] output = new byte[input.length];
boolean swap = (rotation == 90 || rotation == 270);
// **EDIT:** in portrait mode & front cam this needs to be set to true:
boolean yflip = true;// (rotation == 90 || rotation == 180);
boolean xflip = (rotation == 270 || rotation == 180);
for (int x = 0; x < width; x++) {
for (int y = 0; y < height; y++) {
int xo = x, yo = y;
int w = width, h = height;
int xi = xo, yi = yo;
if (swap) {
xi = w * yo / h;
yi = h * xo / w;
}
if (yflip) {
yi = h - yi - 1;
}
if (xflip) {
xi = w - xi - 1;
}
output[w * yo + xo] = input[w * yi + xi];
int fs = w * h;
int qs = (fs >> 2);
xi = (xi >> 1);
yi = (yi >> 1);
xo = (xo >> 1);
yo = (yo >> 1);
w = (w >> 1);
h = (h >> 1);
// adjust for interleave here
int ui = fs + (w * yi + xi) * 2;
int uo = fs + (w * yo + xo) * 2;
// and here
int vi = ui + 1;
int vo = uo + 1;
output[uo] = input[ui];
output[vo] = input[vi];
}
}
return output;
}
导致这张图片：
注意：它仍然是相同的杯子,但你看到它3-4次.
使用另一个建议的旋转功能from here给出了正确的结果：
public static byte[] rotateNV21_working(final byte[] yuv,
final int width,
final int height,
final int rotation)
{
if (rotation == 0) return yuv;
if (rotation % 90 != 0 || rotation < 0 || rotation > 270) {
throw new IllegalArgumentException("0 <= rotation < 360, rotation % 90 == 0");
}
final byte[] output = new byte[yuv.length];
final int frameSize = width * height;
final boolean swap = rotation % 180 != 0;
final boolean xflip = rotation % 270 != 0;
final boolean yflip = rotation >= 180;
for (int j = 0; j < height; j++) {
for (int i = 0; i < width; i++) {
final int yIn = j * width + i;
final int uIn = frameSize + (j >> 1) * width + (i & ~1);
final int vIn = uIn + 1;
final int wOut = swap ? height : width;
final int hOut = swap ? width : height;
final int iSwapped = swap ? j : i;
final int jSwapped = swap ? i : j;
final int iOut = xflip ? wOut - iSwapped - 1 : iSwapped;
final int jOut = yflip ? hOut - jSwapped - 1 : jSwapped;
final int yOut = jOut * wOut + iOut;
final int uOut = frameSize + (jOut >> 1) * wOut + (iOut & ~1);
final int vOut = uOut + 1;
output[yOut] = (byte)(0xff & yuv[yIn]);
output[uOut] = (byte)(0xff & yuv[uIn]);
output[vOut] = (byte)(0xff & yuv[vIn]);
}
}
return output;
}
现在结果很好：
顶部图像使用纹理视图的表面显示直接流并将其添加到captureRequestBuilder.底部图像显示旋转后的原始图像数据.
问题是：
>这对“convertYUV420ToNV21_ALL_PLANES”的攻击是否有效
设备/模拟器？
>为什么rotateNV21不起作用,而rotateNV21_working工作正常.
编辑：镜像问题已修复,请参阅代码注释.挤压问题是固定的,它是由它转发的API引起的.
实际的开放问题是一个适当的不太昂贵的功能,将图像转换并旋转到在任何设备上工作的原始NV21.
解决方法:
所以,这是将Image转换为NV21 byte []的正确代码.这将工作我们imgYUV420 U和V平面有pixelStride = 1(如在模拟器上)或pixelStride = 1(如在Nexus上)：
private byte[] convertYUV420ToNV21_ALL_PLANES(Image imgYUV420) {
assert(imgYUV420.getFormat() == ImageFormat.YUV_420_888);
Log.d(TAG, "image: " + imgYUV420.getWidth() + "x" + imgYUV420.getHeight() + " " + imgYUV420.getFormat());
Log.d(TAG, "planes: " + imgYUV420.getPlanes().length);
for (int nplane = 0; nplane < imgYUV420.getPlanes().length; nplane++) {
Log.d(TAG, "plane[" + nplane + "]: length " + imgYUV420.getPlanes()[nplane].getBuffer().remaining() + ", strides: " + imgYUV420.getPlanes()[nplane].getPixelStride() + " " + imgYUV420.getPlanes()[nplane].getRowStride());
}
byte[] rez = new byte[imgYUV420.getWidth() * imgYUV420.getHeight() * 3 / 2];
ByteBuffer buffer0 = imgYUV420.getPlanes()[0].getBuffer();
ByteBuffer buffer1 = imgYUV420.getPlanes()[1].getBuffer();
ByteBuffer buffer2 = imgYUV420.getPlanes()[2].getBuffer();
int n = 0;
assert(imgYUV420.getPlanes()[0].getPixelStride() == 1);
for (int row = 0; row < imgYUV420.getHeight(); row++) {
for (int col = 0; col < imgYUV420.getWidth(); col++) {
rez[n++] = buffer0.get();
}
}
assert(imgYUV420.getPlanes()[2].getPixelStride() == imgYUV420.getPlanes()[1].getPixelStride());
int stride = imgYUV420.getPlanes()[1].getPixelStride();
for (int row = 0; row < imgYUV420.getHeight(); row += 2) {
for (int col = 0; col < imgYUV420.getWidth(); col += 2) {
rez[n++] = buffer1.get();
rez[n++] = buffer2.get();
for (int skip = 1; skip < stride; skip++) {
if (buffer1.remaining() > 0) {
buffer1.get();
}
if (buffer2.remaining() > 0) {
buffer2.get();
}
}
}
}
Log.w(TAG, "total: " + rez.length);
return rez;
}
如您所见,可以非常轻松地更改此代码,从而在一个步骤中生成旋转图像：
private byte[] rotateYUV420ToNV21(Image imgYUV420) {
Log.d(TAG, "image: " + imgYUV420.getWidth() + "x" + imgYUV420.getHeight() + " " + imgYUV420.getFormat());
Log.d(TAG, "planes: " + imgYUV420.getPlanes().length);
for (int nplane = 0; nplane < imgYUV420.getPlanes().length; nplane++) {
Log.d(TAG, "plane[" + nplane + "]: length " + imgYUV420.getPlanes()[nplane].getBuffer().remaining() + ", strides: " + imgYUV420.getPlanes()[nplane].getPixelStride() + " " + imgYUV420.getPlanes()[nplane].getRowStride());
}
byte[] rez = new byte[imgYUV420.getWidth() * imgYUV420.getHeight() * 3 / 2];
ByteBuffer buffer0 = imgYUV420.getPlanes()[0].getBuffer();
ByteBuffer buffer1 = imgYUV420.getPlanes()[1].getBuffer();
ByteBuffer buffer2 = imgYUV420.getPlanes()[2].getBuffer();
int width = imgYUV420.getHeight();
assert(imgYUV420.getPlanes()[0].getPixelStride() == 1);
for (int row = imgYUV420.getHeight()-1; row >=0; row--) {
for (int col = 0; col < imgYUV420.getWidth(); col++) {
rez[col*width+row] = buffer0.get();
}
}
int uv_offset = imgYUV420.getWidth()*imgYUV420.getHeight();
assert(imgYUV420.getPlanes()[2].getPixelStride() == imgYUV420.getPlanes()[1].getPixelStride());
int stride = imgYUV420.getPlanes()[1].getPixelStride();
for (int row = imgYUV420.getHeight() - 2; row >= 0; row -= 2) {
for (int col = 0; col < imgYUV420.getWidth(); col += 2) {
rez[uv_offset+col/2*width+row] = buffer1.get();
rez[uv_offset+col/2*width+row+1] = buffer2.get();
for (int skip = 1; skip < stride; skip++) {
if (buffer1.remaining() > 0) {
buffer1.get();
}
if (buffer2.remaining() > 0) {
buffer2.get();
}
}
}
}
Log.w(TAG, "total rotated: " + rez.length);
return rez;
}
我真诚地推荐网站http://rawpixels.net/来查看原始图像的实际结构.
标签：android-camera2,android,portrait,rotation,front-camera 来源： https://codeday.me/bug/20190930/1837221.html
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