使用视觉api在脸上拍摄可绘画/油漆
我在尝试什么？
我试图在脸上画上可绘画/油漆，但是我无法在同一张照片上拍摄。
我尝试了什么？
我尝试使用CameraSource.takePicture，但我只是脸上没有任何可绘画/油漆。
mCameraSource.takePicture(shutterCallback, new CameraSource.PictureCallback() {
@Override
public void onPictureTaken(byte[] bytes) {
try {
String mainpath = getExternalStorageDirectory() + separator + "TestXyz" + separator + "images" + separator;
File basePath = new File(mainpath);
if (!basePath.exists())
Log.d("CAPTURE_BASE_PATH", basePath.mkdirs() ? "Success": "Failed");
String path = mainpath + "photo_" + getPhotoTime() + ".jpg";
File captureFile = new File(path);
captureFile.createNewFile();
if (!captureFile.exists())
Log.d("CAPTURE_FILE_PATH", captureFile.createNewFile() ? "Success": "Failed");
FileOutputStream stream = new FileOutputStream(captureFile);
stream.write(bytes);
stream.flush();
stream.close();
} catch (IOException e) {
e.printStackTrace();
}
}
});
我也尝试过使用：
mPreview.setDrawingCacheEnabled(true);
Bitmap drawingCache = mPreview.getDrawingCache();
try {
String mainpath = getExternalStorageDirectory() + separator + "TestXyz" + separator + "images" + separator;
File basePath = new File(mainpath);
if (!basePath.exists())
Log.d("CAPTURE_BASE_PATH", basePath.mkdirs() ? "Success": "Failed");
String path = mainpath + "photo_" + getPhotoTime() + ".jpg";
File captureFile = new File(path);
captureFile.createNewFile();
if (!captureFile.exists())
Log.d("CAPTURE_FILE_PATH", captureFile.createNewFile() ? "Success": "Failed");
FileOutputStream stream = new FileOutputStream(captureFile);
drawingCache.compress(Bitmap.CompressFormat.PNG, 100, stream);
stream.flush();
stream.close();
} catch (IOException e) {
e.printStackTrace();
}
在这种情况下，我只能得到我在脸上画的东西。这里，mPreview是CameraSourcePreview。
刚刚添加了捕获按钮，并在this google示例中添加了上述代码。
3 个答案:
答案 0 :(得分：11)
你非常接近你所需要的东西：）
你有：
- 脸部相机的图像（第一个代码段）
- 来自眼睛画布的图像叠加（第二个代码段）
- 将眼睛覆盖在脸上的图像 - 合并的图像。
你需要什么：
如何合并？
要合并2个图像，只需使用画布，如下所示：
public Bitmap mergeBitmaps(Bitmap face, Bitmap overlay) {
// Create a new image with target size
int width = face.getWidth();
int height = face.getHeight();
Bitmap newBitmap = Bitmap.createBitmap(width, height, Bitmap.Config.ARGB_8888);
Rect faceRect = new Rect(0,0,width,height);
Rect overlayRect = new Rect(0,0,overlay.getWidth(),overlay.getHeight());
// Draw face and then overlay (Make sure rects are as needed)
Canvas canvas = new Canvas(newBitmap);
canvas.drawBitmap(face, faceRect, faceRect, null);
canvas.drawBitmap(overlay, overlayRect, faceRect, null);
return newBitmap
}
然后你可以像现在一样保存新图像。
完整代码如下所示：
mCameraSource.takePicture(shutterCallback, new
CameraSource.PictureCallback() {
@Override
public void onPictureTaken(byte[] bytes) {
// Generate the Face Bitmap
BitmapFactory.Options options = new BitmapFactory.Options();
Bitmap face = BitmapFactory.decodeByteArray(bytes, 0, bytes.length, options);
// Generate the Eyes Overlay Bitmap
mPreview.setDrawingCacheEnabled(true);
Bitmap overlay = mPreview.getDrawingCache();
// Generate the final merged image
Bitmap result = mergeBitmaps(face, overlay);
// Save result image to file
try {
String mainpath = getExternalStorageDirectory() + separator + "TestXyz" + separator + "images" + separator;
File basePath = new File(mainpath);
if (!basePath.exists())
Log.d("CAPTURE_BASE_PATH", basePath.mkdirs() ? "Success": "Failed");
String path = mainpath + "photo_" + getPhotoTime() + ".jpg";
File captureFile = new File(path);
captureFile.createNewFile();
if (!captureFile.exists())
Log.d("CAPTURE_FILE_PATH", captureFile.createNewFile() ? "Success": "Failed");
FileOutputStream stream = new FileOutputStream(captureFile);
result.compress(Bitmap.CompressFormat.PNG, 100, stream);
stream.flush();
stream.close();
} catch (IOException e) {
e.printStackTrace();
}
}
});
请注意，上面只是一个示例代码。 您应该将合并并保存到文件到后台线程。
答案 1 :(得分：5)
我可以通过以下解决方案捕获带有drawable / paint的图像：
private void captureImage() {
mPreview.setDrawingCacheEnabled(true);
Bitmap drawingCache = mPreview.getDrawingCache();
mCameraSource.takePicture(shutterCallback, new CameraSource.PictureCallback() {
@Override
public void onPictureTaken(byte[] bytes) {
int orientation = Exif.getOrientation(bytes);
Bitmap temp = BitmapFactory.decodeByteArray(bytes, 0, bytes.length);
Bitmap picture = rotateImage(temp,orientation);
Bitmap overlay = Bitmap.createBitmap(mGraphicOverlay.getWidth(),mGraphicOverlay.getHeight(),picture.getConfig());
Canvas canvas = new Canvas(overlay);
Matrix matrix = new Matrix();
matrix.setScale((float)overlay.getWidth()/(float)picture.getWidth(),(float)overlay.getHeight()/(float)picture.getHeight());
// mirror by inverting scale and translating
matrix.preScale(-1, 1);
matrix.postTranslate(canvas.getWidth(), 0);
Paint paint = new Paint();
canvas.drawBitmap(picture,matrix,paint);
canvas.drawBitmap(drawingCache,0,0,paint);
try {
String mainpath = getExternalStorageDirectory() + separator + "MaskIt" + separator + "images" + separator;
File basePath = new File(mainpath);
if (!basePath.exists())
Log.d("CAPTURE_BASE_PATH", basePath.mkdirs() ? "Success": "Failed");
String path = mainpath + "photo_" + getPhotoTime() + ".jpg";
File captureFile = new File(path);
captureFile.createNewFile();
if (!captureFile.exists())
Log.d("CAPTURE_FILE_PATH", captureFile.createNewFile() ? "Success": "Failed");
FileOutputStream stream = new FileOutputStream(captureFile);
overlay.compress(Bitmap.CompressFormat.PNG, 100, stream);
stream.flush();
stream.close();
picture.recycle();
drawingCache.recycle();
mPreview.setDrawingCacheEnabled(false);
} catch (IOException e) {
e.printStackTrace();
}
}
});
}
有时在某些设备上也会出现方向问题。为此，我使用了Exif类和rotateImage()函数。
Exif类（来自here的参考）：
public class Exif {
private static final String TAG = "CameraExif";
// Returns the degrees in clockwise. Values are 0, 90, 180, or 270.
public static int getOrientation(byte[] jpeg) {
if (jpeg == null) {
return 0;
}
int offset = 0;
int length = 0;
// ISO/IEC 10918-1:1993(E)
while (offset + 3 < jpeg.length && (jpeg[offset++] & 0xFF) == 0xFF) {
int marker = jpeg[offset] & 0xFF;
// Check if the marker is a padding.
if (marker == 0xFF) {
continue;
}
offset++;
// Check if the marker is SOI or TEM.
if (marker == 0xD8 || marker == 0x01) {
continue;
}
// Check if the marker is EOI or SOS.
if (marker == 0xD9 || marker == 0xDA) {
break;
}
// Get the length and check if it is reasonable.
length = pack(jpeg, offset, 2, false);
if (length < 2 || offset + length > jpeg.length) {
Log.e(TAG, "Invalid length");
return 0;
}
// Break if the marker is EXIF in APP1.
if (marker == 0xE1 && length >= 8 &&
pack(jpeg, offset + 2, 4, false) == 0x45786966 &&
pack(jpeg, offset + 6, 2, false) == 0) {
offset += 8;
length -= 8;
break;
}
// Skip other markers.
offset += length;
length = 0;
}
// JEITA CP-3451 Exif Version 2.2
if (length > 8) {
// Identify the byte order.
int tag = pack(jpeg, offset, 4, false);
if (tag != 0x49492A00 && tag != 0x4D4D002A) {
Log.e(TAG, "Invalid byte order");
return 0;
}
boolean littleEndian = (tag == 0x49492A00);
// Get the offset and check if it is reasonable.
int count = pack(jpeg, offset + 4, 4, littleEndian) + 2;
if (count < 10 || count > length) {
Log.e(TAG, "Invalid offset");
return 0;
}
offset += count;
length -= count;
// Get the count and go through all the elements.
count = pack(jpeg, offset - 2, 2, littleEndian);
while (count-- > 0 && length >= 12) {
// Get the tag and check if it is orientation.
tag = pack(jpeg, offset, 2, littleEndian);
if (tag == 0x0112) {
// We do not really care about type and count, do we?
int orientation = pack(jpeg, offset + 8, 2, littleEndian);
switch (orientation) {
case 1:
return 0;
case 3:
return 3;
case 6:
return 6;
case 8:
return 8;
}
Log.i(TAG, "Unsupported orientation");
return 0;
}
offset += 12;
length -= 12;
}
}
Log.i(TAG, "Orientation not found");
return 0;
}
private static int pack(byte[] bytes, int offset, int length,
boolean littleEndian) {
int step = 1;
if (littleEndian) {
offset += length - 1;
step = -1;
}
int value = 0;
while (length-- > 0) {
value = (value << 8) | (bytes[offset] & 0xFF);
offset += step;
}
return value;
}
}
rotateImage功能：
private Bitmap rotateImage(Bitmap bm, int i) {
Matrix matrix = new Matrix();
switch (i) {
case ExifInterface.ORIENTATION_NORMAL:
return bm;
case ExifInterface.ORIENTATION_FLIP_HORIZONTAL:
matrix.setScale(-1, 1);
break;
case ExifInterface.ORIENTATION_ROTATE_180:
matrix.setRotate(180);
break;
case ExifInterface.ORIENTATION_FLIP_VERTICAL:
matrix.setRotate(180);
matrix.postScale(-1, 1);
break;
case ExifInterface.ORIENTATION_TRANSPOSE:
matrix.setRotate(90);
matrix.postScale(-1, 1);
break;
case ExifInterface.ORIENTATION_ROTATE_90:
matrix.setRotate(90);
break;
case ExifInterface.ORIENTATION_TRANSVERSE:
matrix.setRotate(-90);
matrix.postScale(-1, 1);
break;
case ExifInterface.ORIENTATION_ROTATE_270:
matrix.setRotate(-90);
break;
default:
return bm;
}
try {
Bitmap bmRotated = Bitmap.createBitmap(bm, 0, 0, bm.getWidth(), bm.getHeight(), matrix, true);
bm.recycle();
return bmRotated;
} catch (OutOfMemoryError e) {
e.printStackTrace();
return null;
}
}
答案 2 :(得分：4)
您可以通过将其分成更小的步骤来达到您想要的效果。
- 拍照
- 将位图发送到Google Mobile Vision以检测＆＃34;地标＆＃34;在脸上和每只眼睛打开的可能性
- 画出适当的眼睛＆＃34;到你的形象
使用Google移动视觉的FaceDetector时，您将获得一个SparseArray的Face对象（可能包含多个面，或者可能为空）。因此，您需要处理这些案件。但是你可以循环遍历SparseArray并找到你想要玩的Face对象。
static Bitmap processFaces(Context context, Bitmap picture) {
// Create a "face detector" object, using the builder pattern
FaceDetector detector = new FaceDetector.Builder(context)
.setTrackingEnabled(false) // disable tracking to improve performance
.setClassificationType(FaceDetector.ALL_CLASSIFICATIONS)
.build();
// create a "Frame" object, again using a builder pattern (and passing in our picture)
Frame frame = new Frame.Builder().setBitmap(picture).build(); // build frame
// get a sparse array of face objects
SparseArray<Face> faces = detector.detect(frame); // detect the faces
// This example just deals with a single face for the sake of simplicity,
// but you can change this to deal with multiple faces.
if (faces.size() != 1) return picture;
// make a mutable copy of the background image that we can modify
Bitmap bmOverlay = Bitmap.createBitmap(picture.getWidth(), picture.getHeight(), picture.getConfig());
Canvas canvas = new Canvas(bmOverlay);
canvas.drawBitmap(picture, 0, 0, null);
// get the Face object that we want to manipulate, and process it
Face face = faces.valueAt(0);
processFace(face, canvas);
detector.release();
return bmOverlay;
}
一旦你有了Face对象，就可以找到你感兴趣的功能
private static void processFace(Face face, Canvas canvas) {
// The Face object can tell you the probability that each eye is open.
// I'm comparing this probability to an arbitrary threshold of 0.6 here,
// but you can vary it between 0 and 1 as you please.
boolean leftEyeClosed = face.getIsLeftEyeOpenProbability() < .6;
boolean rightEyeClosed = face.getIsRightEyeOpenProbability() < .6;
// Loop through the face's "landmarks" (eyes, nose, etc) to find the eyes.
// landmark.getPosition() gives you the (x,y) coordinates of each feature.
for (Landmark landmark : face.getLandmarks()) {
if (landmark.getType() == Landmark.LEFT_EYE)
overlayEyeBitmap(canvas, leftEyeClosed, landmark.getPosition().x, landmark.getPosition().y);
if (landmark.getType() == Landmark.RIGHT_EYE)
overlayEyeBitmap(canvas, rightEyeClosed, landmark.getPosition().x, landmark.getPosition().y);
}
}
然后你可以添加你的油漆！
private static void overlayEyeBitmap(Canvas canvas, boolean eyeClosed, float cx, float cy) {
float radius = 40;
// draw the eye's background circle with appropriate color
Paint paintFill = new Paint();
paintFill.setStyle(Paint.Style.FILL);
if (eyeClosed)
paintFill.setColor(Color.YELLOW);
else
paintFill.setColor(Color.WHITE);
canvas.drawCircle(cx, cy, radius, paintFill);
// draw a black border around the eye
Paint paintStroke = new Paint();
paintStroke.setColor(Color.BLACK);
paintStroke.setStyle(Paint.Style.STROKE);
paintStroke.setStrokeWidth(5);
canvas.drawCircle(cx, cy, radius, paintStroke);
if (eyeClosed)
// draw horizontal line across closed eye
canvas.drawLine(cx - radius, cy, cx + radius, cy, paintStroke);
else {
// draw big off-center pupil on open eye
paintFill.setColor(Color.BLACK);
float cxPupil = cx - 10;
float cyPupil = cy + 10;
canvas.drawCircle(cxPupil, cyPupil, 25, paintFill);
}
}
在上面的片段中，我只是对眼睛半径进行了硬编码，以显示概念证明。您可能希望使用face.getWidth()的一定百分比来进行更灵活的缩放，以确定适当的值。但是这里的图像处理可以做什么：
有关Mobile Vision API的更多详细信息是here，Udacity's current Advanced Android course对这些内容进行了很好的演练（拍摄照片，将其发送到Mobile Vision，并在其上添加位图）。该课程是免费的，或者你可以看看他们做了什么on Github。
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