Develop Reference

Show waveform of audio

I am making one music application in android.In this music list coming from server side. I don'tknow how to show waveform of audio in android ? like in soundcloud website. I have attached image below.

Perhaps, you can implements this feature without libraries, of course if you want only visualisation of audio sample.
For example:
public class PlayerVisualizerView extends View {
/**
* constant value for Height of the bar
*/
public static final int VISUALIZER_HEIGHT = 28;
/**
* bytes array converted from file.
*/
private byte[] bytes;
/**
* Percentage of audio sample scale
* Should updated dynamically while audioPlayer is played
*/
private float denseness;
/**
* Canvas painting for sample scale, filling played part of audio sample
*/
private Paint playedStatePainting = new Paint();
/**
* Canvas painting for sample scale, filling not played part of audio sample
*/
private Paint notPlayedStatePainting = new Paint();
private int width;
private int height;
public PlayerVisualizerView(Context context) {
super(context);
init();
}
public PlayerVisualizerView(Context context, #Nullable AttributeSet attrs) {
super(context, attrs);
init();
}
private void init() {
bytes = null;
playedStatePainting.setStrokeWidth(1f);
playedStatePainting.setAntiAlias(true);
playedStatePainting.setColor(ContextCompat.getColor(getContext(), R.color.gray));
notPlayedStatePainting.setStrokeWidth(1f);
notPlayedStatePainting.setAntiAlias(true);
notPlayedStatePainting.setColor(ContextCompat.getColor(getContext(), R.color.colorAccent));
}
/**
* update and redraw Visualizer view
*/
public void updateVisualizer(byte[] bytes) {
this.bytes = bytes;
invalidate();
}
/**
* Update player percent. 0 - file not played, 1 - full played
*
* #param percent
*/
public void updatePlayerPercent(float percent) {
denseness = (int) Math.ceil(width * percent);
if (denseness < 0) {
denseness = 0;
} else if (denseness > width) {
denseness = width;
}
invalidate();
}
#Override
protected void onLayout(boolean changed, int left, int top, int right, int bottom) {
super.onLayout(changed, left, top, right, bottom);
width = getMeasuredWidth();
height = getMeasuredHeight();
}
#Override
protected void onDraw(Canvas canvas) {
super.onDraw(canvas);
if (bytes == null || width == 0) {
return;
}
float totalBarsCount = width / dp(3);
if (totalBarsCount <= 0.1f) {
return;
}
byte value;
int samplesCount = (bytes.length * 8 / 5);
float samplesPerBar = samplesCount / totalBarsCount;
float barCounter = 0;
int nextBarNum = 0;
int y = (height - dp(VISUALIZER_HEIGHT)) / 2;
int barNum = 0;
int lastBarNum;
int drawBarCount;
for (int a = 0; a < samplesCount; a++) {
if (a != nextBarNum) {
continue;
}
drawBarCount = 0;
lastBarNum = nextBarNum;
while (lastBarNum == nextBarNum) {
barCounter += samplesPerBar;
nextBarNum = (int) barCounter;
drawBarCount++;
}
int bitPointer = a * 5;
int byteNum = bitPointer / Byte.SIZE;
int byteBitOffset = bitPointer - byteNum * Byte.SIZE;
int currentByteCount = Byte.SIZE - byteBitOffset;
int nextByteRest = 5 - currentByteCount;
value = (byte) ((bytes[byteNum] >> byteBitOffset) & ((2 << (Math.min(5, currentByteCount) - 1)) - 1));
if (nextByteRest > 0) {
value <<= nextByteRest;
value |= bytes[byteNum + 1] & ((2 << (nextByteRest - 1)) - 1);
}
for (int b = 0; b < drawBarCount; b++) {
int x = barNum * dp(3);
float left = x;
float top = y + dp(VISUALIZER_HEIGHT - Math.max(1, VISUALIZER_HEIGHT * value / 31.0f));
float right = x + dp(2);
float bottom = y + dp(VISUALIZER_HEIGHT);
if (x < denseness && x + dp(2) < denseness) {
canvas.drawRect(left, top, right, bottom, notPlayedStatePainting);
} else {
canvas.drawRect(left, top, right, bottom, playedStatePainting);
if (x < denseness) {
canvas.drawRect(left, top, right, bottom, notPlayedStatePainting);
}
}
barNum++;
}
}
}
public int dp(float value) {
if (value == 0) {
return 0;
}
return (int) Math.ceil(getContext().getResources().getDisplayMetrics().density * value);
}
}
Sorry, code with a small amount of comments, but it is working visualizer. You can attach it to any players you want.
How you can use it: add this view in your xml layout, then you have to update visualizer state with methods
public void updateVisualizer(byte[] bytes) {
playerVisualizerView.updateVisualizer(bytes);
}
public void updatePlayerProgress(float percent) {
playerVisualizerView.updatePlayerPercent(percent);
}
In updateVisualizer you pass bytes array with you audio sample, and in updatePlayerProgress you dynamically pass percentage, while audio sample is playing.
for converting file to bytes you can use this helper method
public static byte[] fileToBytes(File file) {
int size = (int) file.length();
byte[] bytes = new byte[size];
try {
BufferedInputStream buf = new BufferedInputStream(new FileInputStream(file));
buf.read(bytes, 0, bytes.length);
buf.close();
} catch (FileNotFoundException e) {
e.printStackTrace();
} catch (IOException e) {
e.printStackTrace();
}
return bytes;
}
and for example(very shortly), how it looks like with Mosby library:
public class AudioRecorderPresenter extends MvpBasePresenter<AudioRecorderView> {
public void onStopRecord() {
// stopped and released MediaPlayer
// ...
// some preparation and saved audio file in audioFileName variable.
getView().updateVisualizer(FileUtils.fileToBytes(new File(audioFileName)));
}
}
}
UPD: I created the library for resolving this case github.com/scrobot/SoundWaveView. It still in status "WIP"(work in progress), but soon I will complete it.

I believe Scrobot's answer does not work. It assumes the input audio to be in a certain (quite peculiar) encoding (single-channel/mono linear PCM with 5 bit depth). And the algorithm to calculate amplitudes from the wave function is probably flawed. If you use that algorithm with any commonly used audio file format, you will get nothing but random data.
The truth is: It's just a bit more complicated that that.
Here's what's there to be done to achieve the OP's goal:
Use Android's MediaExtractor to read the input audio file (variousformats/encodings are supported)
Use Android's MediaCodec to decode the input audio encoding to a linear PCM encoding with certain bit depth (usually 16 bit)
Only after this step you got a byte array which you can linearly read and calculate amplitudes from.
Apply a loudness measure to the PCM-encoded data. There are many of them, some more complicated (e.g. LUFS/LKFS), some more basic (RMS). Let's take RMS (= Root Mean Squares) for example:
Determine the number of samples per bar.
Read all the samples for a single bar. Usually there are 2 channels, so for each sample you will get 2 short ints (16 bit) for PCM-16.
For each sample calculate the mean of all channels.
Maybe you will want to normalize the value in some way, e.g. to get float values between -1 and 1 you can divide by (2 / (1 << 16))
Square each sample (hence the "S" in RMS)
Calculate the mean of all the samples for a bar (hence the "M" in RMS)
Calculate the square root of the resulting value (hence the "R" in RMS)
Now you get a value which you can base the height of the bar on.
Repeat steps 2-8 for all the bars.
To implement this is quite an involved task. I could not find any library providing this whole process already. But at least Android's media API provides the algorithms for reading audio file in any format.
Note: RMS is considered a not very accurate loudness measure. But it seems to yield results which are at least somewhat related to what you can actually hear. For many applications it should be good enough.

JETPACK COMPOSE
AudioWaveform is a lightweight Jetpack Compose library that draws a waveform of audio.
XML
WaveformSeekBar is an android library that draws a waveform from a local audio file, resource, and URL using android.view.View (XML approach).
AUDIO PROCESSING
If you're looking for a fast audio processing library, you could use the existing Amplituda library. Amplituda also has caching and compressing features out of the box.

Treshold face images in various light

I want to ask about some ideas / study materials connected to binarization. I am trying to create system that detects human emotions. I am able to get areas such as brows, eyes, nose, mouth etc. but then comes another stage -> processing...
My images are taken in various places/time of day/weather conditions. It's problematic during binarization, with the same treshold value one images are fully black, other looks well and provide me informations I want.
What I want to ask you about is:
1) If there is known way how to bring all images to the same level of brightness?
2) How to create dependency between treshold value and brightness on image?
What I have tried for now is normalize the image... but there are no effects, maybe I'm doing something wrong. I'm using OpenCV (for android)
Core.normalize(cleanFaceMatGRAY, cleanFaceMatGRAY,0, 255, Core.NORM_MINMAX, CvType.CV_8U);
EDIT:
I tried adaptive treshold, OTSU - they didnt work for me. I have problems with using CLAHE in Android but I managed to implement Niblack algorithm.
Core.normalize(cleanFaceMatGRAY, cleanFaceMatGRAY,0, 255, Core.NORM_MINMAX, CvType.CV_8U);
nibelBlackTresholding(cleanFaceMatGRAY, -0.2);
private void nibelBlackTresholding(Mat image, double parameter) {
Mat meanPowered = image.clone();
Core.multiply(image, image, meanPowered);
Scalar mean = Core.mean(image);
Scalar stdmean = Core.mean(meanPowered);
double tresholdValue = mean.val[0] + parameter * stdmean.val[0];
int totalRows = image.rows();
int totalCols = image.cols();
for (int cols=0; cols < totalCols; cols++) {
for (int rows=0; rows < totalRows; rows++) {
if (image.get(rows, cols)[0] > tresholdValue) {
image.put(rows, cols, 255);
} else {
image.put(rows, cols, 0);
}
}
}
}
The results are really good, but still not enough for some images. I paste links cuz images are big and I don't want to take too much screen:
For example this one is tresholded really fine:
https://dl.dropboxusercontent.com/u/108321090/a1.png
https://dl.dropboxusercontent.com/u/108321090/a.png
But bad light produce shadows sometimes and this gives this effect:
https://dl.dropboxusercontent.com/u/108321090/b1.png
https://dl.dropboxusercontent.com/u/108321090/b.png
Do you have any idea that could help me to improve treshold of those images with high light difference (shadows)?
EDIT2:
I found that my previous Algorithm is implemented in wrong way. Std was calculated in wrong way. In Niblack Thresholding mean is local value not global. I repaired it according to this reference http://arxiv.org/ftp/arxiv/papers/1201/1201.5227.pdf
private void niblackThresholding2(Mat image, double parameter, int window) {
int totalRows = image.rows();
int totalCols = image.cols();
int offset = (window-1)/2;
double tresholdValue = 0;
double localMean = 0;
double meanDeviation = 0;
for (int y=offset+1; y<totalCols-offset; y++) {
for (int x=offset+1; x<totalRows-offset; x++) {
localMean = calculateLocalMean(x, y, image, window);
meanDeviation = image.get(y, x)[0] - localMean;
tresholdValue = localMean*(1 + parameter * ( (meanDeviation/(1 - meanDeviation)) - 1 ));
Log.d("QWERTY","TRESHOLD " +tresholdValue);
if (image.get(y, x)[0] > tresholdValue) {
image.put(y, x, 255);
} else {
image.put(y, x, 0);
}
}
}
}
private double calculateLocalMean(int x, int y, Mat image, int window) {
int offset = (window-1)/2;
Mat tempMat;
Rect tempRect = new Rect();
Point leftTop, bottomRight;
leftTop = new Point(x - (offset + 1), y - (offset + 1));
bottomRight = new Point(x + offset, y + offset);
tempRect = new Rect(leftTop, bottomRight);
tempMat = new Mat(image, tempRect);
return Core.mean(tempMat).val[0];
}
Results for 7x7 window and proposed in reference k parameter = 0.34: I still can't get rid of shadow on faces.
https://dl.dropboxusercontent.com/u/108321090/b2.png
https://dl.dropboxusercontent.com/u/108321090/b1.png

things to look at:
http://docs.opencv.org/java/org/opencv/imgproc/CLAHE.html
http://docs.opencv.org/java/org/opencv/imgproc/Imgproc.html#adaptiveThreshold(org.opencv.core.Mat,%20org.opencv.core.Mat,%20double,%20int,%20int,%20int,%20double)
http://docs.opencv.org/java/org/opencv/imgproc/Imgproc.html#threshold(org.opencv.core.Mat,%20org.opencv.core.Mat,%20double,%20double,%20int) (THRESH_OTSU)

Color detection on Vuforia frames with OpenCV for Android

I need to do color detection(ball tracking) for Augmented Reality. I want to use Qualcomms Vuforia SDK for AR and OpenCV for image processing. I found a color detection algorithm that works on desktop(OpenCV, C++) and tried to apply this to FrameMarkers(a Vuforia sample code) but no success yet.
I got a frame from Vuforia(I can only get RGB565 or GRAYSCALE frames.) and convert to OpenCV Mat object and apply same steps with desktop solution. But I got an error on HSV conversion side. Below is the code.
//HSV range for orange objects
const int H_MIN = 7;
const int S_MIN = 186;
const int V_MIN = 60;
const int H_MAX = 256;
const int S_MAX = 256;
const int V_MAX = 157;
const bool shouldUseMorphologicalOperators = true;
const int FRAME_WIDTH = 240;
const int FRAME_HEIGHT = 320;
const int MAX_NUM_OBJECTS = 50;
const int MIN_OBJECT_AREA = 20 * 20;
const int MAX_OBJECT_AREA = 320 * 240 / 1.5;
ObjectTracker::ObjectTracker()
{
x=y=0;
}
ObjectTracker::~ObjectTracker()
{
}
void ObjectTracker::track(QCAR::Frame frame)
{
int nImages = frame.getNumImages();
for(int i = 0; i < nImages; i++)
{
const QCAR::Image *image = frame.getImage(i);
if(image->getFormat() == QCAR::RGB565)
{
Mat RGB565 = Mat(image->getHeight(),image->getWidth(),CV_8UC2,(unsigned char *)image->getPixels());
Mat HSV;
//I got error an error here
cvtColor(RGB565,HSV,CV_RGB2HSV);
Mat thresholdedImage;
inRange(HSV,Scalar(H_MIN,S_MIN,V_MIN),Scalar(H_MAX,S_MAX,V_MAX),thresholdedImage);
if(shouldUseMorphologicalOperators)
applyMorphologicalOperator(thresholdedImage);
trackFilteredObject(x,y,thresholdedImage,RGB565);
//waitKey(30);
}
}
}
void ObjectTracker::applyMorphologicalOperator(Mat &thresholdedImage)
{
//create structuring element that will be used to "dilate" and "erode" image
//the element chosen here is 3px by 3px rectangle
Mat erodeElement = getStructuringElement(MORPH_RECT,Size(3,3));
//dilate with larger element so make sure object is nicely visible
Mat dilateElement = getStructuringElement(MORPH_RECT,Size(8,8));
erode(thresholdedImage,thresholdedImage,erodeElement);
erode(thresholdedImage,thresholdedImage,erodeElement);
dilate(thresholdedImage,thresholdedImage,dilateElement);
dilate(thresholdedImage,thresholdedImage,dilateElement);
}
void ObjectTracker::trackFilteredObject(int &x,int &y,Mat &thresholdedImage,Mat &cameraFeed)
{
Mat temp;
thresholdedImage.copyTo(temp);
//Two vectors needed for output of findContours
vector< vector<Point> > contours;
vector<Vec4i> hierarcy;
//find contours of filtered image using openCV findContours function
findContours(temp,contours,hierarcy,CV_RETR_CCOMP,CV_CHAIN_APPROX_SIMPLE);
//use moments method to find out filtered object
double refArea = 0;
bool objectFound = false;
if(hierarcy.size() > 0)
{
int nObjects = hierarcy.size();
//if number of objects greater than MAX_NUM_OBJECTS we have a noisy filter
if(nObjects < MAX_NUM_OBJECTS )
{
for(int index = 0; index >= 0; index = hierarcy[index][0])
{
Moments moment = moments((cv::Mat)contours[index]);
double area = moment.m00;
//if the area is less than 20 px by 20 px then it is probably just noise
//if the area is the same as the 3/2 of the image size, probably just a bad filter
//we only want the object with the largest area so we safe a reference area each
//iteration and compare it to the area in the next iteration.
if(area > MIN_OBJECT_AREA && area < MAX_OBJECT_AREA && area > refArea)
{
x = moment.m10/area;
y = moment.m01/area;
objectFound = true;
refArea = area;
}
else
objectFound = false;
}
//let user know you found an object
if(objectFound ==true)
{
LOG("Object found");
highlightObject(x,y,cameraFeed);
}
}
else
{
LOG("Too much noise");
}
}
else
LOG("Object not found");
}
void ObjectTracker::highlightObject(int x,int y,Mat &frame)
{
}
How to do proper conversion from RGB565 to HSV color space?

Convert it to RGB888 first using some code from this SO Question.
If you have RGB888 your conversion to HSV should work fine.
EDIT: As mentioned in the Comment. In OpenCV you can do it like this:
use cvtColor(BGR565,RGB,CV_BGR5652BGR) to conver from RGB565 to RGB and then cvtColor(RGB,HSV,CV_RGB2HSV) to convert from RGB to HSV.
EDIT2: It seems that you have to use BGR5652BGR since there is no RGB5652RGB

Compare RGB color values of two images in android

To get RGB values of one image i used the follwing code snippet
int[] pix = new int[picw * pich];
bitmap.getPixels(pix, 0, picw, 0, 0, picw, pich);
int R, G, B,Y;
for (int y = 0; y < pich; y++){
for (int x = 0; x < picw; x++)
{
int index = y * picw + x;
int R = (pix[index] >> 16) & 0xff; //bitwise shifting
int G = (pix[index] >> 8) & 0xff;
int B = pix[index] & 0xff;
//R,G.B - Red, Green, Blue
//to restore the values after RGB modification, use
//next statement
pix[index] = 0xff000000 | (R << 16) | (G << 8) | B;
}}
I want to compare two images,i know that comparing pixel values would be more expensive.I also analysed OpenCV library but i won't
get into my requirement.
Is there any algorithm to compare images using RGB values in android?
or
Is any other method to compare RGB values?
Thanks,

I'm not sure what your requirements are, but if all you want to do is compare the (RGB) color palettes of two images, you might want to use the PaletteFactory methods from Apache Commons Imaging (fka "Sanselan"):
The PaletteFactory methods build up collections (int[] and List<>) which can then be iterated over. I'm not sure just what kind of comparison you need to do, but a fairly simple case, using e.g. makeExactRgbPaletteSimple(), would be:
final File img1 = new File("path/to/image_1.ext")
final File img2 = new File("path/to/image_2.ext")
final PaletteFactory pf;
final int MAX_COLORS = 256;
final Palette p1 = pf.makeExactRgbPaletteSimple(img1, MAX_COLORS);
final Palette p2 = pf.makeExactRgbPaletteSimple(img2, MAX_COLORS);
final ArrayList<Int> matches = new ArrayList<Int>(Math.max(p1.length(), p2.length()));
int matchPercent;
// Palette objects are pre-sorted, afaik
if ( (p1 != null) && (p2 != null) ) {
if (p1.length() > p2.length()) {
for (int i = 0; i < p1.length(); i++) {
final int c1 = p1.getEntry(i);
final int c2 = p2.getPaletteIndex(c1);
if (c2 != -1) {
matches.add(c1);
}
}
matchPercent = ( (int)( (float)matches.size()) / ((float)p1.length) * 100 ) )
} else if (p2.length() >= p1.length()) {
for (int i = 0; i < p1.length(); i++) {
final int c1 = p2.getEntry(i);
final int c2 = p1.getPaletteIndex(c1);
if (c2 != -1) {
matches.add(c1);
}
}
matchPercent = ( (int)( (float)matches.size()) / ((float)p2.length) * 100 ) )
}
}
This is just a minimal example which may or may not compile and is almost certainly not what you're looking for in terms of comparison logic.
Basically what it does is check if each member of p1 is also a member of p2, and if so, adds it to matches. Hopefully the logic is correct, no guarantees. matchPercent is the percentage of colors which exist in both Palettes.
This is probably not the comparison method you want. It is just a simple example.
You will definitely need to play around with the 2nd parameter to makeExactRgbPaletteSimple(), int max, as I chose 256 arbitrarily - remember, the method will (annoyingly, imo) return null if max is too small.
I would suggest building from source as the repos have not been updated for quite some time. The project is definitely not mature, but it is fairly small, reasonably fast for medium-sized images, and pure Java.
Hope this helps.

android ffmpeg opengl es render movie

I am trying to render video via the NDK, to add some features that just aren't supported in the sdk. I am using FFmpeg to decode the video and can compile that via the ndk, and used this as a starting point. I have modified that example and instead of using glDrawTexiOES to draw the texture I have setup some vertices and am rendering the texture on top of that (opengl es way of rendering quad).
Below is what I am doing to render, but creating the glTexImage2D is slow. I want to know if there is any way to speed this up, or give the appearance of speeding this up, such as trying to setup some textures in the background and render pre-setup textures. Or if there is any other way to more quickly draw the video frames to screen in android? Currently I can only get about 12fps.
glClear(GL_COLOR_BUFFER_BIT);
glEnableClientState(GL_VERTEX_ARRAY);
glEnableClientState(GL_TEXTURE_COORD_ARRAY);
glBindTexture(GL_TEXTURE_2D, textureConverted);
//this is slow
glTexImage2D(GL_TEXTURE_2D, /* target */
0, /* level */
GL_RGBA, /* internal format */
textureWidth, /* width */
textureHeight, /* height */
0, /* border */
GL_RGBA, /* format */
GL_UNSIGNED_BYTE,/* type */
pFrameConverted->data[0]);
glEnableClientState(GL_TEXTURE_COORD_ARRAY);
glTexCoordPointer(2, GL_FLOAT, 0, texCoords);
glVertexPointer(3, GL_FLOAT, 0, vertices);
glDrawElements(GL_TRIANGLES, 6, GL_UNSIGNED_BYTE, indices);
glDisableClientState(GL_VERTEX_ARRAY);
glDisableClientState(GL_TEXTURE_COORD_ARRAY);
EDIT
I changed my code to initialize a gltextImage2D only once, and modify it with glSubTexImage2D, it didn't make much of an improvement to the framerate.
I then modified the code to modify a native Bitmap object on the NDK. With this approach I have a background thread that runs that process the next frames and populates the bitmap object on the native side. I think this has potential, but I need to get the speed increased of converting the AVFrame object from FFmpeg into a native bitmap. Below is currently what I am using to convert, a brute force approach. Is there any way to increase the speed of this or optimize this conversion?
static void fill_bitmap(AndroidBitmapInfo* info, void *pixels, AVFrame *pFrame)
{
uint8_t *frameLine;
int yy;
for (yy = 0; yy < info->height; yy++) {
uint8_t* line = (uint8_t*)pixels;
frameLine = (uint8_t *)pFrame->data[0] + (yy * pFrame->linesize[0]);
int xx;
for (xx = 0; xx < info->width; xx++) {
int out_offset = xx * 4;
int in_offset = xx * 3;
line[out_offset] = frameLine[in_offset];
line[out_offset+1] = frameLine[in_offset+1];
line[out_offset+2] = frameLine[in_offset+2];
line[out_offset+3] = 0;
}
pixels = (char*)pixels + info->stride;
}
}

Yes, texture (and buffer, and shader, and framebuffer) creation is slow.
That's why you should create texture only once. After it is created, you can modify its data by calling glSubTexImage2D.
And to make uploading texture data more faster - create two textures. While you use one to display, upload texture data from ffmpeg to second one. When you display second one, upload data to first one. And repeat from beginning.
I think it will still be not very fast. You could try to use jnigraphics library that allows to access Bitmap object pixels from NDK. After that - you just diplay this Bitmap on screen on java side.

Yes, you can optimized this code:
static void fill_bitmap(AndroidBitmapInfo* info, void *pixels, AVFrame *pFrame)
{
uint8_t *frameLine;
int yy;
for (yy = 0; yy < info->height; yy++)
{
uint8_t* line = (uint8_t*)pixels;
frameLine = (uint8_t *)pFrame->data[0] + (yy * pFrame->linesize[0]);
int xx;
for (xx = 0; xx < info->width; xx++) {
int out_offset = xx * 4;
int in_offset = xx * 3;
line[out_offset] = frameLine[in_offset];
line[out_offset+1] = frameLine[in_offset+1];
line[out_offset+2] = frameLine[in_offset+2];
line[out_offset+3] = 0;
}
pixels = (char*)pixels + info->stride;
}
}
to be something like:
static void fill_bitmap(AndroidBitmapInfo* info, void *pixels, AVFrame *pFrame)
{
uint8_t *frameLine = (uint8_t *)pFrame->data[0];
int yy;
for (yy = 0; yy < info->height; yy++)
{
uint8_t* line = (uint8_t*)pixels;
int xx;
int out_offset = 0;
int in_offset = 0;
for (xx = 0; xx < info->width; xx++) {
int out_offset += 4;
int in_offset += 3;
line[out_offset] = frameLine[in_offset];
line[out_offset+1] = frameLine[in_offset+1];
line[out_offset+2] = frameLine[in_offset+2];
line[out_offset+3] = 0;
}
pixels = (char*)pixels + info->stride;
frameLine += pFrame->linesize[0];
}
}
That will save you some cycles.

A couple of minor additions will solve your problem, first convert your AVFrame to RGB with swscale, then apply it directly to your texture i.e.:
AVPicture *pFrameConverted;
struct SwsContext img_convert_ctx;
void init(){
pFrameConverted=(AVPicture *)avcodec_alloc_frame();
avpicture_alloc(pFrameConverted, AV_PIX_FMT_RGB565, videoWidth, videoHeight);
img_convert_ctx = sws_getCachedContext(&img_convert_ctx,
videoWidth,
videoHeight,
pCodecCtx->pix_fmt,
videoWidth,
videoHeight,
AV_PIX_FMT_RGB565,
SWS_FAST_BILINEAR,
NULL, NULL, NULL );
ff_get_unscaled_swscale(img_convert_ctx);
}
void render(AVFrame* pFrame){
sws_scale(img_convert_ctx, (uint8_t const * const *)pFrame->data, pFrame->linesize, 0, pFrame->height, pFrameConverted->data, pFrameConverted->lineSize);
glClear(GL_COLOR_BUFFER_BIT);
glTexSubImage2D(GL_TEXTURE_2D, 0, 0, 0, videoWidth, videoHeight, GL_RGB, GL_UNSIGNED_BYTE, pFrameConverted->data[0]);
glDrawTexiOES(0, 0, 0, videoWidth, videoHeight);
}

Oh,maybe you can use jnigraphics as https://github.com/havlenapetr/FFMpeg/commits/debug.
but if when you get yuv data after decode frame,you should convert it to RGB555,it is too slowly.Use android's mediaplayer is a good idea