Vehicle Speed Estimation via Blob Opencv C++ - opencv

bool checkIfBlobsCrossedTheLine2(std::vector<Blob> &blobs, int &intHorizontalLinePosition,int &intHorizontalLinePosition2, cv::Mat &imgFrame2Copy) {
bool blnAtLeastOneBlobCrossedTheLine = false;
for (auto blob : blobs) {
if (blob.blnStillBeingTracked == true && blob.centerPositions.size() >= 2) {
int prevFrameIndex = (int)blob.centerPositions.size() - 2;
int currFrameIndex = (int)blob.centerPositions.size() - 1;
if ((blob.centerPositions[prevFrameIndex].y > intHorizontalLinePosition && blob.centerPositions[currFrameIndex].y <= intHorizontalLinePosition)&&(blob.centerPositions[prevFrameIndex].y > intHorizontalLinePosition2 && blob.centerPositions[currFrameIndex].y <= intHorizontalLinePosition2)) {
int time = 30;
int distance = 200;
int speed = distance/time;
double dblFontScale = blobs[currFrameIndex].dblCurrentDiagonalSize / 10.0;
int intFontThickness = (int)std::round(dblFontScale * 1.0);
std::cout<<"Speed: "<<speed<<std::endl;
cv::putText(imgFrame2Copy, std::to_string(speed), blobs[currFrameIndex].centerPositions.back(), CV_FONT_HERSHEY_SIMPLEX, dblFontScale, SCALAR_RED, intFontThickness);
blnAtLeastOneBlobCrossedTheLine = true;
}
}
}
return blnAtLeastOneBlobCrossedTheLine;
}
Please I didn't understand why I can't display the speed of each vehicle,
so help please

Related

Run-Time Check Failure #2 - Stack around the variable 'maxlong' was corrupted

I wrote a code to print the length of the longest line from my input and print out as much as possible of the longest line(There is a maximum length of what I can output the longest line). But I got this error. I tried everything I could yet still no clue. Is there anyone who might help?
#include<stdio.h>
#define MAXLINE 10
int getline(char line[], int len) {
int i,c,max;
i = 0;
max = 0;
while ((c = getchar()) != EOF&&c!='\n') {
if (i < len) {
line[i] = c;
}
i += 1;
}
if (i < len) {
if (c == '\n') {
line[i] = c;
i += 1;
}
line[i] = '\0';
}
else if (i >= len) {
line[len] = '\0';
}
return i;
}
void copy(char from[], char to[]) {
int i = 0;
while (from[i] != '\0') {
to[i] = from[i];
i += 1;
}
to[i] = '\0';
}
main() {
char longline[MAXLINE];
char longestline[MAXLINE];
char maxlong[MAXLINE];
int length;
int max = 0;
int maxline = 0;
while ((length = getline(longline, MAXLINE)) > 0) {
if (length > max && length < MAXLINE) {
copy(longline, longestline);
max = length;
}
else if (length > MAXLINE) {
if (length > maxline) {
maxline = length;
copy(longline, maxlong);
}
}
}
if (maxline == 0) {
printf("%s", longestline);
}
else {
printf("%s\n%d\n", maxlong, maxline);
}
}

Can I create Fill and Eraser tools for winrt app like paint app in windows by Win2d or sharpdx?

I tried to create Fill and Eraser Tools by GDI but this way is too slow for windows phone devices and work with large photos with this method is too hard for this divices.
I search for Alternative soulation for Image Processing and find Win2D and Sharpdx but not sure These Api can help me for create these tools.
this is Fill tool in winrtxamltoolkit
public static void FloodFill(this WriteableBitmap target, int x, int y, int outlineColor, int fillColor, byte maxdiff)
{
var width = target.PixelWidth;
var height = target.PixelHeight;
var queue = new List<Pnt>();
using (var context = target.GetBitmapContext(ReadWriteMode.ReadWrite))
{
queue.Add(new Pnt { X = x, Y = y });
while (queue.Count > 0)
{
var p = queue[queue.Count - 1];
queue.RemoveAt(queue.Count - 1);
if (p.X == -1) continue;
if (p.X == width) continue;
if (p.Y == -1) continue;
if (p.Y == height) continue;
if (context.Pixels[width * p.Y + p.X] == outlineColor) continue;
if (context.Pixels[width * p.Y + p.X] == fillColor) continue;
if (context.Pixels[width * p.Y + p.X].MaxDiff(outlineColor) > maxdiff)
{
context.Pixels[width * p.Y + p.X] = fillColor;
}
else
{
continue;
}
context.Pixels[width * p.Y + p.X] = fillColor;
queue.Add(new Pnt { X = p.X, Y = p.Y - 1 });
queue.Add(new Pnt { X = p.X + 1, Y = p.Y });
queue.Add(new Pnt { X = p.X, Y = p.Y + 1 });
queue.Add(new Pnt { X = p.X - 1, Y = p.Y });
}
target.Invalidate();
}
}
and this is Ereaser tool in WriteableBitmapEx
public static void FillEllipseCenteredTrsnceparent(this WriteableBitmap bmp, int xc, int yc, int xr, int yr, Color color)
{
using (BitmapContext context = bmp.GetBitmapContext())
{
Func<Color, int> toInt32 = c =>
{
var i = ((((c.A << 0x18) | (((c.R * c.A + 1) >> 8) << 0x10)) | (((c.G * c.A + 1) >> 8) << 8)) | ((c.B * c.A + 1) >> 8));
return i;
};
int[] pixels = context.Pixels;
int width = context.Width;
int height = context.Height;
if ((xr >= 1) && (yr >= 1))
{
int num3;
int num4;
int num5;
int num6;
int num7;
int num8;
int num9 = xr;
int num10 = 0;
int num11 = (xr * xr) << 1;
int num12 = (yr * yr) << 1;
int num13 = (yr * yr) * (1 - (xr << 1));
int num14 = xr * xr;
int num15 = 0;
int num16 = num12 * xr;
int num17 = 0;
//int sa = (color >> 0x18) & 0xff;
//int sr = (color >> 0x10) & 0xff;
//int sg = (color >> 8) & 0xff;
//int sb = color & 0xff;
//bool flag = !doAlphaBlend || (sa == 0xff);
while (num16 >= num17)
{
num5 = yc + num10;
num6 = yc - num10;
if (num5 < 0)
{
num5 = 0;
}
if (num5 >= height)
{
num5 = height - 1;
}
if (num6 < 0)
{
num6 = 0;
}
if (num6 >= height)
{
num6 = height - 1;
}
num3 = num5 * width;
num4 = num6 * width;
num8 = xc + num9;
num7 = xc - num9;
if (num8 < 0)
{
num8 = 0;
}
if (num8 >= width)
{
num8 = width - 1;
}
if (num7 < 0)
{
num7 = 0;
}
if (num7 >= width)
{
num7 = width - 1;
}
for (int i = num7; i <= num8; i++)
{
pixels[i + num3] = toInt32(color);
pixels[i + num4] = toInt32(color);
}
num10++;
num17 += num11;
num15 += num14;
num14 += num11;
if ((num13 + (num15 << 1)) > 0)
{
num9--;
num16 -= num12;
num15 += num13;
num13 += num12;
}
}
num9 = 0;
num10 = yr;
num5 = yc + num10;
num6 = yc - num10;
if (num5 < 0)
{
num5 = 0;
}
if (num5 >= height)
{
num5 = height - 1;
}
if (num6 < 0)
{
num6 = 0;
}
if (num6 >= height)
{
num6 = height - 1;
}
num3 = num5 * width;
num4 = num6 * width;
num13 = yr * yr;
num14 = (xr * xr) * (1 - (yr << 1));
num15 = 0;
num16 = 0;
num17 = num11 * yr;
while (num16 <= num17)
{
num8 = xc + num9;
num7 = xc - num9;
if (num8 < 0)
{
num8 = 0;
}
if (num8 >= width)
{
num8 = width - 1;
}
if (num7 < 0)
{
num7 = 0;
}
if (num7 >= width)
{
num7 = width - 1;
}
for (int j = num7; j <= num8; j++)
{
pixels[j + num3] = toInt32(color);
pixels[j + num4] = toInt32(color);
}
num9++;
num16 += num12;
num15 += num13;
num13 += num12;
if ((num14 + (num15 << 1)) > 0)
{
num10--;
num5 = yc + num10;
num6 = yc - num10;
if (num5 < 0)
{
num5 = 0;
}
if (num5 >= height)
{
num5 = height - 1;
}
if (num6 < 0)
{
num6 = 0;
}
if (num6 >= height)
{
num6 = height - 1;
}
num3 = num5 * width;
num4 = num6 * width;
num17 -= num11;
num15 += num14;
num14 += num11;
}
}
}
}
}
Is there a way to conver this code to win2d or Sharpdx?

Computing gradient orientation in c++ using opencv functions

Can anyone help me out with this?
I am trying to calculate gradient orientation using the Sobel operator in OpenCV for gradient in x and y direction. I am using the atan2 function for computing the tangent in radians, which I later convert to degrees, but all the angles I am getting are between 0 and 90 degrees.
My expectation is to get angles between 0 and 360 degrees. The image I am using is grayscale. The code segment is here below.
Mat PeripheralArea;
Mat grad_x, grad_y; // this is the matrix for the gradients in x and y directions
int off_set_y = 0, off_set_x = 0;
int scale = 1, num_bins = 8, bin = 0;
int delta=-1 ;
int ddepth = CV_16S;
GaussianBlur(PeripheralArea, PeripheralArea, Size(3, 3), 0, 0, BORDER_DEFAULT);
Sobel(PeripheralArea, grad_y, ddepth, 0, 1,3,scale, delta, BORDER_DEFAULT);
Sobel(PeripheralArea, grad_x, ddepth, 1, 0,3, scale, delta, BORDER_DEFAULT);
for (int row_y1 = 0, row_y2 = 0; row_y1 < grad_y.rows / 5, row_y2 < grad_x.rows / 5; row_y1++, row_y2++) {
for (int col_x1 = 0, col_x2 = 0; col_x1 < grad_y.cols / 5, col_x2 < grad_x.cols / 5; col_x1++, col_x2++) {
gradient_direction_radians = (double) atan2((double) grad_y.at<uchar>(row_y1 + off_set_y, col_x1 + off_set_x), (double) grad_x.at<uchar>(row_y2 + off_set_y, col_x2 + off_set_x));
gradient_direction_degrees = (int) (180 * gradient_direction_radians / 3.1415);
gradient_direction_degrees = gradient_direction_degrees < 0
? gradient_direction_degrees+360
: gradient_direction_degrees;
}
}
Note the off_set_x and off_set_y variable are not part of the computation
but to offset to different square blocks for which I eventually want to
compute an histogram feature vector
You have specified that the destination depth of Sobel() is CV_16S.
Yet, when you access grad_x and grad_y, you use .at<uchar>(), implying that their elements are 8 bit unsigned quantities, when in fact they are 16 bit signed. You could use .at<short>() instead, but to me it looks like there a number of issues with your code, not the least of which is that there is an OpenCV function that does exactly what you want.
Use cv::phase(), and replace your for loops with
cv::Mat gradient_angle_degrees;
bool angleInDegrees = true;
cv::phase(grad_x, grad_y, gradient_angle_degrees, angleInDegrees);
I solved this need when I dived into doing some edge detection using C++.
For orientation of gradient I use artan2(), this standard API defines its +y and +x same as how we usually traverse a 2D image.
Plot it to show you my understanding.
///////////////////////////////
// Quadrants of image:
// 3(-dx,-dy) | 4(+dx,-dy) [-pi,0]
// ------------------------->+x
// 2(-dx,+dy) | 1(+dx,+dy) [0,pi]
// v
// +y
///////////////////////////////
// Definition of arctan2():
// -135(-dx,-dy) | -45(+dx,-dy)
// ------------------------->+x
// 135(-dx,+dy) | +45(+dx,+dy)
// v
// +y
///////////////////////////////
How I do for gradient:
bool gradient(double*& magnitude, double*& orientation, double* src, int width, int height, string file) {
if (src == NULL)
return false;
if (width <= 0 || height <= 0)
return false;
double gradient_x_correlation[3*3] = {-0.5, 0.0, 0.5,
-0.5, 0.0, 0.5,
-0.5, 0.0, 0.5};
double gradient_y_correlation[3*3] = {-0.5,-0.5,-0.5,
0.0, 0.0, 0.0,
0.5, 0.5, 0.5};
double *Gx = NULL;
double *Gy = NULL;
this->correlation(Gx, src, gradient_x_correlation, width, height, 3);
this->correlation(Gy, src, gradient_y_correlation, width, height, 3);
if (Gx == NULL || Gy == NULL)
return false;
//magnitude
magnitude = new double[sizeof(double)*width*height];
if (magnitude == NULL)
return false;
memset(magnitude, 0, sizeof(double)*width*height);
double gx = 0.0;
double gy = 0.0;
double gm = 0.0;
for (int j=0; j<height; j++) {
for (int i=0; i<width; i++) {
gx = pow(Gx[i+j*width],2);
gy = pow(Gy[i+j*width],2);
gm = sqrt(pow(Gx[i+j*width],2)+pow(Gy[i+j*width],2));
if (gm >= 255.0) {
return false;
}
magnitude[i+j*width] = gm;
}
}
//orientation
orientation = new double[sizeof(double)*width*height];
if (orientation == NULL)
return false;
memset(orientation, 0, sizeof(double)*width*height);
double ori = 0.0;
double dtmp = 0.0;
double ori_normalized = 0.0;
for (int j=0; j<height; j++) {
for (int i=0; i<width; i++) {
gx = (Gx[i+j*width]);
gy = (Gy[i+j*width]);
ori = atan2(Gy[i+j*width], Gx[i+j*width])/PI*(180.0); //[-pi,+pi]
if (gx >= 0 && gy >= 0) { //[Qudrant 1]:[0,90] to be [0,63]
if (ori < 0) {
printf("[Err1QUA]ori:%.1f\n", ori);
return false;
}
ori_normalized = (ori)*255.0/360.0;
if (ori != 0.0 && dtmp != ori) {
printf("[Qudrant 1]orientation: %.1f to be %.1f(%d)\n", ori, ori_normalized, (uint8_t)ori_normalized);
dtmp = ori;
}
}
else if (gx >= 0 && gy < 0) { //[Qudrant 4]:[270,360) equal to [-90, 0) to be [191,255]
if (ori > 0) {
printf("[Err4QUA]orientation:%.1f\n", ori);
return false;
}
ori_normalized = (360.0+ori)*255.0/360.0;
if (ori != 0.0 && dtmp != ori) {
printf("[Qudrant 4]orientation:%.1f to be %.1f(%d)\n", ori, ori_normalized, (uint8_t)ori_normalized);
dtmp = ori;
}
}
else if (gx < 0 && gy >= 0) { //[Qudrant 2]:(90,180] to be [64,127]
if (ori < 0) {
printf("[Err2QUA]orientation:%.1f\n", ori);
return false;
}
ori_normalized = (ori)*255.0/360.0;
if (ori != 0.0 && dtmp != ori) {
printf("[Qudrant 2]orientation: %.1f to be %.1f(%d)\n", ori, ori_normalized, (uint8_t)ori_normalized);
dtmp = ori;
}
}
else if (gx < 0 && gy < 0) { //[Qudrant 3]:(180,270) equal to (-180, -90) to be [128,190]
if (ori > 0) {
printf("[Err3QUA]orientation:%.1f\n", ori);
return false;
}
ori_normalized = (360.0+ori)*255.0/360.0;
if (ori != 0.0 && dtmp != ori) {
printf("[Qudrant 3]orientation:%.1f to be %.1f(%d)\n", ori, ori_normalized, (uint8_t)ori_normalized);
dtmp = ori;
}
}
else {
printf("[EXCEPTION]orientation:%.1f\n", ori);
return false;
}
orientation[i+j*width] = ori_normalized;
}
}
return true;
}
How I do for cross correlation:
bool correlation(double*& dst, double* src, double* kernel, int width, int height, int window) {
if (src == NULL || kernel == NULL)
return false;
if (width <= 0 || height <= 0 || width < window || height < window )
return false;
dst = new double[sizeof(double)*width*height];
if (dst == NULL)
return false;
memset(dst, 0, sizeof(double)*width*height);
int ii = 0;
int jj = 0;
int nn = 0;
int mm = 0;
double max = std::numeric_limits<double>::min();
double min = std::numeric_limits<double>::max();
double range = std::numeric_limits<double>::max();
for (int j=0; j<height; j++) {
for (int i=0; i<width; i++) {
for (int m=0; m<window; m++) {
for (int n=0; n<window; n++) {
ii = i+(n-window/2);
jj = j+(m-window/2);
nn = n;
mm = m;
if (ii >=0 && ii<width && jj>=0 && jj<height) {
dst[i+j*width] += src[ii+jj*width]*kernel[nn+mm*window];
}
else {
dst[i+j*width] += 0;
}
}
}
if (dst[i+j*width] > max)
max = dst[i+j*width];
else if (dst[i+j*width] < min)
min = dst[i+j*width];
}
}
//normalize double matrix to be an uint8_t matrix
range = max - min;
double norm = 0.0;
printf("correlated matrix max:%.1f, min:%.1f, range:%.1f\n", max, min, range);
for (int j=0; j<height; j++) {
for (int i=0; i<width; i++) {
norm = dst[i+j*width];
norm = 255.0*norm/range;
dst[i+j*width] = norm;
}
}
return true;
}
For me, I use an image like a hollow rectangle, you can download it on my sample.
The orientation of gradient of the hollow rectangle part of my sample image would move from 0 to 360 clockwise (Quadrant 1 to 2 to 3 to 4).
Here is my print which describes the trace of orientation:
[Qudrant 1]orientation: 45.0 to be 31.9(31)
[Qudrant 1]orientation: 90.0 to be 63.8(63)
[Qudrant 2]orientation: 135.0 to be 95.6(95)
[Qudrant 2]orientation: 180.0 to be 127.5(127)
[Qudrant 3]orientation:-135.0 to be 159.4(159)
[Qudrant 3]orientation:-116.6 to be 172.4(172)
[Qudrant 4]orientation:-90.0 to be 191.2(191)
[Qudrant 4]orientation:-63.4 to be 210.1(210)
[Qudrant 4]orientation:-45.0 to be 223.1(223)
You can see more source code about digital image processing on my GitHub :)

Convert Libraw format to cv::Mat

I'm trying to load RAW formats(especially Nikon .NEF) with libraw library and than convert it to opencv format cv::Mat.
Has anybody solved this problem in past? How do I do this?
I have a conversion method from libraw to QImage (Qt). However, this demonstrates the use of libraw and should be easily adapted to cv::Mat.
My solution is loosely similar to this: https://github.com/mardy/qtraw/blob/master/src/raw-io-handler.cpp
Due to open questions in the comments to the original question, a further comment: You can control the white-balance, chromatic abberation-, distortion correction and much more with libraw: http://www.libraw.org/docs/API-datastruct-eng.html#libraw_output_params_t
Converting embedded RAW thumbnail from libraw to QImage:
LibRaw RawProcessor;
QImage thumbnail;
if( LIBRAW_SUCCESS == RawProcessor.open_file(filename)) {
if( LIBRAW_SUCCESS == RawProcessor.unpack_thumb() ) {
if (LIBRAW_THUMBNAIL_JPEG == RawProcessor.imgdata.thumbnail.tformat ) {
thumbnail.loadFromData((uchar*)RawProcessor.imgdata.thumbnail.thumb,
RawProcessor.imgdata.thumbnail.tlength,
"JPEG");
LibRawImagePerformFlip(RawProcessor.imgdata.sizes.flip, thumbnail);
} else if (LIBRAW_THUMBNAIL_BITMAP == RawProcessor.imgdata.thumbnail.tformat) {
thumbnail = LibRawImageToQImage(
(uchar*)RawProcessor.imgdata.thumbnail.thumb,
RawProcessor.imgdata.thumbnail.twidth,
RawProcessor.imgdata.thumbnail.theight,
RawProcessor.imgdata.thumbnail.tcolors);
} // else: could not read
}
RawProcessor.recycle();
}
Converting full RAW image from libraw to QImage:
LibRaw RawProcessor;
QImage image;
RawProcessor.imgdata.params.gamm[0] = 1.0;
RawProcessor.imgdata.params.gamm[1] = 0.0;
RawProcessor.imgdata.params.user_qual = 0; // fastest interpolation (linear)
RawProcessor.imgdata.params.use_camera_wb = 1;
if( LIBRAW_SUCCESS == rawProcessor.open_file(filename) {
if( LIBRAW_SUCCESS == RawProcessor.unpack() ) {
if (LIBRAW_SUCCESS == RawProcessor.dcraw_process()) {
libraw_processed_image_t* output = RawProcessor.dcraw_make_mem_image();
if (LIBRAW_IMAGE_JPEG == output->type ) {
image.loadFromData((uchar*)output->data,
output->data_size,
"JPEG");
LibRawImagePerformFlip(RawProcessor.imgdata.sizes.flip, image);
} else if (LIBRAW_IMAGE_BITMAP == output->type) {
image= LibRawImageToQImage(
(uchar*)output->data,
output->width,
output->height,
output->colors,
output->bits);
} // else: could not read
LibRaw::dcraw_clear_mem(output);
}
RawProcessor.recycle();
}
}
with the two helper functions:
QImage MiscToolsLibRawImageToQImage(const uchar *data,
const int width,
const int height,
const int nCols,
const int colorBits)
{
int colorSize = (colorBits % 8) == 0 ? colorBits / 8 : ceil(colorBits / 8.0);
int numPixels = width * height;
int pixelSize = nCols * colorSize;
uchar* pixels = new uchar[numPixels * 3];
for (int i = 0; i < numPixels; i++, data += pixelSize) {
if (nCols == 3) {
// this ordering produces correct RGB results - don't ask why
// tested with .CR2 (Canon)
pixels[i * 3] = data[3*colorSize];
pixels[i * 3 + 1] = data[colorSize];
pixels[i * 3 + 2] = data[2*colorSize];
} else {
pixels[i * 3] = data[0];
pixels[i * 3 + 1] = data[0];
pixels[i * 3 + 2] = data[0];
}
}
// immediately create a copy since otherwise we'd have to
// 'delete[] pixels' somewhere else, ourselves
// see http://doc.qt.io/qt-5.5/qimage.html#QImage-6
QImage out = QImage(pixels, width, height, width * 3,
QImage::Format_RGB888).copy();
delete[] pixels;
return out;
}
void LibRawImagePerformFlip(const int flip, QImage& image)
{
if (flip != 0) {
QTransform rotation;
int angle = 0;
if (flip == 3) angle = 180;
else if (flip == 5) angle = -90;
else if (flip == 6) angle = 90;
if (angle != 0) {
rotation.rotate(angle);
image = image.transformed(rotation);
}
}
}

wrong perspective image after taking picture on accelerometer supported blackberry device

There is a perspective image issue when I read a picture that is taken from the camera. When the direction is north, the picture looks like needed to be rotated 270 degrees. When the direction is east, picture should be rotated 180 degrees. But it's good when the direction is west. I tried getMetaData().getKeyValue("orientation") in EncodedImage for producing a good rotating formula, but it returned empty string. Please help me how to solve this problem.
Found solution here:
https://gist.github.com/3788313
import java.io.ByteArrayInputStream;
import java.io.IOException;
import java.io.InputStream;
import javax.microedition.io.Connector;
import javax.microedition.io.file.FileConnection;
import net.rim.device.api.system.Bitmap;
import net.rim.device.api.system.EncodedImage;
public class ExifRotate {
/**
* Flip the image horizontally.
*/
public static final int FLIP_H = 1;
/**
* Flip the image vertically.
*/
public static final int FLIP_V = 2;
/**
* Flip the image horizontally and vertically.
*/
public static final int FLIP_HV = 3;
/**
* Rotate the image 90 degrees clockwise.
*/
public static final int FLIP_90CW = 4;
/**
* Rotate the image 90 degrees counter-clockwise.
*/
public static final int FLIP_90CCW = 5;
/**
* Rotate the image 180 degrees.
*/
public static final int FLIP_180 = 6;
private final static int read2bytes(InputStream in) throws IOException {
return in.read() << 8 | in.read();
}
private final static int readByte(InputStream in) throws IOException {
return in.read();
}
public static Bitmap readImageFromFile(String filename, int width, int height) throws IOException {
EncodedImage img = null;
byte[] data = null;
FileConnection file = null;
try {
file = (FileConnection) Connector.open(filename, Connector.READ);
int fileSize = (int) file.fileSize();
if (fileSize == 0) {
throw new IOException("File is empty");
}
data = new byte[fileSize];
InputStream input = file.openInputStream();
input.read(data);
input.close();
img = EncodedImage.createEncodedImage(data, 0, data.length);
int orientation = -1;
if ( filename.toLowerCase().endsWith(".jpg") || filename.toLowerCase().endsWith(".jpeg")) {
ByteArrayInputStream is = new ByteArrayInputStream( data );
orientation = getRotation(is);
}
if ( orientation == 2 ) {
return rotateBitmap(img.getBitmap(), ImageUtil.FLIP_H);
} else if ( orientation == 3 ) {
return rotateBitmap(img.getBitmap(), ImageUtil.FLIP_180);
} else if ( orientation == 4 ) {
return rotateBitmap(img.getBitmap(), ImageUtil.FLIP_V);
} else if ( orientation == 5 ) {
Bitmap tmp = rotateBitmap(img.getBitmap(), ImageUtil.FLIP_H);
tmp = rotateBitmap(tmp, ImageUtil.FLIP_90CCW);
return tmp;
} else if ( orientation == 6 ) {
return rotateBitmap(img.getBitmap(), ImageUtil.FLIP_90CW);
} else if ( orientation == 7 ) {
Bitmap tmp = rotateBitmap(img.getBitmap(), ImageUtil.FLIP_H);
tmp = rotateBitmap(tmp, ImageUtil.FLIP_90CW);
return tmp;
} else if ( orientation == 8 ) {
return rotateBitmap(img.getBitmap(), ImageUtil.FLIP_90CCW);
} else {
return img.getBitmap();
}
} finally {
if (file != null) {
try { file.close(); }
catch(Exception ex){}
}
}
}
public static int getRotation(InputStream in) throws IOException {
int [] exif_data = new int[100];
int n_flag = 0, set_flag = 0;
int is_motorola = 0;
/* Read File head, check for JPEG SOI + Exif APP1 */
for (int i = 0; i < 4; i++)
exif_data[i] = readByte(in);
if (exif_data[0] != 0xFF || exif_data[1] != 0xD8 || exif_data[2] != 0xFF || exif_data[3] != 0xE1)
return -2;
/* Get the marker parameter length count */
int length = read2bytes(in);
// exif_data = new int[length];
/* Length includes itself, so must be at least 2 */
/* Following Exif data length must be at least 6 */
if (length < 8)
return -1;
length -= 8;
/* Read Exif head, check for "Exif" */
for (int i = 0; i < 6; i++)
exif_data[i] = in.read();
if (exif_data[0] != 0x45 || exif_data[1] != 0x78 || exif_data[2] != 0x69 || exif_data[3] != 0x66 || exif_data[4] != 0 || exif_data[5] != 0)
return -1;
/* Read Exif body */
length = length > exif_data.length ? exif_data.length : length;
for (int i = 0; i < length; i++)
exif_data[i] = in.read();
if (length < 12)
return -1; /* Length of an IFD entry */
/* Discover byte order */
if (exif_data[0] == 0x49 && exif_data[1] == 0x49)
is_motorola = 0;
else if (exif_data[0] == 0x4D && exif_data[1] == 0x4D)
is_motorola = 1;
else
return -1;
/* Check Tag Mark */
if (is_motorola == 1) {
if (exif_data[2] != 0)
return -1;
if (exif_data[3] != 0x2A)
return -1;
} else {
if (exif_data[3] != 0)
return -1;
if (exif_data[2] != 0x2A)
return -1;
}
/* Get first IFD offset (offset to IFD0) */
int offset;
if (is_motorola == 1) {
if (exif_data[4] != 0)
return -1;
if (exif_data[5] != 0)
return -1;
offset = exif_data[6];
offset <<= 8;
offset += exif_data[7];
} else {
if (exif_data[7] != 0)
return -1;
if (exif_data[6] != 0)
return -1;
offset = exif_data[5];
offset <<= 8;
offset += exif_data[4];
}
if (offset > length - 2)
return -1; /* check end of data segment */
/* Get the number of directory entries contained in this IFD */
int number_of_tags;
if (is_motorola == 1) {
number_of_tags = exif_data[offset];
number_of_tags <<= 8;
number_of_tags += exif_data[offset + 1];
} else {
number_of_tags = exif_data[offset + 1];
number_of_tags <<= 8;
number_of_tags += exif_data[offset];
}
if (number_of_tags == 0)
return -1;
offset += 2;
/* Search for Orientation Tag in IFD0 */
for (;;) {
if (offset > length - 12)
return -1; /* check end of data segment */
/* Get Tag number */
int tagnum;
if (is_motorola == 1) {
tagnum = exif_data[offset];
tagnum <<= 8;
tagnum += exif_data[offset + 1];
} else {
tagnum = exif_data[offset + 1];
tagnum <<= 8;
tagnum += exif_data[offset];
}
if (tagnum == 0x0112)
break; /* found Orientation Tag */
if (--number_of_tags == 0)
return -1;
offset += 12;
}
/*
* if (set_flag==1) { Set the Orientation value if (is_motorola==1) {
* exif_data[offset+2] = 0; Format = unsigned short (2 octets)
* exif_data[offset+3] = 3; exif_data[offset+4] = 0; Number Of
* Components = 1 exif_data[offset+5] = 0; exif_data[offset+6] = 0;
* exif_data[offset+7] = 1; exif_data[offset+8] = 0; exif_data[offset+9]
* = set_flag; exif_data[offset+10] = 0; exif_data[offset+11] = 0; }
* else { exif_data[offset+2] = 3; Format = unsigned short (2 octets)
* exif_data[offset+3] = 0; exif_data[offset+4] = 1; Number Of
* Components = 1 exif_data[offset+5] = 0; exif_data[offset+6] = 0;
* exif_data[offset+7] = 0; exif_data[offset+8] = set_flag;
* exif_data[offset+9] = 0; exif_data[offset+10] = 0;
* exif_data[offset+11] = 0; } }
*/
// else {
/* Get the Orientation value */
if (is_motorola == 1) {
if (exif_data[offset + 8] != 0)
return -1;
set_flag = exif_data[offset + 9];
} else {
if (exif_data[offset + 9] != 0)
return -1;
set_flag = exif_data[offset + 8];
}
if (set_flag > 8)
return -1;
// }
/* Write out Orientation value */
if (n_flag == 1)
System.out.println("set_flag " + set_flag);
else
System.out.println("set_flag " + set_flag);
return set_flag;
}
public static Bitmap rotateBitmap(Bitmap src, int operation) {
int width = src.getWidth();
int height = src.getHeight();
int[] inPixels = new int[width*height];
src.getARGB(inPixels, 0, width, 0, 0, width, height);
int x = 0, y = 0;
int w = width;
int h = height;
int newX = 0;
int newY = 0;
int newW = w;
int newH = h;
switch (operation) {
case FLIP_H:
newX = width - (x + w);
break;
case FLIP_V:
newY = height - (y + h);
break;
case FLIP_HV:
newW = h;
newH = w;
newX = y;
newY = x;
break;
case FLIP_90CW:
newW = h;
newH = w;
newX = height - (y + h);
newY = x;
break;
case FLIP_90CCW:
newW = h;
newH = w;
newX = y;
newY = width - (x + w);
break;
case FLIP_180:
newX = width - (x + w);
newY = height - (y + h);
break;
}
int[] newPixels = new int[newW * newH];
int index, newRow, newCol, newIndex;
if ( operation == FLIP_H ) {
for (int row = 0; row < h; row++) {
for (int col = 0; col < w; col++) {
index = row * width + col;
newRow = row;
newCol = w - col - 1;
newIndex = newRow * newW + newCol;
newPixels[newIndex] = inPixels[index];
}
}
} else if ( operation == FLIP_V ) {
for (int row = 0; row < h; row++) {
for (int col = 0; col < w; col++) {
index = row * width + col;
newRow = h - row - 1;
newCol = col;
newIndex = newRow * newW + newCol;
newPixels[newIndex] = inPixels[index];
}
}
} else if ( operation == FLIP_HV ) {
for (int row = 0; row < h; row++) {
for (int col = 0; col < w; col++) {
index = row * width + col;
newRow = col;
newCol = row;
newIndex = newRow * newW + newCol;
newPixels[newIndex] = inPixels[index];
}
}
} else if ( operation == FLIP_90CW ) {
for (int row = 0; row < h; row++) {
for (int col = 0; col < w; col++) {
index = row * width + col;
newRow = col;
newCol = h - row - 1;
newIndex = newRow * newW + newCol;
newPixels[newIndex] = inPixels[index];
}
}
} else if ( operation == FLIP_90CCW ) {
for (int row = 0; row < h; row++) {
for (int col = 0; col < w; col++) {
index = row * width + col;
newRow = w - col - 1;
newCol = row;
newIndex = newRow * newW + newCol;
newPixels[newIndex] = inPixels[index];
}
}
} else if ( operation == FLIP_180 ) {
for (int row = 0; row < h; row++) {
for (int col = 0; col < w; col++) {
index = row * width + col;
newRow = h - row - 1;
newCol = w - col - 1;
newIndex = newRow * newW + newCol;
newPixels[newIndex] = inPixels[index];
}
}
}
Bitmap dst = new Bitmap( newW, newH );
dst.setARGB(newPixels, 0, newW, 0, 0, newW, newH);
return dst;
}
}

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