in my app i calculate the CPU usage and i get the result in % but sometimes the result is too big 20.234234234234
My question is, how can i completely remove the result numbers after the "."? And can i do this without changing float to integer?
Here is my code:
private float readCpuUsage() {
try {
RandomAccessFile reader = new RandomAccessFile("/proc/stat", "r");
String load = reader.readLine();
String[] toks = load.split(" ");
long idle1 = Long.parseLong(toks[5]);
long cpu1 = Long.parseLong(toks[2]) + Long.parseLong(toks[3])
+ Long.parseLong(toks[4]) + Long.parseLong(toks[6])
+ Long.parseLong(toks[7]) + Long.parseLong(toks[8]);
try {
Thread.sleep(360);
} catch (Exception e) {
}
reader.seek(0);
load = reader.readLine();
reader.close();
toks = load.split(" ");
long idle2 = Long.parseLong(toks[5]);
long cpu2 = Long.parseLong(toks[2]) + Long.parseLong(toks[3])
+ Long.parseLong(toks[4]) + Long.parseLong(toks[6])
+ Long.parseLong(toks[7]) + Long.parseLong(toks[8]);
return (float) (cpu2 - cpu1) / ((cpu2 + idle2) - (cpu1 + idle1));
} catch (IOException ex) {
ex.printStackTrace();
}
return 0;
}
To print the result i just throw:
textview.setText((readCpuUsage() * 100) + "%");
where readCpuUsage() is the result and to transform it to % i multiply it with 100
This is how i did it:
float xxz=readCpuUsage()*100;
textview.setText(String.format("%.0f",xxz) + "%");
Try This it may be help to you
String.format("%.0f",floatvalue);
or
Float.parseFloat(String.format("%.0f",floatvalue))
It looks like you are unnecessarily complicating things.
When you know for sure that you do not want the decimal component of your number you should just use the integer or long types. Unless you have a valid reason or specific bias against the int datatype.
There is only Long type used in the below operation hence the result will be always long.
return (float) (cpu2 - cpu1) / ((cpu2 + idle2) - (cpu1 + idle1));
I don't understand why are you typecasting it to float at the first place.
Just change the return type to long from float.
And change the return statement to :
return (cpu2 - cpu1) / ((cpu2 + idle2) - (cpu1 + idle1));
float x = 100.5;
float result = x - (int)x;
if (result != 0)
{
//If the value of `result` is not equal to zero, then, you have a decimal portion which is not equal to 0.
//If you want integer result
Integer yourAnswer1 = (Integer)result;
Float yourAnswer2 = (float)result;
}
float f=2443.4333;
println(Math.floor(f)+"");
this will give you result 2443.0
Related
Can I get some examples about pointclouds with ARCore? I really search it for days.
Currently I am working on an application similar to this one:This app
Has the feature to view pcl and save files in .ply format
Thanks
The HelloARSample app renders pointcloud in a scene. You can get the coordinates for each point and save them manually in a .ply format.
To get a point cloud, you can create a float buffer and add the points from each frame.
FloatBuffer myPointCloud = FloatBuffer.allocate(capacity);
Session session = new Session(context);
Frame frame = session.update();
try (PointCloud ptcld = frame.acquirePointCloud()) {
myPointCloud.put(ptcld.getPoints());
}
The float buffer saves the points like [x1,x1,z1,confidence1, x2,x2,z2,confidence2, ...].
I havent looked at .ply file struckture, but if you want to save it to a .pcd file, you must create a header, then insert a point per line. Here is a detailed explanation on how to do it.
I did it like this
private boolean savePointCloudFile() {
String data = "";
String fileName = "pointCloud";
int points = 0;
String holder = "";
// Write the point cloud data by iterating over each point:
for (int i=0; i<pointCloud.position(); i+=4) {
data += pointCloud.get(i) + " " + // x
pointCloud.get(i + 1) + " " + // y
pointCloud.get(i + 2) + " " + // z
pointCloud.get(i + 3) + "\n"; // confidence
points = i;
}
points = points / 4 - 10; // Removed last 10 points to prevent errors in case that I lost points
// Write file header
data = "# .PCD v.7 - Point Cloud Data file format\n" +
"VERSION .7\n" +
"FIELDS x y z rgb\n" + // confidence represented by rgb
"SIZE 4 4 4 4\n" + // you only have 3 values xyz
"TYPE F F F F\n" + // all floats
"COUNT 1 1 1 1\n" +
"WIDTH " + points + "\n" +
"HEIGHT 1\n" +
"VIEWPOINT 0 0 0 1 0 0 0\n" +
"POINTS " + points + "\n" +
"DATA ascii \n" + data;
//BufferedWriter out = new BufferedWriter(new FileWriter(new File(new File(Environment.getExternalStoragePublicDirectory(
// Environment.DIRECTORY_DOCUMENTS), fileName + ".pcd"));
try {
File file = new File(context.getExternalFilesDir(null), fileName +".pcd");
FileOutputStream stream = new FileOutputStream(file);
file.createNewFile();
//FileOutputStream out = new FileOutputStream(file);
stream.write(data.getBytes());
stream.close();
Log.i("SUCCESS", "File saved successfully in " + file.getAbsolutePath());
return true;
} catch (IOException e) {
Log.e("Exception", "File write failed: " + e.toString());
return false;
}
}
You should save the file from within a separate thread as it may cause a timeout error, because it takes too long to save so many points to a file.
You should get a file similar to this
# .PCD v.7 - Point Cloud Data file format
VERSION .7
FIELDS x y z rgb
SIZE 4 4 4 4
TYPE F F F F
COUNT 1 1 1 1
WIDTH 3784
HEIGHT 1
VIEWPOINT 0 0 0 1 0 0 0
POINTS 3784
DATA ascii
0.068493545 -0.18897545 -0.6662081 0.007968704
0.26833203 -0.18425867 -1.5039357 0.02365576
0.19286658 -0.2141684 -1.58289 0.038087178
0.070703566 -0.17931458 -0.69418937 0.016636848
0.044586033 -0.18726173 -0.6926071 0.024707714
0.04002113 -0.20350328 -0.68689686 0.018577512
0.029185327 -0.18594348 -0.73340106 0.12292312
0.0027626567 -0.20299685 -1.5578543 0.15424652
-0.031320766 -0.20478198 -0.70128816 0.13745676
-0.06351853 -0.20185146 -0.61755043 0.15234329
-0.08655308 -0.19128543 -0.6776818 0.170851
1.0159657 -0.41043654 -6.8713074 0.05946503
-0.031778865 -0.20536968 -1.5218562 0.15976532
-0.09223208 -0.19543779 -0.61643535 0.12331226
0.02384475 -0.20319816 -1.7497014 0.15273231
-0.10013421 -0.19931296 -0.5924832 0.16186734
0.49137634 -0.09052197 -5.7263794 0.16080469
To viaualize the point cloud you can use pcl_viewer or Matlab. In Matlab I just typed
ptCloud = pcread('pointCloud.pcd');
pcshow(ptCloud);
I have created a simple Android-Application that takes a photo and stores the devices GPS infos in the exif-tags for the jpg-file. The following code shows this process (i know it's messy)
Android.Locations.Location loc = await client.GetLastLocationAsync();
ByteBuffer buffer = mImage.GetPlanes()[0].Buffer;
byte[] bytes = new byte[buffer.Remaining()];
buffer.Get(bytes);
using (var output = new FileOutputStream(mFile))
{
try
{
output.Write(bytes);
output.Flush();
ExifInterface exif = new ExifInterface(mFile.AbsolutePath);
string[] degMinSec = Location.Convert(loc.Latitude, Format.Seconds).Split(':');
string dms = degMinSec[0] + "/1," + degMinSec[1] + "/1" + degMinSec[2] + "/1000";
string[] degMinSec1 = Location.Convert(loc.Longitude, Format.Seconds).Split(':');
string dms1 = degMinSec1[0] + "/1," + degMinSec1[1] + "/1" + degMinSec1[2] + "/1000";
exif.SetAttribute(ExifInterface.TagGpsLatitude, dms);
exif.SetAttribute(ExifInterface.TagGpsLatitudeRef, loc.Latitude < 0?"S":"N");
exif.SetAttribute(ExifInterface.TagGpsLongitude, dms1);
exif.SetAttribute(ExifInterface.TagGpsLongitudeRef, loc.Longitude < 0 ? "W" : "E");
exif.SaveAttributes();
}
...
So now to the problem:
When i take a picture and debug the loc variable, it looks as this:
as you can see, the latitude is 48.4080605 and de longitude is 15.6257273
when i debug the converted values dms & dms1 they show these values:
dms represents latitude and has the value 48° 24' 29.0178'', dms1 represents longitude and has the value 15° 37' 32.61828''.
when i look at the pictures exif-data in metapicz.com it shows these values:
can anyone explain me what is going on and what i'm doing wrong?
i can't figure out why it shows a different location than it should
dms = degMinSec[0] + "/1," + degMinSec[1] + "/1" + degMinSec[2] + "/1000";
Should that not be
dms = degMinSec[0] + "/1," + degMinSec[1] + "/1," + degMinSec[2] + "/1000";
?
I am implementing the fall detection using accelerometer sensor, and create below code.
public void onSensorChanged(SensorEvent foEvent) {
if (foEvent.sensor.getType() == Sensor.TYPE_ACCELEROMETER) {
double loX = foEvent.values[0];
double loY = foEvent.values[1];
double loZ = foEvent.values[2];
double loAccelerationReader = Math.sqrt(Math.pow(loX, 2)
+ Math.pow(loY, 2)
+ Math.pow(loZ, 2));
mlPreviousTime = System.currentTimeMillis();
Log.i(TAG, "loX : " + loX + " loY : " + loY + " loZ : " + loZ);
if (loAccelerationReader <= 6.0) {
moIsMin = true;
Log.i(TAG, "min");
}
if (moIsMin) {
i++;
Log.i(TAG, " loAcceleration : " + loAccelerationReader);
if (loAccelerationReader >= 30) {
long llCurrentTime = System.currentTimeMillis();
long llTimeDiff = llCurrentTime - mlPreviousTime;
Log.i(TAG, "loTime :" + llTimeDiff);
if (llTimeDiff >= 10) {
moIsMax = true;
Log.i(TAG, "max");
}
}
}
if (moIsMin && moIsMax) {
Log.i(TAG, "loX : " + loX + " loY : " + loY + " loZ : " + loZ);
Log.i(TAG, "FALL DETECTED!!!!!");
Toast.makeText(this, "FALL DETECTED!!!!!", Toast.LENGTH_LONG).show();
i = 0;
moIsMin = false;
moIsMax = false;
}
if (i > 5) {
i = 0;
moIsMin = false;
moIsMax = false;
}
}
}
its give me fall detected, but if i am riding or running it will also give me fall alert.
if i throw device from 6 inch, alert shown.
I also see the sensitivity is device specific.
when i test moto e and mi 4 with same height
Moto e return maximum 32 value for loAccelerationReader
and in mi 4 it will return 60 value for loAccelerationReader
can any one help me out for the correct way.
I got some solution not sure its work for all or not, but i am using below code and its working for me.
if (foEvent.sensor.getType() == Sensor.TYPE_ACCELEROMETER) {
double loX = foEvent.values[0];
double loY = foEvent.values[1];
double loZ = foEvent.values[2];
double loAccelerationReader = Math.sqrt(Math.pow(loX, 2)
+ Math.pow(loY, 2)
+ Math.pow(loZ, 2));
DecimalFormat precision = new DecimalFormat("0.00");
double ldAccRound = Double.parseDouble(precision.format(loAccelerationReader));
if (ldAccRound > 0.3d && ldAccRound < 0.5d) {
//Do your stuff
}
}
You are on the right track. It can detect fall! But it also detect other non-fall events. My suggestion is instead of single point thresholding (e.g. magnitude > 30), get a time interval of accelerometer readings (e.g. 1 second). I am sure that that the readings for fall, running, and driving will be very different statistically (e.g. mean, variance). I hope this can serve as a starting point for your next iteration of detection algorithm.
It is very likely that the readings will be different from machine to machine since the accelerometers they use are different and may have different sensitivity.
I'm writing gallery.But I got double when i use exifInterface.getAttribute(ExifInterface.TAG_EXPOSURE_TIME), it should be rational(fraction). If I open system gallery, it is rational.Please help me.Thanks.
To get precise/correct values use the new ExifInterface support library instead of the old ExifInterface.
You must add to your gradle:
compile "com.android.support:exifinterface:25.1.0"
And then ensure you use the new android.support.media.ExifInterface library instead of the old android.media.ExifInterface.
import android.support.media.ExifInterface;
String getExposureTime(final ExifInterface exif)
{
String exposureTime = exif.getAttribute(ExifInterface.TAG_EXPOSURE_TIME);
if (exposureTime != null)
{
exposureTime = formatExposureTime(Double.valudeOf(exposureTime));
}
return exposureTime;
}
public static String formatExposureTime(final double value)
{
String output;
if (value < 1.0f)
{
output = String.format(Locale.getDefault(), "%d/%d", 1, (int)(0.5f + 1 / value));
}
else
{
final int integer = (int)value;
final double time = value - integer;
output = String.format(Locale.getDefault(), "%d''", integer);
if (time > 0.0001f)
{
output += String.format(Locale.getDefault(), " %d/%d", 1, (int)(0.5f + 1 / time));
}
}
return output;
}
I'm following javacv Face Detection/Recognition code, there is confusion regarding face recognition.. What I'm doing is (Sorry if it sounds stupid but I'm stuck)
1) Detect Face crop it and save it to sdcard and place path in learn.txt file (Learning part)
2) Detect Face crop it and find it in existing faces whether it exists or not, but it always return nearest position even if the face doesn't exist in sample faces..
what I'm doing wrong?
// Method, I'm using to recognize face
public Integer recognizeFace(Bitmap face, Context context) {
Log.i(TAG, "===========================================");
Log.i(TAG, "recognizeFace (single face)");
float[] projectedTestFace;
float confidence = 0.0f;
int nearest = -1; // closest match -- -1 for nothing.
int iNearest;
if (trainPersonNumMat == null) {
return null;
}
Log.i(TAG, "NUMBER OF EIGENS: " + nEigens);
// project the test images onto the PCA subspace
projectedTestFace = new float[nEigens];
// Start timing recognition
long startTime = System.nanoTime();
testFaceImg = bmpToIpl(face);
// saveBmp(face, "blah");
// convert Bitmap it IplImage
//testFaceImg = IplImage.create(face.getWidth(), face.getHeight(),
// IPL_DEPTH_8U, 4);
//face.copyPixelsToBuffer(testFaceImg.getByteBuffer());
// project the test image onto the PCA subspace
cvEigenDecomposite(testFaceImg, // obj
nEigens, // nEigObjs
new PointerPointer(eigenVectArr), // eigInput (Pointer)
0, // ioFlags
null, // userData
pAvgTrainImg, // avg
projectedTestFace); // coeffs
// LOGGER.info("projectedTestFace\n" +
// floatArrayToString(projectedTestFace));
Log.i(TAG, "projectedTestFace\n" + floatArrayToString(projectedTestFace));
final FloatPointer pConfidence = new FloatPointer(confidence);
iNearest = findNearestNeighbor(projectedTestFace, new FloatPointer(pConfidence));
confidence = pConfidence.get();
// truth = personNumTruthMat.data_i().get(i);
nearest = trainPersonNumMat.data_i().get(iNearest); // result
// get endtime and calculate time recognition process takes
long endTime = System.nanoTime();
long duration = endTime - startTime;
double seconds = (double) duration / 1000000000.0;
Log.i(TAG, "recognition took: " + String.valueOf(seconds));
Log.i(TAG, "nearest = " + nearest + ". Confidence = " + confidence);
Toast.makeText(context, "Nearest: "+nearest+" Confidence: "+confidence, Toast.LENGTH_LONG).show();
//Save the IplImage so we can see what it looks like
Random generator = new Random();
int n = 10000;
n = generator.nextInt(n);
String fname = "/sdcard/saved_images/" + nearest + " " + String.valueOf(seconds) + " " + String.valueOf(confidence) + " " + n + ".jpg";
Log.i(TAG, "Saving image as: " + fname);
cvSaveImage(fname, testFaceImg);
return nearest;
} // end of recognizeFace
EDIT The confidence is always negative!
Thanks in advance