The document discusses best practices for loading and caching bitmap images in Android applications. It recommends using a memory cache like LRUCache to cache bitmaps in memory and avoid OutOfMemoryErrors. It also recommends using a disk cache like DiskLruCache to cache bitmaps to disk for faster loading. Libraries like Picasso and Glide are also introduced, which simplify bitmap loading and caching.
SOM (Self-Organizing Map) is one of the most popular artificial neural network algorithms in the unsupervised learning category. For efficient construction of large maps searching the best-matching unit is usually the computationally heaviest operation in the SOM. The parallel nature of the algorithm and the huge computations involved makes it a good target for GPU based parallel implementation. This paper presents an overall idea of the optimization strategies used for the parallel implementation of Basic-SOM on GPU using CUDA programming paradigm.
SOM (Self-Organizing Map) is one of the most popular artificial neural network algorithms in the unsupervised learning category. For efficient construction of large maps searching the best-matching unit is usually the computationally heaviest operation in the SOM. The parallel nature of the algorithm and the huge computations involved makes it a good target for GPU based parallel implementation. This paper presents an overall idea of the optimization strategies used for the parallel implementation of Basic-SOM on GPU using CUDA programming paradigm.
Automated histopathological image analysis: a review on ROI extractioniosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
CETPA INFOTECH PVT LTD is one of the IT education and training service provider brands of India that is preferably working in 3 most important domains. It includes IT Training services, software and embedded product development and consulting services.
http://www.cetpainfotech.com
Digital image processing is the use of computer algorithms to perform image processing on digital images. As a subcategory or field of digital signal processing, digital image processing has many advantages over analog image processing.
Spatial filtering using image processingAnuj Arora
spatial filtering in image processing (explanation cocept of
mask),lapace filtering and filtering process of image for extract information and reduce noise
Bitmap make our app more beautiful and there are some risk as well if we do not handle it correctly. There are many things about the bitmap that we have to know to understand how it works.
Automated histopathological image analysis: a review on ROI extractioniosrjce
IOSR Journal of Computer Engineering (IOSR-JCE) is a double blind peer reviewed International Journal that provides rapid publication (within a month) of articles in all areas of computer engineering and its applications. The journal welcomes publications of high quality papers on theoretical developments and practical applications in computer technology. Original research papers, state-of-the-art reviews, and high quality technical notes are invited for publications.
CETPA INFOTECH PVT LTD is one of the IT education and training service provider brands of India that is preferably working in 3 most important domains. It includes IT Training services, software and embedded product development and consulting services.
http://www.cetpainfotech.com
Digital image processing is the use of computer algorithms to perform image processing on digital images. As a subcategory or field of digital signal processing, digital image processing has many advantages over analog image processing.
Spatial filtering using image processingAnuj Arora
spatial filtering in image processing (explanation cocept of
mask),lapace filtering and filtering process of image for extract information and reduce noise
Bitmap make our app more beautiful and there are some risk as well if we do not handle it correctly. There are many things about the bitmap that we have to know to understand how it works.
Shem will share development tips while explaining how things work under-the-hood. As part of his talk, he will demonstrate the right way of working with images, custom views, ListViews and Animations, with an emphasis of how to make your app feel slick and fast on all Android devices.
Nous entendons aujourd’hui parler de Deep Learning un peu partout : reconnaissance d’images, de sons, génération de textes, etc. Suite aux récentes annonces sur Android Neural Network API et TensorFlowLite et à la release du framework CoreML d’Apple, tout nous pousse vers le “on-device intelligence”.
Bien que les techniques et frameworks soient en train de se démocratiser, il reste difficile d’en voir les applications concrètes en entreprise, et encore moins sur des applications mobiles. Nous avons donc décidé de construire un Proof Of Concept pour relever les défis du domaine.
A travers une application mobile à but éducatif, utilisant du Deep Learning pour de la reconnaissance d’objets, nous aborderons les impacts de ce type de modèles sur les smartphones, l’architecture pour l’entraînement et le déploiement de modèles sur un service Cloud, ainsi que la construction de l’application mobile avec les dernières nouveautés annoncées.
Ever since we broke apart the front and back-end of our systems, we’ve longed to partially reunite them with a shared language. The benefits of code reuse and shared tooling are compelling but is this nirvana possible? In this session we will explore building both the front (mobile and web) and back-end of an application with a shared Kotlin codebase. You will learn how to setup the build, share code, and deploy the back-end as a serverless app.
Reversible data hiding in encrypted images by reserving room before encryptionIEEEFINALYEARPROJECTS
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09849539085, 09966235788 or mail us - ieeefinalsemprojects@gmail.co¬m-Visit Our Website: www.finalyearprojects.org
Lecture 4 from the COSC 426 graduate class on Augmented Reality. Taught by Mark Billinghurst from the HIT Lab NZ at the University of Canterbury. August 1st 2012
With Launchers and Choosers in Windows Phone, 3rd party apps integrate more closely into the underlying operating system while allowing end-users to perform common tasks. With Launchers and Choosers you will provide more functionality to your end-users while still maintaining that consistent user experience that will make your app feel like a native app. In this session we’ll cover how to use Windows Phone resources including camera, video and Bing maps. We’ll also cover accessing contacts and calendar as well as sensors (including accelerometer, compass, gyroscope and motion).
How much is your home screen useful with just icons? Not so much...Deep dive how to differentiate the home screen in order to increases user engagement, decreases the chance that an app will be uninstalled and increases the likelihood of its being used...
Deck was presented in Droidcon NYC 19 #DCNYC19
One important way we measure an Action's success is user engagement, or how effective the Action is at bringing users back after their first interaction. To help make this easier, there are several features you can implement in your Action that give users paths back into your conversation. In this talk covers user engagement features and best practices for Actions on Google
Change the way you navigate inside your Android mobile app. Let's see together how the new navigation architecture component can simplify the implementation of navigation in your app.
If you like or not, nowadays Firebase is an important milestone in the development of mobile applications and you can't avoid it.This deck is based on a true story!
Engage and retain users in the android world - Droidcon Italy 2016Matteo Bonifazi
Making your app engaging, so that users who have installed it actually use it, is crucial to your app’s success. In this speech, we explore a number of Android and Google features you can take advantage of that help make your app a more useful and embedded part of the user’s Android experience.
How to bring your app out from the dust on the web thanks to App Links and App Indexing API. How to acquire new users for you mobile app and to re-engage existing ones thanks to Google Search.
The unconventional devices for the Android video streamingMatteo Bonifazi
Streaming video is not just through Android smartphone and tablet.
The 2014 was the year where Chromecast reached its brightness, getting into 4 millions living rooms. The 2015 instead is the year of the Android TV, the Google way “to smart” the TV.
This talk we’ll give you an overview about the streaming in Android. Starting from video streaming on mobile devices, we will guide you into the evolution of the development through Chromecast up to Android TV.
Matteo Bonifazi and Alessandro Martellucci will be illustrating this talk with their experiences developing mobile television applications for the main Italian broadcaster providers.
What is the real state of the new features, appliance and general news shown in the last Google IO ? What is up whats is down about the new Google technologies...
Video Streaming: from the native Android player to uncoventional devicesMatteo Bonifazi
Getting a streaming video in your Android smartphone or tablet is no longer enough.In the latest period, Google shows how to push this concept forward to new appliances. Chromecast and Android TV are two of the most promising gadgets for upsetting the way users enjoy video streaming.
This talk we’ll give you an overview about the streaming in Android. Starting from video streaming on mobile devices, we will guide you into the evolution of the development through Chromecast up to Android TV. Matteo Bonifazi and Alessandro Martellucci will be illustrating this talk with their experiences developing mobile television applications for the main Italian broadcaster providers.
4. Handling Bitmaps
Loading bitmaps in app is tricky
● Bitmaps can very easily exhaust an app's memory budget.
● Loading bitmaps on the UI thread can degrade your app's
performance
● If your app is loading multiple bitmaps into memory, you
need to skillfully manage memory and disk caching.
6. Images come in all shapes and sizes. In many
cases they are larger than required for a
typical application user interface (UI).
7. Read bitmap dimensions and type
BitmapFactory.Options options = new BitmapFactory.Options();
options.inJustDecodeBounds = true;
BitmapFactory.decodeResource(getResources(), R.id.myimage, options);
int imageHeight = options.outHeight;
int imageWidth = options.outWidth;
String imageType = options.outMimeType;
The BitmapFactory class provides several
decoding methods (decodeByteArray(),
decodeFile(), decodeResource(), etc.) for
creating a Bitmap from various sources
To avoid java.lang.OutOfMemory
exceptions, check the dimensions of a
bitmap before decoding it.
8. Load a Scaled Down Version into Memory
public static int calculateInSampleSize( BitmapFactory.Options options,
int reqWidth, int reqHeight) {
// Raw height and width of image
final int height = options.outHeight; final int width = options.outWidth;
int inSampleSize = 1;
if (height > reqHeight || width > reqWidth) {
//Downsize of the resources
final int halfHeight = height / 2; final int halfWidth = width / 2;
while ((halfHeight / inSampleSize) >= reqHeight &&
(halfWidth / inSampleSize) >= reqWidth) {
inSampleSize *= 2;
}
}
return inSampleSize;
}
A power of two value is calculated because
the decoder uses a final value by rounding
down to the nearest power of two, as per
the inSampleSize documentation.
9. Decode the images
public static Bitmap decodeSampledBitmapFromResource(Resources res, int resId,
int reqWidth, int reqHeight) {
// First decode with inJustDecodeBounds=true to check dimensions
final BitmapFactory.Options options = new BitmapFactory.Options();
options.inJustDecodeBounds = true;
BitmapFactory.decodeResource(res, resId, options);
// Calculate inSampleSize
options.inSampleSize = calculateInSampleSize(options, reqWidth, reqHeight);
// Decode bitmap with inSampleSize set
options.inJustDecodeBounds = false;
return BitmapFactory.decodeResource(res, resId, options);
}
If set to true, the decoder will return null (no
bitmap), but the out... fields will still be set,
allowing the caller to query the bitmap without
having to allocate the memory for its pixels.
10. Load the image into the ImageView
mImageView.setImageBitmap(
decodeSampledBitmapFromResource(getResources(), R.id.myimage, 100, 100));
12. Load a new bitmap for your apps’ social media
stream, or whatever, but you're out of memory.
13. Use a Memory Cache
LRU Cache for all of us
This container keeps a list of objects, and ranks them based
upon how many times they’ve been accessed. When it’s
time to evict one of them (to make space for a new object)
the LRUCache already knows which ones to get rid of. All
done without you having to worry about any of it.
14. Suitable size for a LruCache
Factors should be taken into consideration
● How memory intensive is the rest of your activity and/or
application?
● How many images will be on-screen at once?
● How many need to be available ready to come on-screen?
● What is the screen size and density of the device?
● What dimensions and configuration are the bitmaps?
● How frequently will the images be accessed?
15. There is no ONE SOLUTION!
Avoid java.lang.OutOfMemory exceptions
16. Memory LRU cache
private LruCache<String, Bitmap> mMemoryCache;
protected void onCreate(Bundle savedInstanceState) {
final int maxMemory = (int) (Runtime.getRuntime().maxMemory() / 1024);
// Use 1/8th of the available memory for this memory cache.
final int cacheSize = maxMemory / 8;
mMemoryCache = new LruCache<String, Bitmap>(cacheSize) {
@Override
protected int sizeOf(String key, Bitmap bitmap) {
// The cache size will be measured in kilobytes
// rather than number of items.
return bitmap.getByteCount() / 1024;
}
};
Get max available VM memory,
exceeding this amount will throw an
OutOfMemory exception. Stored in
kilobytes as LruCache takes an
int in its constructor.
17. Memory LRU cache
// Add bitmap to the cache
public void addBitmapToMemoryCache(String key, Bitmap bitmap) {
if (getBitmapFromMemCache(key) == null) {
mMemoryCache.put(key, bitmap);
}
}
//Retrieve the bitmap from the cache
public Bitmap getBitmapFromMemCache(String key) {
return mMemoryCache.get(key);
}
18. Disk LRU cache
private DiskLruCache mDiskLruCache;
private static final int DISK_CACHE_SIZE = 1024 * 1024 * 10; // 10MB
protected void onCreate(Bundle savedInstanceState) {
// Initialize disk cache on background thread
File cacheDir = getDiskCacheDir(this, "thumbnails");
new InitDiskCacheTask().execute(cacheDir);
}
class InitDiskCacheTask extends AsyncTask<File, Void, Void> {
protected Void doInBackground(File... params) {
synchronized (mDiskCacheLock) {
File cacheDir = params[0];
mDiskLruCache = DiskLruCache.open(cacheDir, DISK_CACHE_SIZE);
}
....
19. Disk LRU cache
public void addBitmapToCache(String key, Bitmap bitmap) {
if (getBitmapFromMemCache(key) == null) { // Add to memory cache as before
mMemoryCache.put(key, bitmap);
}
synchronized (mDiskCacheLock) { // Also add to disk cache
if (mDiskLruCache != null && mDiskLruCache.get(key) == null) {
mDiskLruCache.put(key, bitmap);
}
...
public Bitmap getBitmapFromDiskCache(String key) {
synchronized (mDiskCacheLock) {
while (mDiskCacheStarting) {// Wait while disk cache is started
try { mDiskCacheLock.wait(); } ….
if (mDiskLruCache != null) { return mDiskLruCache.get(key); }
....
20. Disk LRU cache
final String imageKey = String.valueOf(params[0]);
// Check disk cache in background thread
Bitmap bitmap = getBitmapFromDiskCache(imageKey);
if (bitmap == null) { // Not found in disk cache
// Process as normal
final Bitmap bitmap = decodeSampledBitmapFromResource(getResources(),
params[0], 100, 100));
}
// Add final bitmap to caches
addBitmapToCache(imageKey, bitmap);