Numerous times I have seen people post on android-developers about some code they got from somewhere to accomplish something, which uses such tricks and will in fact break in the future. In spite of all that effort, if you know the right tricks you can easily subvert those protections - such by using reflection in Java, or copying in a header like here in C++ - which others then see and use without realizing what they are doing. We have spent literally months of engineering time trying to clearly define what can be supported and what can't, and setting things up so that developers will as clearly as possible know when they get outside of that supported world. Here are some examples of the same using other techniques I have tested:
#Ndk camera android#
I have been experimenting with performance of different frameworks or technologies to understand performance of image processing in Android taking this as the problem statement. The reason I chose this as the problem statement, is because YUV_420_888 is one of the most common OUTPUT format supported from Android Camera APIs and images are commonly consumed as Bitmap in Android - thus making this a fairly common problem statement to address. Also, the articles below have better description of the problem statement. You can read more about YUV format on Wikipedia. The problem statement is to convert an 8MP (3264x2448) image in a certain format called YUV_420_888 which has one planar Y channel and two semi-planar subsampled UV channels to ARGB_8888 format which is commonly supported with Bitmap in Android. Example problem statement: YUV to RGB conversion
If you are looking for “Fast image processing using Java Native Interface or JNI in Android” - I believe you have come to the right place, this article will help you the same. I’ll also show by an example that the performance of a very simple and unoptimized C++ code comes very close to fairly optimized Java code for the same problem statement.
#Ndk camera how to#
This is a very basic article demonstrating how to do image processing with native code in Android. In my experience, its both easier and better to handle these complex image processing operations with native code very particularly to keep it performant. The smartphones these days are also equipped with multicore, SIMD supported CPUs, so there are ways to do it faster than serialized 13 million iterations but at the same time the types of algorithms we want to run are usually much more complex than the one I just stated. Image(x, y) = std::clamp(alpha * image(x, y) + beta, 0, 255) It’s easy to find 13MP (Mega Pixels), 24MP, 48MP or even 108MP cameras now being shipped on Android devices. These days camera on phones are easily equipped with high resolution sensors. If you are writing applications that processes large images captured with a camera or an existing image on the device you need to be extra careful. I don’t need to oversell the importance of performance to my manager or to you, but I came across this snippet which strengthens the performance is a feature construct - it’s a good to know fact. Half a second delay killed user satisfaction. Half a second delay caused a 20% drop in traffic. The page with 30 results took 0.9 seconds. the page with 10 results took 0.4 seconds to generate. I work onĪn Android Camera App and my team gives very high priority to performance.
#Ndk camera software#
Performance is a feature for most of the software products out there, but thereĪre few programs which are more performance sensitive than the others.
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