Using Native OpenCV Code in Android Projects

8 min readOct 6, 2016

There are many ways to integrate the OpenCV library into Android projects. The simplest way is to invoke the OpenCV Manager APIs provided by the OpenCV Manager, an individual app containing the actual library, which is published and maintained by the official OpenCV dev group and must be installed on the device before running apps that require OpenCV. This using model is the easiest one to be implemented among all the methods but it seems to be the worst one for the end users because they need to install another “useless” app on their phones.

A better way than using the OpenCV Manager is to import the OpenCV4Android distribution into the projects. Generated library files can be found in the SDK and the download link can be found directly on the OpenCV home page. You can find the libraries in the sdk/native/libs directory. Copy them into your src/main/jniLibs directory and you can use the OpenCV Java APIs. Writing OpenCV codes in Java seems to be attracting because of the familiar language features like garbage collection and the not-so-bad performance as the computations are performed on the native level via JNI.

However, both the two methods above have the same drawback that, when you’re performing too much API calls to the OpenCV, the extra cost of JNI calls will sorely slow down the computations. Besides, the Java APIs are not the same as the native C++ APIs of OpenCV. For example, you cannot find an alternative in the Java APIs to the Vec class used widely in the C++ side, so when you are “translating” some C++ OpenCV codes into Java, you might easily get confused by the differences of the two sets of APIs.

Thus when you require the maximum performance or you need 100% API support or if you’ve got some native C++ OpenCV code that you want to use directly in your project, the only way is to import the native OpenCV library into your projects.

Writing native code means you need to set up NDK for your development environment. Remember to add the path to NDK into your PATH environment variable. I’m assuming that you’ve already installed and configured the NDK properly. If not, you may find an official guide provided here.

Prepare the OpenCV Library

First of all, you need to prepare the OpenCV library. Download the OpenCV for Android SDK from the OpenCV home page. Extract the zip file to somewhere you like. Go to the sdk/native/jni directory, and you can find many .mk and .cmake files here along with the C++ header files in include. Create a directory named jni in the app/src/main directory of your Android project (replace app with your module’s name if you are importing the OpenCV library into another module), and then copy all the files and directories from OpenCV’s sdk/native/jni to your newly created jni directory.

After that, copy 3rdparty and libs two folders from OpenCV’s sdk/native/ to app/main/. These directories contain the libraries that are required to build the native OpenCV code.

Finally, you should import the OpenCV Java code as a module into your project. Select File > New > Import Module in the Android Studio’s menu bar, browse the location of the sdk/java directory of the extracted OpenCV library, and type in a name you’d like to use (e.g., open-cv). You’ll need to use the Java interfaces of the OpenCV Android SDK when interacting with the native C++ code and share types like Mat from OpenCV. Remember to open the module settings of your app module and add the open-cv module as a dependency.

Get the C++ Code Ready

After importing the OpenCV library into your project, it’s time to get use of your C++ code. In order to use native C++ code in your Android project, you need to make a NDK module and build it into a library file to be included in the APK files (a NDK module is different from a module in an Android project, which is just a logical project containing a bunch of code and configuration files).

Create two files named and in the jni directory, which is required for the Android NDK’s ndk-build tool to build the JNI project. You can find more about the two .mk files at here and there. Basically you can write them like this:

You can find the explanations of the code at the Android Development with OpenCV tutorial.

Some key points you need to pay attention to when writing your own .mk files:

  1. CLEAR_VARS clears many LOCAL_* variables for you, which must be placed above all the other includes and variable declarations.
  2. Setting OPENCV_INSTALL_MODULES to on will copy necessary OpenCV dynamic libraries to the libs directory and include them into APK files. OPENCV_CAMERA_MODULES is used to enable native OpenCV camera related libraries.
  3. LOCAL_MODULE defines the name that will be used to name your compiled native library. For example, if you set LOCAL_MODULE to CvExample, then the compile library will be named as
  4. LOCAL_SRC_FILES includes the C++ programs that you write. In the example above the first file com_example_yourapp_CvUtil.cpp is a C++ class generated by JNI, which will be introduced later. The second one is the C++ file that contains your native OpenCV code.
  5. APP_STL in chooses a runtime to provide Standard C++ Library support for your native code. You can find a list of runtimes and the differences between them here.
  6. APP_PLATFORM defines the target Android version to build the native library. You must install the corresponding Android platform and build tools in the Android SDK Manager before building your native code.

In order to use the JNI module you’ve created, you should clear the default JNI source directories in build.gradle of your app module. Add a sourceSets part into android in the file and write something like:

With the NDK project configured, you can now copy your OpenCV C++ programs into the jni directory. But in order to call the native C++ methods from your Java code, you have to use Java Native Interface (JNI) which acts as a bridge between Java and C++. You can find the official introduction and guide to the JNI here. Here I’ll provide a simple example of creating a JNI.

1. Write a Java class.

The Java class should contain the methods that you would like to call “from the C++ code” by which I mean the Java methods declarations are connected through the JNI with the C++ methods definitions.

Let’s suppose that you need to send a Mat with a float threshold value from the Java code to your native C++ code. Then you should generate some data from the Mat and the threshold and return it back to the Java code. To help you understand how the complex data types should be dealt with in JNI, I’m assuming the return type is an ArrayList of (two) float arrays which both contain 10 elements, complex enough. You can define the Java class like this:

The static part of this class loads the OpenCV library and the library that your C++ code will be built into. The OpenCVLoader#initDebug method loads the OpenCV library in debugging mode, which will load the lib instead of using the OpenCV Manager APIs. CvExample is what we named the NDK module in the file.

Two methods named processMat are declared. The first method is the one that should be called, which will convert the Mat into a native object address and pass it to the native code. The second one with the native modifier has its method body defined in the C++ code.

2. Generate a JNI C++ class.

After creating the Java class, you can generate a JNI C++ class with the javah command in your terminal. For example:

$ cd your_app_project/app/src/main/jni
$ javah -jni -d ./ -cp ~/Library/Android/sdk/platforms/android-15/android.jar:../../../../open-cv/src/main/java:../java com.example.yourapp.CvUtil

Read more about the javah tool at Oracle’s Java Documetation.

The -cp argument defines the classpaths from which javah should find the classes, separated by a colon in Unix or a semicolon in Windows. Here the first path points to an android.jar of the version same to the one you specified in The second one is the java folder of your open-cv module in your Android project, providing references to the OpenCV Java classes and interfaces. The last path is where your Java files is located.

After executing the command, a header file named com_example_yourapp_CvUtil.h should be generated in the jni folder. The content should be like:

The CvUtil#processMat method is converted into a C++ function declaration. Be careful with the signature in the method’s comment. A signature is by what a method can be identified. You can see the method arguments are represented as (JF), J for long and F for float. The return type is represented as Ljava/util/ArrayList, and the L stands for “fully qualified class”, which means it is a Java class referred to by the following qualifier java/util/ArrayList. Now that the header is generated, you need to implement the function in a separate .cpp file.

Read more about the types and signatures in JNI at JNI Types and Data Structures.

3. Provide your C++ code.

Create a file next to the .h file generated named com_example_yourapp_CvUtil.cpp. Now you can implement the function with the C++ OpenCV program you’ve already got — just include it into this C++ code and call the functions from that one. Here I will only show how to parse the data provided by the function call and how to return data back to Java.

There are four arguments with the generated function declaration. The first one is a pointer to JNIEnv which is a environmental object of the JNI providing many useful functions (sounds like Context in Android). The second argument type is jclass, which is a reference to a class in Java. Here it is the class of which the method belongs to. The following two arguments are what we will pass from the Java caller to this C++ function, in which jlong and jfloat can be viewed as a C++ wrapper for Java’s primitive types long and float. Let’s name the four arguments like the code below:

The mat_addr is a native object address as mentioned above, which means you can directly create a Mat from this address like:

cv::Mat *image = (cv::Mat *) image_addr;

Now you can process the Mat and prepare to return some data. Here’s how an ArrayList<float[]> object is created:

Now we’ve created two float arrays, how can we put values into these arrays? Can we directly put C++ float values into Java float arrays? Absolutely not. Although JNI provides methods like JNIEnv#SetObjectArrayElement which can set the value of an element in a jobjectArray, you just cannot use the C++ data types here. You must use java.lang.Float instead here, because the Float class has a constructor so that we can put the value into it using the method ID of the constructor.

Huge work to be done for a simple task, isn’t it?

Build Your Native Library

Android doesn’t provide the ability to run the C++ code directly on your phone. Instead, you should build your native module into a library for your app to use.

The ndk-build tool from the NDK is used to build your native module. You can use ndk-build in your terminal, but there’s a more convenient way of doing this. You can write some tasks in your build.gradle to ask Gradle to build it for you every time you compile your project. The task is created like:

Set the ndkBuild task as a dependency of Gradle’s JavaCompile tasks:

Build your project and you will find the generated library files at app/build/intermediates/ndk/libs folder of your project. You need to copy them to your app/src/main/jniLibs directory. Also, you should copy from OpenCV’s sdk/native/libs into jniLibs too. Now you can call the method you declared in the CvUtil class and thus make use of your native OpenCV programs.

Whenever you build your project, your JNI module will be built automatically. If you’ve made any changes to the native code, don’t forget to copy the latest libs into your app/src/main/jniLibs directory.