- Note
- You don't have to build your own copy if you simply want to start using it. Refer the Using Opencv.js tutorial for steps on getting a prebuilt copy from our releases or online documentation.
Installing Emscripten
Emscripten is an LLVM-to-JavaScript compiler. We will use Emscripten to build OpenCV.js.
- Note
- While this describes installation of required tools from scratch, there's a section below also describing an alternative procedure to perform the same build using docker containers which is often easier.
To Install Emscripten, follow instructions of Emscripten SDK.
For example:
After install, ensure the EMSDK
environment is setup correctly.
For example:
Modern versions of Emscripten requires to use emcmake
/ emmake
launchers:
The version 2.0.10 of emscripten is verified for latest WebAssembly. Please check the version of Emscripten to use the newest features of WebAssembly.
For example:
Obtaining OpenCV Source Code
You can use the latest stable OpenCV version or you can grab the latest snapshot from our Git repository.
Obtaining the Latest Stable OpenCV Version
- Go to our releases page.
- Download the source archive and unpack it.
Obtaining the Cutting-edge OpenCV from the Git Repository
Launch Git client and clone OpenCV repository.
For example:
- Note
- It requires
git
installed in your development environment.
Building OpenCV.js from Source
To build
opencv.js
, execute python script<opencv_src_dir>/platforms/js/build_js.py <build_dir>
.For example, to build in
build_js
directory:emcmake python ./opencv/platforms/js/build_js.py build_js- Note
- It requires
python
andcmake
installed in your development environment.
The build script builds asm.js version by default. To build WebAssembly version, append
--build_wasm
switch. By default everything is bundled into one JavaScript file bybase64
encoding the WebAssembly code. For production builds you can add--disable_single_file
which will reduce total size by writing the WebAssembly code to a dedicated.wasm
file which the generated JavaScript file will automatically load.For example, to build wasm version in
build_wasm
directory:emcmake python ./opencv/platforms/js/build_js.py build_wasm --build_wasm[Optional] To build the OpenCV.js loader, append
--build_loader
.For example:
emcmake python ./opencv/platforms/js/build_js.py build_js --build_loader- Note
- The loader is implemented as a js file in the path
<opencv_js_dir>/bin/loader.js
. The loader utilizes the WebAssembly Feature Detection to detect the features of the browser and load corresponding OpenCV.js automatically. To use it, you need to use the UMD version of WebAssembly Feature Detection and introduce theloader.js
in your Web application.
Example Code:
// Set paths configurationlet pathsConfig = {wasm: "../../build_wasm/opencv.js",threads: "../../build_mt/opencv.js",simd: "../../build_simd/opencv.js",threadsSimd: "../../build_mtSIMD/opencv.js",}// Load OpenCV.js and use the pathsConfiguration and main function as the params.loadOpenCV(pathsConfig, main);[optional] To build documents, append
--build_doc
option.For example:
emcmake python ./opencv/platforms/js/build_js.py build_js --build_doc- Note
- It requires
doxygen
installed in your development environment.
[optional] To build tests, append
--build_test
option.For example:
emcmake python ./opencv/platforms/js/build_js.py build_js --build_test[optional] To enable OpenCV contrib modules append
--cmake_option="-DOPENCV_EXTRA_MODULES_PATH=/path/to/opencv_contrib/modules/"
For example:
emcmake python ./platforms/js/build_js.py build_js --cmake_option="-DOPENCV_EXTRA_MODULES_PATH=opencv_contrib/modules"[optional] To enable WebNN backend, append
--webnn
option.For example:
emcmake python ./opencv/platforms/js/build_js.py build_js --webnn
Running OpenCV.js Tests
Remember to launch the build command passing --build_test
as mentioned previously. This will generate test source code ready to run together with opencv.js
file in build_js/bin
Manually in your browser
To run tests, launch a local web server in \<build_dir\>/bin
folder. For example, node http-server which serves on localhost:8080
.
Navigate the web browser to http://localhost:8080/tests.html
, which runs the unit tests automatically. Command example:
- Note
- This snippet and the following require Node.js to be installed.
Headless with Puppeteer
Alternatively tests can run with GoogleChrome/puppeteer which is a version of Google Chrome that runs in the terminal (useful for Continuous integration like travis CI, etc)
- Note
- Checkout
node run_puppeteer --help
for more options to debug and reporting. -
The command
npm install
only needs to be executed once, since installs the tools dependencies; after that they are ready to use. -
Use
PUPPETEER_SKIP_CHROMIUM_DOWNLOAD=1 npm install --no-save puppeteer
to skip automatic downloading of Chromium. You may specify own Chromium/Chrome binary throughPUPPETEER_EXECUTABLE_PATH=$(which google-chrome)
environment variable. BEWARE: Puppeteer is only guaranteed to work with the bundled Chromium, use at your own risk.
Using Node.js.
For example:
- Note
- If all tests are failed, then consider using Node.js from 8.x version (
lts/carbon
fromnvm
).
[optional] To build
opencv.js
with threads optimization, append--threads
option.For example:
emcmake python ./opencv/platforms/js/build_js.py build_js --build_wasm --threadsThe default threads number is the logic core number of your device. You can use
cv.parallel_pthreads_set_threads_num(number)
to set threads number by yourself and usecv.parallel_pthreads_get_threads_num()
to get the current threads number.- Note
- You should build wasm version of
opencv.js
if you want to enable this optimization. And the threads optimization only works in browser, not in node.js. You need to enable theWebAssembly threads support
feature first with your browser. For example, if you use Chrome, please enable this flag in chrome://flags.
[optional] To build
opencv.js
with wasm simd optimization, append--simd
option.For example:
emcmake python ./opencv/platforms/js/build_js.py build_js --build_wasm --simdThe simd optimization is experimental as wasm simd is still in development.
- Note
- Now only emscripten LLVM upstream backend supports wasm simd, referring to https://emscripten.org/docs/porting/simd.html. So you need to setup upstream backend environment with the following command first: ./emsdk update./emsdk install latest-upstream./emsdk activate latest-upstreamsource ./emsdk_env.sh
-
You should build wasm version of
opencv.js
if you want to enable this optimization. For browser, you need to enable theWebAssembly SIMD support
feature first. For example, if you use Chrome, please enable this flag in chrome://flags. For Node.js, you need to run script with flag--experimental-wasm-simd
. -
The simd version of
opencv.js
built by latest LLVM upstream may not work with the stable browser or old version of Node.js. Please use the latest version of unstable browser or Node.js to get new features, likeChrome Dev
.
[optional] To build wasm intrinsics tests, append
--build_wasm_intrin_test
option.For example:
emcmake python ./opencv/platforms/js/build_js.py build_js --build_wasm --simd --build_wasm_intrin_testFor wasm intrinsics tests, you can use the following function to test all the cases:
cv.test_hal_intrin_all()And the failed cases will be logged in the JavaScript debug console.
If you only want to test single data type of wasm intrinsics, you can use the following functions:
cv.test_hal_intrin_uint8()cv.test_hal_intrin_int8()cv.test_hal_intrin_uint16()cv.test_hal_intrin_int16()cv.test_hal_intrin_uint32()cv.test_hal_intrin_int32()cv.test_hal_intrin_uint64()cv.test_hal_intrin_int64()cv.test_hal_intrin_float32()cv.test_hal_intrin_float64()[optional] To build performance tests, append
--build_perf
option.For example:
emcmake python ./opencv/platforms/js/build_js.py build_js --build_perfTo run performance tests, launch a local web server in <build_dir>/bin folder. For example, node http-server which serves on
localhost:8080
.There are some kernels now in the performance test like
cvtColor
,resize
andthreshold
. For example, if you want to testthreshold
, please navigate the web browser tohttp://localhost:8080/perf/perf_imgproc/perf_threshold.html
. You need to input the test parameter like(1920x1080, CV_8UC1, THRESH_BINARY)
, and then click theRun
button to run the case. And if you don't input the parameter, it will run all the cases of this kernel.You can also run tests using Node.js.
For example, run
threshold
with parameter(1920x1080, CV_8UC1, THRESH_BINARY)
:cd bin/perfnpm installnode perf_threshold.js --test_param_filter="(1920x1080, CV_8UC1, THRESH_BINARY)"
Building OpenCV.js with Docker
Alternatively, the same build can be can be accomplished using docker containers which is often easier and more reliable, particularly in non linux systems. You only need to install docker on your system and use a popular container that provides a clean well tested environment for emscripten builds like this, that already has latest versions of all the necessary tools installed.
So, make sure docker is installed in your system and running. The following shell script should work in Linux and MacOS:
In Windows use the following PowerShell command:
- Warning
- The example uses latest version of emscripten. If the build fails you should try a version that is known to work fine which is
2.0.10
using the following command:
In Windows use the following PowerShell command:
Building the documentation with Docker
To build the documentation doxygen
needs to be installed. Create a file named Dockerfile
with the following content:
Then we build the docker image and name it opencv-js-doc
with the following command (that needs to be run only once):
Now run the build command again, this time using the new image and passing --build_doc
: