mirror of
https://github.com/peterbraden/node-opencv.git
synced 2025-12-08 19:45:55 +00:00
Merge branch 'peterbraden-master'
This commit is contained in:
commit
d2a918bedc
70
.travis.yml
70
.travis.yml
@ -1,10 +1,70 @@
|
||||
language: node_js
|
||||
|
||||
node_js:
|
||||
- "0.10"
|
||||
- "0.11"
|
||||
- '0.10'
|
||||
- '0.11'
|
||||
- '0.12'
|
||||
|
||||
compiler: clang
|
||||
|
||||
env:
|
||||
global:
|
||||
- secure: "kCAwXdfcMv4l4ok5lO89ANbKXXwWQpn5/3qupSbhmX2NDIGUxyXze/cs90u9gF5hcT7ebq27ZJPEtu7pRov8MadfQM9BAd4ZZrHcMHWSkA0Iz+nM+m0Urwach6jkp2Iuwx15L2NHSis7f5PUKJcEv4Gnqs8jrCJzHHS7m7dO0Xo="
|
||||
- secure: "lBIk4BhdIkSmJtFUNp93UjDm445i9eF7nKA+oSiLRu+b9i/WeRLiKFI89tehexWeXBlyNhziBN16LrHmx3I86yZfEok9dBMA1JuzYBjrvpjRAflGcqaCFLV3axyyyNQRIh7Q+ziAlg0xg8HL752BpnfXO91g3jfDPjGxcvBb5xQ="
|
||||
|
||||
|
||||
before_install:
|
||||
# Fix a problem with apt-get failing later, see http://docs.travis-ci.com/user/installing-dependencies/#Installing-Ubuntu-packages
|
||||
- sudo apt-get update -qq
|
||||
- sudo add-apt-repository -y ppa:kubuntu-ppa/backports
|
||||
- sudo apt-get update
|
||||
- sudo apt-get install libcv-dev
|
||||
- sudo apt-get install libopencv-dev
|
||||
- sudo apt-get install libhighgui-dev
|
||||
- sudo apt-get install --force-yes libcv-dev libcvaux-dev libhighgui-dev libopencv-dev
|
||||
# get commit message
|
||||
- COMMIT_MESSAGE=$(git show -s --format=%B $TRAVIS_COMMIT | tr -d '\n')
|
||||
# put local node-pre-gyp on PATH
|
||||
- export PATH=./node_modules/.bin/:$PATH
|
||||
# install node-pre-gyp so it is available for packaging and publishing
|
||||
- npm install node-gyp -g
|
||||
# install node-pre-gyp so it is available for packaging and publishing
|
||||
- npm install node-pre-gyp
|
||||
# install aws-sdk so it is available for publishing to AS3
|
||||
- npm install aws-sdk
|
||||
# figure out if we should publish
|
||||
- PUBLISH_BINARY=false
|
||||
# if we are building a tag then publish
|
||||
- if [[ $TRAVIS_BRANCH == `git describe --tags --always HEAD` ]]; then PUBLISH_BINARY=true; fi;
|
||||
# or if we put [publish binary] in the commit message
|
||||
- if test "${COMMIT_MESSAGE#*'[publish binary]'}" != "$COMMIT_MESSAGE"; then PUBLISH_BINARY=true; fi;
|
||||
- platform=$(uname -s | sed "y/ABCDEFGHIJKLMNOPQRSTUVWXYZ/abcdefghijklmnopqrstuvwxyz/")
|
||||
|
||||
install:
|
||||
# ensure source install works
|
||||
- npm install --build-from-source
|
||||
# test our module
|
||||
- npm test
|
||||
- node lib/opencv.js
|
||||
|
||||
before_script:
|
||||
- echo "Publishing native platform Binary Package? ->" $PUBLISH_BINARY
|
||||
# if publishing, do it
|
||||
- if [[ $PUBLISH_BINARY == true ]]; then node-pre-gyp package publish || true; fi;
|
||||
# cleanup
|
||||
- node-pre-gyp clean
|
||||
- node-gyp clean
|
||||
- sudo apt-get purge libcv-dev
|
||||
- sudo apt-get purge libopencv-dev
|
||||
- sudo apt-get purge libhighgui-dev
|
||||
|
||||
script:
|
||||
# if publishing, test installing from remote
|
||||
- INSTALL_RESULT=0
|
||||
- if [[ $PUBLISH_BINARY == true ]]; then INSTALL_RESULT=$(npm install --fallback-to-build=false > /dev/null)$? || true; fi;
|
||||
# if install returned non zero (errored) then we first unpublish and then call false so travis will bail at this line
|
||||
- if [[ $INSTALL_RESULT != 0 ]]; then echo "returned $INSTALL_RESULT";node-pre-gyp unpublish;false; fi
|
||||
# If success then we arrive here so lets clean up
|
||||
- node-pre-gyp clean
|
||||
# Can't compile opencv 32bit in 64 bit env.
|
||||
|
||||
after_success:
|
||||
# if success then query and display all published binaries
|
||||
- node-pre-gyp info
|
||||
|
||||
23
CHANGELOG.md
23
CHANGELOG.md
@ -1,6 +1,29 @@
|
||||
|
||||
# Changelog
|
||||
|
||||
### 3.0.0
|
||||
|
||||
You wait ages for a release, and 2 come along at once...
|
||||
|
||||
This one is awesome. It adds prebuilt binaries, so you don't need
|
||||
to build opencv for the common platforms.
|
||||
|
||||
Many many thanks to @edgarsilva for awesome work here, and
|
||||
http://hybridgroup.com/ for hosting the binaries
|
||||
|
||||
|
||||
### 2.0.0
|
||||
|
||||
- Support for node 0.12
|
||||
- Camera Calibration Functions from @queuecumber
|
||||
- Fix for Nan 1.5.1 from @IMGNRY
|
||||
- More build fixes from @scanlime
|
||||
- Matrix crop prototype from @dbpieter
|
||||
- Many fixes from @madshall
|
||||
|
||||
Thanks to everyone that contributed!
|
||||
|
||||
|
||||
### 1.0.0
|
||||
|
||||
Ok, let's do a proper semver release :)
|
||||
|
||||
34
Makefile
Normal file
34
Makefile
Normal file
@ -0,0 +1,34 @@
|
||||
VERSION := $(shell node -e "console.log(require('./package.json').version)")
|
||||
|
||||
.PHONY: default release smoke
|
||||
|
||||
test:
|
||||
npm test
|
||||
|
||||
smoke:
|
||||
npm install --build-from-source
|
||||
node smoke/smoketest.js
|
||||
npm test
|
||||
|
||||
|
||||
release:
|
||||
@echo "Tagging release $(VERSION)"
|
||||
@git tag -m "$(VERSION)" v$(VERSION)
|
||||
|
||||
@echo "Pushing tags to GitHub"
|
||||
@git push --tags
|
||||
|
||||
@echo "Switching to osx-binaries branch"
|
||||
@git checkout osx-binaries
|
||||
|
||||
@echo "Merging master into osx-binaries"
|
||||
@git merge --no-ff --commit -m "Merge master into osx-binaries [publish binary]" master
|
||||
|
||||
@echo "Pushing osx-binaries"
|
||||
@git push
|
||||
|
||||
@echo "Switching to master branch"
|
||||
@git checkout master
|
||||
|
||||
@echo "Publishing to NPM"
|
||||
@npm publish
|
||||
13
README.md
13
README.md
@ -22,6 +22,7 @@ $ npm install opencv
|
||||
```
|
||||
|
||||
## Examples
|
||||
Run the examples from the parent directory.
|
||||
|
||||
### Face Detection
|
||||
|
||||
@ -172,29 +173,29 @@ See [relevant source code](src/Contours.cc) and [examples](examples/)
|
||||
```javascript
|
||||
var contours = im.findContours;
|
||||
|
||||
# Count of contours in the Contours object
|
||||
// Count of contours in the Contours object
|
||||
contours.size();
|
||||
|
||||
# Count of corners(verticies) of contour `index`
|
||||
// Count of corners(verticies) of contour `index`
|
||||
contours.cornerCount(index);
|
||||
|
||||
# Access vertex data of contours
|
||||
// Access vertex data of contours
|
||||
for(var c = 0; c < contours.size(); ++c) {
|
||||
console.log("Contour " + c);
|
||||
for(var i = 0; i < contours.cornerCount(c); ++i) {
|
||||
var point = contours.point(c, i);
|
||||
console.log("(" + point.x + "," + point.y + ")");"
|
||||
console.log("(" + point.x + "," + point.y + ")");
|
||||
}
|
||||
}
|
||||
|
||||
# Computations of contour `index`
|
||||
// Computations of contour `index`
|
||||
contours.area(index);
|
||||
contours.arcLength(index, isClosed);
|
||||
contours.boundingRect(index);
|
||||
contours.minAreaRect(index);
|
||||
contours.isConvex(index);
|
||||
|
||||
# Destructively alter contour `index`
|
||||
// Destructively alter contour `index`
|
||||
contours.approxPolyDP(index, epsilon, isClosed);
|
||||
contours.convexHull(index, clockwise);
|
||||
```
|
||||
|
||||
105
appveyor.yml
Normal file
105
appveyor.yml
Normal file
@ -0,0 +1,105 @@
|
||||
# environment variables
|
||||
environment:
|
||||
node_pre_gyp_accessKeyId:
|
||||
secure: 3GHZvq0y83PQ8Qi7FOc5rKoULRQvd2OohhtGqRQLZB4=
|
||||
node_pre_gyp_secretAccessKey:
|
||||
secure: AiX8Bx+U8LKu5JZHb5CMth5xOHuWawkQW3il0OFWfV4kodPZnC8dLYIqb4XZeF7f
|
||||
|
||||
# try on unstable version of the server to build node-opencv
|
||||
os: unstable
|
||||
|
||||
# to add several platforms to build matrix:
|
||||
platform:
|
||||
- x64
|
||||
|
||||
install:
|
||||
- cmd: ECHO "INSTALL OPENCV:"
|
||||
- cmd: choco install OpenCV
|
||||
- cmd: ECHO "APPVEYOR_REPO_COMMIT_MESSAGE ->"
|
||||
- cmd: ECHO %APPVEYOR_REPO_COMMIT_MESSAGE%
|
||||
- cmd: SET COMMIT_MSG="%APPVEYOR_REPO_COMMIT_MESSAGE%"
|
||||
- cmd: SET PUBLISH_BINARY=false
|
||||
# Check to verify the branch is the same than latest tag, if so
|
||||
# then we publish the binaries if everything else is successful.
|
||||
- cmd: git describe --tags --always HEAD > _git_tag.tmp
|
||||
- cmd: SET /p GIT_TAG=<_git_tag.tmp
|
||||
- cmd: ECHO "LATEST LOCAL TAG:"
|
||||
- cmd: ECHO %GIT_TAG%
|
||||
- cmd: ECHO "APPVEYOR REPO BRANCH/TAG:"
|
||||
- cmd: ECHO %APPVEYOR_REPO_BRANCH%
|
||||
- cmd: DEL _git_tag.tmp
|
||||
- cmd: IF x%APPVEYOR_REPO_BRANCH%==x%GIT_TAG% SET PUBLISH_BINARY=true
|
||||
# Or look for commit message containing `[publish binary]`
|
||||
- cmd: IF not x%COMMIT_MSG:[publish binary]=%==x%COMMIT_MSG% SET PUBLISH_BINARY=true
|
||||
- cmd: ECHO "Env Var PUBLISH_BINARY:"
|
||||
- cmd: ECHO %PUBLISH_BINARY%
|
||||
- cmd: git clone https://github.com/marcelklehr/nodist.git c:\nodist 2>&1
|
||||
- cmd: SET PATH=C:\nodist\bin;%PATH%
|
||||
- cmd: SET NODIST_PREFIX=C:\nodist
|
||||
|
||||
before_build:
|
||||
- cmd: SET ARCH=x64
|
||||
- cmd: SET NODIST_X64=1
|
||||
- cmd: call nodist update
|
||||
- cmd: call nodist stable
|
||||
- cmd: npm install -g node-gyp
|
||||
- cmd: SET APP_PATH=%CD%
|
||||
- cmd: IF EXIST C:\OpenCV* CD C:\OpenCV*
|
||||
- cmd: SET OPENCV_ROOT_PATH=%CD%\opencv
|
||||
- cmd: CD %APP_PATH%
|
||||
- cmd: SET OPENCV_DIR=%OPENCV_ROOT_PATH%\build\%ARCH%\vc12\bin
|
||||
- cmd: SET PATH=%cd%\node_modules\.bin\;C:\MinGW\bin;C:\GTK\bin;C:\msys\1.0\bin;%OPENCV_DIR%;%PATH%
|
||||
- cmd: SET PKG_CONFIG_PATH=C:\GTK\lib\pkgconfig
|
||||
- cmd: DIR %OPENCV_ROOT_PATH%\build\%ARCH%\vc12\bin
|
||||
- cmd: DIR %OPENCV_ROOT_PATH%\build\%ARCH%\vc12\lib
|
||||
# Here we need to copy the opencv.pc file from the repo into PKG_CONFIG_PATH
|
||||
# trick part is to check for the vc12 folder and use that one
|
||||
- cmd: copy .\utils\opencv_x64.pc C:\GTK\lib\pkgconfig\opencv.pc
|
||||
|
||||
# to run your custom scripts instead of automatic MSBuild
|
||||
build_script:
|
||||
- cmd: ECHO "BUILDING x64 binary package:"
|
||||
- cmd: npm install --build-from-source --msvs_version=2013
|
||||
- cmd: npm test
|
||||
- cmd: node lib/opencv.js
|
||||
- cmd: ECHO "PUBLISH x64 binary package:"
|
||||
- cmd: npm install aws-sdk
|
||||
- cmd: IF %PUBLISH_BINARY%==true (node-pre-gyp package publish 2>&1)
|
||||
- cmd: node-pre-gyp clean
|
||||
- cmd: node-gyp clean
|
||||
- cmd: npm uninstall -g node-gyp
|
||||
- cmd: rmdir /q /s node_modules
|
||||
- cmd: DEL C:\GTK\lib\pkgconfig\opencv.pc
|
||||
|
||||
after_build:
|
||||
- cmd: SET ARCH=x86
|
||||
- cmd: SET OPENCV_DIR=%OPENCV_ROOT_PATH%\build\%ARCH%\vc12\bin
|
||||
- cmd: SET PATH=%OPENCV_DIR%;%PATH%
|
||||
- cmd: SET NODIST_X64=0
|
||||
- cmd: call nodist update
|
||||
- cmd: call nodist stable
|
||||
- cmd: npm install -g node-gyp
|
||||
- cmd: copy .\utils\opencv_x86.pc C:\GTK\lib\pkgconfig\opencv.pc
|
||||
- cmd: ECHO "BUILDING x86 binary package:"
|
||||
- cmd: npm install --build-from-source --msvs_version=2013
|
||||
- cmd: npm test
|
||||
- cmd: node lib/opencv.js
|
||||
- cmd: ECHO "PUBLISH x86 binary package:"
|
||||
- cmd: npm install aws-sdk
|
||||
- cmd: IF %PUBLISH_BINARY%==true (node-pre-gyp package publish 2>&1)
|
||||
- cmd: node-pre-gyp clean
|
||||
- cmd: node-gyp clean
|
||||
- cmd: rmdir /q /s node_modules
|
||||
|
||||
on_success:
|
||||
# test installing from binary package works
|
||||
- cmd: ECHO "ON SUCCESS:"
|
||||
- cmd: ECHO "Try installing from binary:"
|
||||
#- cmd: IF %PUBLISH_BINARY%==true npm install --fallback-to-build=false
|
||||
- cmd: npm install --fallback-to-build=false
|
||||
# Print Available Binaries
|
||||
- cmd: node-pre-gyp info
|
||||
|
||||
test: OFF
|
||||
|
||||
deploy: OFF
|
||||
111
binding.gyp
111
binding.gyp
@ -1,51 +1,80 @@
|
||||
{
|
||||
"targets": [{
|
||||
"target_name": "opencv"
|
||||
, "sources": [
|
||||
"src/init.cc"
|
||||
, "src/Matrix.cc"
|
||||
, "src/OpenCV.cc"
|
||||
, "src/CascadeClassifierWrap.cc"
|
||||
, "src/Contours.cc"
|
||||
, "src/Point.cc"
|
||||
, "src/VideoCaptureWrap.cc"
|
||||
, "src/CamShift.cc"
|
||||
, "src/HighGUI.cc"
|
||||
, "src/FaceRecognizer.cc"
|
||||
, "src/BackgroundSubtractor.cc"
|
||||
, "src/Constants.cc"
|
||||
]
|
||||
, 'libraries': [
|
||||
'<!@(pkg-config --libs opencv)'
|
||||
]
|
||||
"target_name": "opencv",
|
||||
"sources": [
|
||||
"src/init.cc",
|
||||
"src/Matrix.cc",
|
||||
"src/OpenCV.cc",
|
||||
"src/CascadeClassifierWrap.cc",
|
||||
"src/Contours.cc",
|
||||
"src/Point.cc",
|
||||
"src/VideoCaptureWrap.cc",
|
||||
"src/CamShift.cc",
|
||||
"src/HighGUI.cc",
|
||||
"src/FaceRecognizer.cc",
|
||||
"src/BackgroundSubtractor.cc",
|
||||
"src/Constants.cc",
|
||||
"src/Calib3D.cc",
|
||||
"src/ImgProc.cc",
|
||||
"src/Stereo.cc"
|
||||
],
|
||||
|
||||
"libraries": [
|
||||
"<!@(pkg-config --libs opencv)"
|
||||
],
|
||||
# For windows
|
||||
,'include_dirs': [
|
||||
'<!@(pkg-config --cflags opencv)',
|
||||
"<!(node -e \"require('nan')\")"
|
||||
]
|
||||
|
||||
, 'cflags': [
|
||||
'<!@(pkg-config --cflags "opencv >= 2.3.1" )'
|
||||
, '-Wall'
|
||||
]
|
||||
, 'cflags!' : [ '-fno-exceptions']
|
||||
, 'cflags_cc!': [ '-fno-rtti', '-fno-exceptions']
|
||||
, "conditions": [
|
||||
['OS=="mac"', {
|
||||
# cflags on OS X are stupid and have to be defined like this
|
||||
'xcode_settings': {
|
||||
'OTHER_CFLAGS': [
|
||||
"-mmacosx-version-min=10.7",
|
||||
"-std=c++11",
|
||||
"-stdlib=libc++",
|
||||
'<!@(pkg-config --cflags opencv)'
|
||||
"include_dirs": [
|
||||
"<!@(pkg-config --cflags opencv)",
|
||||
"<!(node -e \"require('nan')\")"
|
||||
],
|
||||
|
||||
"cflags!" : [ "-fno-exceptions"],
|
||||
"cflags_cc!": [ "-fno-rtti", "-fno-exceptions"],
|
||||
|
||||
"conditions": [
|
||||
[ "OS==\"linux\"", {
|
||||
"cflags": [
|
||||
"<!@(pkg-config --cflags \"opencv >= 2.3.1\" )",
|
||||
"-Wall"
|
||||
]
|
||||
, "GCC_ENABLE_CPP_RTTI": "YES"
|
||||
, "GCC_ENABLE_CPP_EXCEPTIONS": "YES"
|
||||
}],
|
||||
[ "OS==\"win\"", {
|
||||
"cflags": [
|
||||
"<!@(pkg-config --cflags \"opencv >= 2.4.9\" )",
|
||||
"-Wall"
|
||||
],
|
||||
"msvs_settings": {
|
||||
"VCCLCompilerTool": {
|
||||
"ExceptionHandling": "2",
|
||||
"DisableSpecificWarnings": [ "4530", "4506", "4244" ],
|
||||
},
|
||||
}
|
||||
}],
|
||||
[ # cflags on OS X are stupid and have to be defined like this
|
||||
"OS==\"mac\"", {
|
||||
"xcode_settings": {
|
||||
"OTHER_CFLAGS": [
|
||||
"-mmacosx-version-min=10.7",
|
||||
"-std=c++11",
|
||||
"-stdlib=libc++",
|
||||
"<!@(pkg-config --cflags opencv)"
|
||||
],
|
||||
"GCC_ENABLE_CPP_RTTI": "YES",
|
||||
"GCC_ENABLE_CPP_EXCEPTIONS": "YES"
|
||||
}
|
||||
}]
|
||||
|
||||
]
|
||||
}]
|
||||
},
|
||||
{
|
||||
"target_name": "action_after_build",
|
||||
"type": "none",
|
||||
"dependencies": [ "<(module_name)" ],
|
||||
"copies": [
|
||||
{
|
||||
"files": [ "<(PRODUCT_DIR)/<(module_name).node" ],
|
||||
"destination": "<(module_path)"
|
||||
}
|
||||
]
|
||||
}]
|
||||
}
|
||||
|
||||
@ -1,6 +1,6 @@
|
||||
<?xml version="1.0"?>
|
||||
<opencv_storage>
|
||||
<cascade>
|
||||
<output type_id="opencv-haar-classifier">
|
||||
<stageType>BOOST</stageType>
|
||||
<featureType>HOG</featureType>
|
||||
<height>24</height>
|
||||
@ -835,5 +835,7 @@
|
||||
16 8 16 8 24</rect></_>
|
||||
<_>
|
||||
<rect>
|
||||
16 8 16 8 28</rect></_></features></cascade>
|
||||
16 8 16 8 28</rect></_></features>
|
||||
|
||||
</output>
|
||||
</opencv_storage>
|
||||
|
||||
@ -1,14 +1,14 @@
|
||||
var cv = require('../lib/opencv');
|
||||
|
||||
cv.readImage("./files/mona.png", function(err, orig) {
|
||||
cv.readImage("./examples/files/mona.png", function(err, orig) {
|
||||
if (err) throw err;
|
||||
|
||||
cv.readImage("./files/over_text.png", function(err, over_text) {
|
||||
cv.readImage("./examples/files/over_text.png", function(err, over_text) {
|
||||
if (err) throw err;
|
||||
|
||||
var result = new cv.Matrix(orig.width(), orig.height());
|
||||
result.addWeighted(orig, 0.7, over_text, 0.9);
|
||||
result.save("./tmp/weighted.png");
|
||||
console.log('Image saved to ./tmp/weighted.png');
|
||||
result.save("./examples/tmp/weighted.png");
|
||||
console.log('Image saved to ./examples/tmp/weighted.png');
|
||||
});
|
||||
});
|
||||
|
||||
@ -1,12 +1,20 @@
|
||||
var cv = require('../lib/opencv');
|
||||
|
||||
var camera = new cv.VideoCapture(0);
|
||||
var window = new cv.NamedWindow('Video', 0)
|
||||
|
||||
setInterval(function() {
|
||||
camera.read(function(err, im) {
|
||||
if (err) throw err;
|
||||
window.show(im);
|
||||
window.blockingWaitKey(0, 50);
|
||||
});
|
||||
}, 20);
|
||||
try {
|
||||
var camera = new cv.VideoCapture(0);
|
||||
var window = new cv.NamedWindow('Video', 0)
|
||||
/*
|
||||
setInterval(function() {
|
||||
camera.read(function(err, im) {
|
||||
if (err) throw err;
|
||||
console.log(im.size())
|
||||
if (im.size()[0] > 0 && im.size()[1] > 0){
|
||||
window.show(im);
|
||||
}
|
||||
window.blockingWaitKey(0, 50);
|
||||
});
|
||||
}, 20);
|
||||
*/
|
||||
} catch (e){
|
||||
console.log("Couldn't start camera:", e)
|
||||
}
|
||||
|
||||
@ -1,3 +1,6 @@
|
||||
/* For some reason the cascade file is broken on linux :(
|
||||
|
||||
|
||||
var cv = require('../lib/opencv');
|
||||
|
||||
cv.readImage("./files/car1.jpg", function(err, im){
|
||||
@ -16,3 +19,4 @@ cv.readImage("./files/car1.jpg", function(err, im){
|
||||
console.log('Image saved to ./tmp/car-detection.jpg');
|
||||
});
|
||||
});
|
||||
*/
|
||||
|
||||
@ -3,7 +3,7 @@ var http = require('http'),
|
||||
request = require('request'),
|
||||
cv = require('../lib/opencv');
|
||||
|
||||
http.createServer(function(req, resp){
|
||||
var server = http.createServer(function(req, resp){
|
||||
var url = req.url.slice(1);
|
||||
request({uri:url, encoding:'binary'}, function(err, r, body){
|
||||
if (err) return resp.end(err.stack);
|
||||
@ -27,4 +27,7 @@ http.createServer(function(req, resp){
|
||||
});
|
||||
});
|
||||
|
||||
}).listen(3000, function(){ console.log('Listening on http://localhost:3000'); })
|
||||
})
|
||||
|
||||
|
||||
//server.listen(3000, function(){ console.log('Listening on http://localhost:3000'); })
|
||||
|
||||
@ -1,7 +1,7 @@
|
||||
var cv = require('../lib/opencv');
|
||||
|
||||
cv.readImage("./files/mona.png", function(err, im) {
|
||||
salt(im, 1000);
|
||||
salt(im, 100);
|
||||
im.save("./tmp/salt.png");
|
||||
console.log('Image saved to ./tmp/salt.png');
|
||||
});
|
||||
|
||||
@ -1,24 +1,32 @@
|
||||
var cv = require('../lib/opencv');
|
||||
var vid = new cv.VideoCapture(0);
|
||||
try {
|
||||
var vid = new cv.VideoCapture(0);
|
||||
|
||||
vid.read(function(err, im){
|
||||
if (err) throw err;
|
||||
|
||||
im.detectObject(cv.FACE_CASCADE, {}, function(err, faces){
|
||||
vid.read(function(err, im){
|
||||
if (err) throw err;
|
||||
if (!faces.length) return console.log("No Faces");
|
||||
if (im.size()[0] > 0 && im.size()[1] > 0){
|
||||
|
||||
var face = faces[0];
|
||||
var ims = im.size();
|
||||
var im2 = im.roi(face.x, face.y, face.width, face.height)
|
||||
/*
|
||||
im.adjustROI(
|
||||
-face.y
|
||||
, (face.y + face.height) - ims[0]
|
||||
, -face.x
|
||||
, (face.x + face.width) - ims[1])
|
||||
*/
|
||||
im2.save('./tmp/take-face-pics.jpg')
|
||||
console.log('Image saved to ./tmp/take-face-pics.jpg');
|
||||
})
|
||||
});
|
||||
im.detectObject(cv.FACE_CASCADE, {}, function(err, faces){
|
||||
if (err) throw err;
|
||||
if (!faces.length) return console.log("No Faces");
|
||||
|
||||
var face = faces[0];
|
||||
var ims = im.size();
|
||||
var im2 = im.roi(face.x, face.y, face.width, face.height)
|
||||
/*
|
||||
im.adjustROI(
|
||||
-face.y
|
||||
, (face.y + face.height) - ims[0]
|
||||
, -face.x
|
||||
, (face.x + face.width) - ims[1])
|
||||
*/
|
||||
im2.save('./examples/tmp/take-face-pics.jpg')
|
||||
console.log('Image saved to ./tmp/take-face-pics.jpg');
|
||||
})
|
||||
} else {
|
||||
console.log("Camera didn't return image")
|
||||
}
|
||||
});
|
||||
} catch (e){
|
||||
console.log("Couldn't start camera", e)
|
||||
}
|
||||
|
||||
@ -1,6 +1,6 @@
|
||||
var cv = require('../lib/opencv');
|
||||
|
||||
cv.readImage("./mona.png", function(err, im) {
|
||||
cv.readImage("./files/mona.png", function(err, im) {
|
||||
if (err) throw err;
|
||||
|
||||
var width = im.width();
|
||||
@ -11,6 +11,6 @@ cv.readImage("./mona.png", function(err, im) {
|
||||
var dstArray = [0, 0, width * 0.9, height * 0.1, width, height, width * 0.2, height * 0.8];
|
||||
var xfrmMat = im.getPerspectiveTransform(srcArray, dstArray);
|
||||
im.warpPerspective(xfrmMat, width, height, [255, 255, 255]);
|
||||
im.save("./warp-image.png");
|
||||
im.save("./tmp/warp-image.png");
|
||||
console.log('Image saved to ./tmp/warp-image.png');
|
||||
});
|
||||
|
||||
@ -1 +1,7 @@
|
||||
module.exports = require('../build/Release/opencv.node');
|
||||
var binary = require('node-pre-gyp');
|
||||
var path = require('path');
|
||||
var binding_path = binary.find(path.resolve(path.join(__dirname,'../package.json')));
|
||||
var binding = require(binding_path);
|
||||
|
||||
//module.exports = require('../build/Release/opencv.node');
|
||||
module.exports = binding;
|
||||
|
||||
21
package.json
21
package.json
@ -3,17 +3,23 @@
|
||||
"description": "Node Bindings to OpenCV",
|
||||
"author": "Peter Braden <peterbraden@peterbraden.co.uk>",
|
||||
"dependencies": {
|
||||
"node-pre-gyp": "0.5.31",
|
||||
"buffers": "0.1.1",
|
||||
"nan": "^1.3.0"
|
||||
"nan": "1.4.3"
|
||||
},
|
||||
"version": "1.0.0",
|
||||
"version": "3.0.1",
|
||||
"devDependencies": {
|
||||
"tape": "^3.0.0"
|
||||
"tape": "^3.0.0",
|
||||
"aws-sdk": "~2.0.21",
|
||||
"glob": "^4.0.6",
|
||||
"request": "^2.45.0"
|
||||
},
|
||||
"bundledDependencies":["node-pre-gyp"],
|
||||
"license": "MIT",
|
||||
"scripts": {
|
||||
"build": "node-gyp build",
|
||||
"test": "node test/unit.js"
|
||||
"test": "node test/unit.js",
|
||||
"install": "node-pre-gyp install --fallback-to-build"
|
||||
},
|
||||
"keywords": [
|
||||
"opencv",
|
||||
@ -28,5 +34,12 @@
|
||||
},
|
||||
"engines": {
|
||||
"node": ">=0.10"
|
||||
},
|
||||
"binary": {
|
||||
"module_name" : "opencv",
|
||||
"module_path" : "./build/{module_name}/v{version}/{configuration}/{node_abi}-{platform}-{arch}/",
|
||||
"remote_path" : "./{module_name}/v{version}/{configuration}/",
|
||||
"package_name": "{node_abi}-{platform}-{arch}.tar.gz",
|
||||
"host" : "https://node-opencv.s3.amazonaws.com"
|
||||
}
|
||||
}
|
||||
|
||||
71
publish-binaries.md
Normal file
71
publish-binaries.md
Normal file
@ -0,0 +1,71 @@
|
||||
How to publish the pre compiled binaries.
|
||||
=========================================
|
||||
|
||||
## Setup for Linux, Windows and OSX
|
||||
|
||||
Every time a new tag for the latest release is pushed to github the continous integration
|
||||
builds in Travis-CI and AppVeyor will generate the binaries for each platform and architecture,
|
||||
package and publish to the AS3 bucket.
|
||||
|
||||
This can be checked in the .travis.yml file and appveyor.yml file. Within the files there are two
|
||||
methods for publishing new binaries for each version, one is if a `git tag` is detected; the other
|
||||
can be triggered by passing the string `[publish binary]` in the commit message itself.
|
||||
|
||||
We also have an automated make task, we should always use this task to avoid forgetting any steps
|
||||
(like merging into the `osx-binaries` branch).
|
||||
|
||||
The process for generating the binaries, publishing and releasing the npm module should be as follows:
|
||||
|
||||
1. Merge all changes and new features into master.
|
||||
2. Bump up version of npm module in `package.json`.
|
||||
3. execute make task: `make release`
|
||||
|
||||
This task will do the following for you:
|
||||
|
||||
1. Generate new tags based on package.json version number
|
||||
2. Push tags to Github
|
||||
3. Checkout into `osx-binaries` branch
|
||||
4. Merge `master` into `osx-binaries`
|
||||
5. Push `osx-binaries`
|
||||
6. Checkout master
|
||||
7. Finally it will run `npm publish`
|
||||
|
||||
With this we will make sure the binaries for all platforms and architectures will be generated each time
|
||||
a new version is released.
|
||||
|
||||
|
||||
## Config Travis, AppVeyor and Github to generate all of the binaries.
|
||||
|
||||
Before we are able to run everything stated above some steps need to be taken.
|
||||
Specifically for being able to publish the pre compiled binaries to AWS-S3. The
|
||||
correct keys need to be setup in the travis and appveyor `.yml` files. This needs
|
||||
to be done by the admin of the repo, in the case of Travis, and the owner of the account,
|
||||
in the case of appveyor.
|
||||
|
||||
### Setting up secure keys in Travis.
|
||||
|
||||
Setting up the keys in Travis is easy if you have ruby and ruby gems installed and working then install:
|
||||
|
||||
`gem install travis`
|
||||
|
||||
After the travis gem is installed run the following command for each of the required keys:
|
||||
|
||||
`travis encrypt SOMEVAR=secretvalue`
|
||||
|
||||
And substitute the values in the `.travis.yml` file for the new ones. Detailed instructions can
|
||||
be found here: http://docs.travis-ci.com/user/environment-variables/#Secure-Variables
|
||||
|
||||
### Setting up secure keys in AppVeyor
|
||||
|
||||
It is even easier than Travis, you do not need to install anything, just go to your account and
|
||||
click in `encrypt tool`, there enter the values in the input field and click encrypt. Same as with
|
||||
Travis we then need to substitute the newly generated values for the old ones.
|
||||
|
||||
Detailed instructions can be found here: http://www.appveyor.com/docs/build-configuration#secure-variables
|
||||
|
||||
### OSX binaries
|
||||
|
||||
Since Travis does not support config file for multiple OSs we need to create a new branch that contains
|
||||
a slightly different version of the .travis.yml file to compile for OSX. The branch needs to be called
|
||||
`osx-binaries` and be based of `master` once the pre-compiled binaries PR has been merged in.
|
||||
|
||||
@ -1,14 +0,0 @@
|
||||
#!/bin/bash
|
||||
|
||||
if [ ! -f smoke/smoketest.js ]; then
|
||||
echo "Please run smoke test from the top-level folder of the repository." >&2
|
||||
exit 1
|
||||
fi
|
||||
|
||||
node-gyp build && echo '-- Compiled OK --
|
||||
|
||||
' && node smoke/smoketest.js && echo '-- Smoke Done, running tests --
|
||||
|
||||
' && npm test # && echo '-- Tests Run, runnning examples --
|
||||
#(building example data)
|
||||
#' && ./examples/make-example-files.sh && node examples/motion-track.js
|
||||
@ -1,6 +1,6 @@
|
||||
var cv = require('../lib/opencv')
|
||||
var cv = require('../lib/opencv');
|
||||
|
||||
var trainingData = []
|
||||
var trainingData = [];
|
||||
/*
|
||||
for (var i = 1; i< 41; i++){
|
||||
for (var j = 1; j<10; j++){
|
||||
@ -22,5 +22,5 @@ cv.readImage("/Users/peterbraden/Downloads/orl_faces/s6/10.pgm", function(e, im)
|
||||
*/
|
||||
cv.readImage("./examples/files/mona.png", function(e, mat){
|
||||
var th = mat.threshold(200, 200, "Threshold to Zero Inverted");
|
||||
th.save('./examples/tmp/out.png')
|
||||
})
|
||||
th.save('./examples/tmp/out.png');
|
||||
});
|
||||
|
||||
@ -42,17 +42,17 @@ NAN_METHOD(BackgroundSubtractorWrap::New) {
|
||||
NAN_METHOD(BackgroundSubtractorWrap::CreateMOG) {
|
||||
NanScope();
|
||||
|
||||
int history = 200;
|
||||
int nmixtures = 5;
|
||||
double backgroundRatio = 0.7;
|
||||
double noiseSigma = 0;
|
||||
|
||||
if(args.Length() > 1){
|
||||
INT_FROM_ARGS(history, 0)
|
||||
INT_FROM_ARGS(nmixtures, 1)
|
||||
DOUBLE_FROM_ARGS(backgroundRatio, 2)
|
||||
DOUBLE_FROM_ARGS(noiseSigma, 3)
|
||||
}
|
||||
// int history = 200;
|
||||
// int nmixtures = 5;
|
||||
// double backgroundRatio = 0.7;
|
||||
// double noiseSigma = 0;
|
||||
//
|
||||
// if(args.Length() > 1){
|
||||
// INT_FROM_ARGS(history, 0)
|
||||
// INT_FROM_ARGS(nmixtures, 1)
|
||||
// DOUBLE_FROM_ARGS(backgroundRatio, 2)
|
||||
// DOUBLE_FROM_ARGS(noiseSigma, 3)
|
||||
// }
|
||||
|
||||
Local<Object> n = NanNew(BackgroundSubtractorWrap::constructor)->GetFunction()->NewInstance();
|
||||
|
||||
@ -136,3 +136,4 @@ BackgroundSubtractorWrap::BackgroundSubtractorWrap(cv::Ptr<cv::BackgroundSubtrac
|
||||
};
|
||||
|
||||
#endif
|
||||
|
||||
|
||||
589
src/Calib3D.cc
Normal file
589
src/Calib3D.cc
Normal file
@ -0,0 +1,589 @@
|
||||
#include "Calib3D.h"
|
||||
#include "Matrix.h"
|
||||
|
||||
inline Local<Object> matrixFromMat(cv::Mat &input)
|
||||
{
|
||||
Local<Object> matrixWrap = NanNew(Matrix::constructor)->GetFunction()->NewInstance();
|
||||
Matrix *matrix = ObjectWrap::Unwrap<Matrix>(matrixWrap);
|
||||
matrix->mat = input;
|
||||
|
||||
return matrixWrap;
|
||||
}
|
||||
|
||||
inline cv::Mat matFromMatrix(Handle<Value> matrix)
|
||||
{
|
||||
Matrix* m = ObjectWrap::Unwrap<Matrix>(matrix->ToObject());
|
||||
return m->mat;
|
||||
}
|
||||
|
||||
inline cv::Size sizeFromArray(Handle<Value> jsArray)
|
||||
{
|
||||
cv::Size patternSize;
|
||||
|
||||
if (jsArray->IsArray())
|
||||
{
|
||||
Local<Object> v8sz = jsArray->ToObject();
|
||||
|
||||
patternSize = cv::Size(v8sz->Get(0)->IntegerValue(), v8sz->Get(1)->IntegerValue());
|
||||
}
|
||||
else
|
||||
{
|
||||
JSTHROW_TYPE("Size is not a valid array");
|
||||
}
|
||||
|
||||
return patternSize;
|
||||
}
|
||||
|
||||
inline std::vector<cv::Point2f> points2fFromArray(Handle<Value> array)
|
||||
{
|
||||
std::vector<cv::Point2f> points;
|
||||
if(array->IsArray())
|
||||
{
|
||||
Local<Array> pointsArray = Local<Array>::Cast(array->ToObject());
|
||||
|
||||
for(unsigned int i = 0; i < pointsArray->Length(); i++)
|
||||
{
|
||||
Local<Object> pt = pointsArray->Get(i)->ToObject();
|
||||
points.push_back(cv::Point2f(pt->Get(NanNew<String>("x"))->ToNumber()->Value(),
|
||||
pt->Get(NanNew<String>("y"))->ToNumber()->Value()));
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
JSTHROW_TYPE("Points not a valid array");
|
||||
}
|
||||
|
||||
return points;
|
||||
}
|
||||
|
||||
inline std::vector<cv::Point3f> points3fFromArray(Handle<Value> array)
|
||||
{
|
||||
std::vector<cv::Point3f> points;
|
||||
if(array->IsArray()) {
|
||||
Local<Array> pointsArray = Local<Array>::Cast(array->ToObject());
|
||||
|
||||
for(unsigned int i = 0; i < pointsArray->Length(); i++)
|
||||
{
|
||||
Local<Object> pt = pointsArray->Get(i)->ToObject();
|
||||
points.push_back(cv::Point3f(pt->Get(NanNew<String>("x"))->ToNumber()->Value(),
|
||||
pt->Get(NanNew<String>("y"))->ToNumber()->Value(),
|
||||
pt->Get(NanNew<String>("z"))->ToNumber()->Value()));
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
JSTHROW_TYPE("Must pass array of object points for each frame")
|
||||
}
|
||||
|
||||
return points;
|
||||
}
|
||||
|
||||
inline std::vector<std::vector<cv::Point2f> > points2fFromArrayOfArrays(Handle<Value> array)
|
||||
{
|
||||
std::vector<std::vector<cv::Point2f> > points;
|
||||
if(array->IsArray())
|
||||
{
|
||||
Local<Array> pointsArray = Local<Array>::Cast(array->ToObject());
|
||||
|
||||
for(unsigned int i = 0; i < pointsArray->Length(); i++)
|
||||
{
|
||||
points.push_back(points2fFromArray(pointsArray->Get(i)));
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
JSTHROW_TYPE("Must pass array of object points for each frame")
|
||||
}
|
||||
|
||||
return points;
|
||||
}
|
||||
|
||||
inline std::vector<std::vector<cv::Point3f> > points3fFromArrayOfArrays(Handle<Value> array)
|
||||
{
|
||||
std::vector<std::vector<cv::Point3f> > points;
|
||||
if(array->IsArray())
|
||||
{
|
||||
Local<Array> pointsArray = Local<Array>::Cast(array->ToObject());
|
||||
|
||||
for(unsigned int i = 0; i < pointsArray->Length(); i++)
|
||||
{
|
||||
points.push_back(points3fFromArray(pointsArray->Get(i)));
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
JSTHROW_TYPE("Must pass array of object points for each frame")
|
||||
}
|
||||
|
||||
return points;
|
||||
}
|
||||
|
||||
void Calib3D::Init(Handle<Object> target)
|
||||
{
|
||||
Persistent<Object> inner;
|
||||
Local<Object> obj = NanNew<Object>();
|
||||
NanAssignPersistent(inner, obj);
|
||||
|
||||
NODE_SET_METHOD(obj, "findChessboardCorners", FindChessboardCorners);
|
||||
NODE_SET_METHOD(obj, "drawChessboardCorners", DrawChessboardCorners);
|
||||
NODE_SET_METHOD(obj, "calibrateCamera", CalibrateCamera);
|
||||
NODE_SET_METHOD(obj, "solvePnP", SolvePnP);
|
||||
NODE_SET_METHOD(obj, "getOptimalNewCameraMatrix", GetOptimalNewCameraMatrix);
|
||||
NODE_SET_METHOD(obj, "stereoCalibrate", StereoCalibrate);
|
||||
NODE_SET_METHOD(obj, "stereoRectify", StereoRectify);
|
||||
NODE_SET_METHOD(obj, "computeCorrespondEpilines", ComputeCorrespondEpilines);
|
||||
NODE_SET_METHOD(obj, "reprojectImageTo3d", ReprojectImageTo3D);
|
||||
|
||||
target->Set(NanNew("calib3d"), obj);
|
||||
}
|
||||
|
||||
// cv::findChessboardCorners
|
||||
NAN_METHOD(Calib3D::FindChessboardCorners)
|
||||
{
|
||||
NanEscapableScope();
|
||||
|
||||
try {
|
||||
// Get the arguments from javascript
|
||||
|
||||
// Arg 0 is the image
|
||||
cv::Mat mat = matFromMatrix(args[0]);
|
||||
|
||||
// Arg 1 is the pattern size
|
||||
cv::Size patternSize = sizeFromArray(args[1]);
|
||||
|
||||
// Arg 2 would normally be the flags, ignoring this for now and using the default flags
|
||||
|
||||
// Find the corners
|
||||
std::vector<cv::Point2f> corners;
|
||||
bool found = cv::findChessboardCorners(mat, patternSize, corners);
|
||||
|
||||
// Make the return value
|
||||
Local<Object> ret = NanNew<Object>();
|
||||
ret->Set(NanNew<String>("found"), NanNew<Boolean>(found));
|
||||
|
||||
Local<Array> cornersArray = NanNew<Array>(corners.size());
|
||||
for(unsigned int i = 0; i < corners.size(); i++)
|
||||
{
|
||||
Local<Object> point_data = NanNew<Object>();
|
||||
point_data->Set(NanNew<String>("x"), NanNew<Number>(corners[i].x));
|
||||
point_data->Set(NanNew<String>("y"), NanNew<Number>(corners[i].y));
|
||||
|
||||
cornersArray->Set(NanNew<Number>(i), point_data);
|
||||
}
|
||||
|
||||
ret->Set(NanNew<String>("corners"), cornersArray);
|
||||
|
||||
NanReturnValue(ret);
|
||||
|
||||
|
||||
} catch (cv::Exception &e) {
|
||||
const char *err_msg = e.what();
|
||||
NanThrowError(err_msg);
|
||||
NanReturnUndefined();
|
||||
}
|
||||
|
||||
};
|
||||
|
||||
// cv::drawChessboardCorners
|
||||
NAN_METHOD(Calib3D::DrawChessboardCorners)
|
||||
{
|
||||
NanEscapableScope();
|
||||
|
||||
try {
|
||||
// Get the arguments
|
||||
|
||||
// Arg 0 is the image
|
||||
cv::Mat mat = matFromMatrix(args[0]);
|
||||
|
||||
// Arg 1 is the pattern size
|
||||
cv::Size patternSize = sizeFromArray(args[1]);
|
||||
|
||||
// Arg 2 is the corners array
|
||||
std::vector<cv::Point2f> corners = points2fFromArray(args[2]);
|
||||
|
||||
// Arg 3, pattern found boolean
|
||||
bool patternWasFound = args[3]->ToBoolean()->Value();
|
||||
|
||||
// Draw the corners
|
||||
cv::drawChessboardCorners(mat, patternSize, corners, patternWasFound);
|
||||
|
||||
// Return the passed image, now with corners drawn on it
|
||||
NanReturnValue(args[0]);
|
||||
|
||||
} catch (cv::Exception &e) {
|
||||
const char *err_msg = e.what();
|
||||
NanThrowError(err_msg);
|
||||
NanReturnUndefined();
|
||||
}
|
||||
}
|
||||
|
||||
// cv::calibrateCamera
|
||||
NAN_METHOD(Calib3D::CalibrateCamera)
|
||||
{
|
||||
NanEscapableScope();
|
||||
|
||||
try {
|
||||
// Get the arguments
|
||||
|
||||
// Arg 0, the array of object points, an array of arrays
|
||||
std::vector<std::vector<cv::Point3f> > objectPoints = points3fFromArrayOfArrays(args[0]);
|
||||
|
||||
// Arg 1, the image points, another array of arrays
|
||||
std::vector<std::vector<cv::Point2f> > imagePoints = points2fFromArrayOfArrays(args[1]);
|
||||
|
||||
// Arg 2, the image size
|
||||
cv::Size imageSize = sizeFromArray(args[2]);
|
||||
|
||||
// Arg 3, 4, input guesses for the camrea matrix and distortion coefficients, skipping for now
|
||||
cv::Mat K, dist;
|
||||
|
||||
// Arg 5, 6 flags and termination criteria, skipping for now
|
||||
|
||||
// Calibrate the camera
|
||||
std::vector<cv::Mat> rvecs, tvecs;
|
||||
|
||||
double error = cv::calibrateCamera(objectPoints, imagePoints, imageSize, K, dist, rvecs, tvecs);
|
||||
|
||||
// make the return values
|
||||
Local<Object> ret = NanNew<Object>();
|
||||
|
||||
// Reprojection error
|
||||
ret->Set(NanNew<String>("reprojectionError"), NanNew<Number>(error));
|
||||
|
||||
// K
|
||||
Local<Object> KMatrixWrap = matrixFromMat(K);
|
||||
ret->Set(NanNew<String>("K"), KMatrixWrap);
|
||||
|
||||
// dist
|
||||
Local<Object> distMatrixWrap = matrixFromMat(dist);
|
||||
ret->Set(NanNew<String>("distortion"), distMatrixWrap);
|
||||
|
||||
// Per frame R and t, skiping for now
|
||||
|
||||
// Return
|
||||
NanReturnValue(ret);
|
||||
|
||||
} catch (cv::Exception &e) {
|
||||
const char *err_msg = e.what();
|
||||
NanThrowError(err_msg);
|
||||
NanReturnUndefined();
|
||||
}
|
||||
}
|
||||
|
||||
// cv::solvePnP
|
||||
NAN_METHOD(Calib3D::SolvePnP)
|
||||
{
|
||||
NanEscapableScope();
|
||||
|
||||
try {
|
||||
// Get the arguments
|
||||
|
||||
// Arg 0, the array of object points
|
||||
std::vector<cv::Point3f> objectPoints = points3fFromArray(args[0]);
|
||||
|
||||
// Arg 1, the image points
|
||||
std::vector<cv::Point2f> imagePoints = points2fFromArray(args[1]);
|
||||
|
||||
// Arg 2, the camera matrix
|
||||
cv::Mat K = matFromMatrix(args[2]);
|
||||
|
||||
// Arg 3, the distortion coefficients
|
||||
cv::Mat dist = matFromMatrix(args[3]);
|
||||
|
||||
// Arg 4, use extrinsic guess, skipped for now
|
||||
|
||||
// Arg 5, flags, skip for now
|
||||
|
||||
// solve for r and t
|
||||
cv::Mat rvec, tvec;
|
||||
|
||||
cv::solvePnP(objectPoints, imagePoints, K, dist, rvec, tvec);
|
||||
|
||||
// make the return values
|
||||
Local<Object> ret = NanNew<Object>();
|
||||
|
||||
// rvec
|
||||
Local<Object> rMatrixWrap = matrixFromMat(rvec);
|
||||
ret->Set(NanNew<String>("rvec"), rMatrixWrap);
|
||||
|
||||
// tvec
|
||||
Local<Object> tMatrixWrap = matrixFromMat(tvec);
|
||||
ret->Set(NanNew<String>("tvec"), tMatrixWrap);
|
||||
|
||||
// Return
|
||||
NanReturnValue(ret);
|
||||
|
||||
} catch (cv::Exception &e) {
|
||||
const char *err_msg = e.what();
|
||||
NanThrowError(err_msg);
|
||||
NanReturnUndefined();
|
||||
}
|
||||
}
|
||||
|
||||
// cv::getOptimalNewCameraMAtrix
|
||||
NAN_METHOD(Calib3D::GetOptimalNewCameraMatrix)
|
||||
{
|
||||
NanEscapableScope();
|
||||
|
||||
try {
|
||||
// Get the arguments
|
||||
|
||||
// Arg 0 is the original camera matrix
|
||||
cv::Mat Kin = matFromMatrix(args[0]);
|
||||
|
||||
// Arg 1 is the distortion coefficients
|
||||
cv::Mat dist = matFromMatrix(args[1]);
|
||||
|
||||
// Arg 2, the image size
|
||||
cv::Size imageSize = sizeFromArray(args[2]);
|
||||
|
||||
// Arg 3 is the alpha free scaling parameter
|
||||
double alpha = args[3]->ToNumber()->Value();
|
||||
|
||||
// Arg 4, the new image size
|
||||
cv::Size newImageSize = sizeFromArray(args[4]);
|
||||
|
||||
// Arg 5, valid ROI, skip for now
|
||||
// Arg 6, center principal point, skip for now
|
||||
|
||||
// Get the optimal new camera matrix
|
||||
cv::Mat Kout = cv::getOptimalNewCameraMatrix(Kin, dist, imageSize, alpha, newImageSize);
|
||||
|
||||
// Wrap the output K
|
||||
Local<Object> KMatrixWrap = matrixFromMat(Kout);
|
||||
|
||||
// Return the new K matrix
|
||||
NanReturnValue(KMatrixWrap);
|
||||
|
||||
} catch (cv::Exception &e) {
|
||||
const char *err_msg = e.what();
|
||||
NanThrowError(err_msg);
|
||||
NanReturnUndefined();
|
||||
}
|
||||
}
|
||||
|
||||
// cv::stereoCalibrate
|
||||
NAN_METHOD(Calib3D::StereoCalibrate)
|
||||
{
|
||||
NanEscapableScope();
|
||||
|
||||
try {
|
||||
// Get the arguments
|
||||
|
||||
// Arg 0, the array of object points, an array of arrays
|
||||
std::vector<std::vector<cv::Point3f> > objectPoints = points3fFromArrayOfArrays(args[0]);
|
||||
|
||||
// Arg 1, the image points1, another array of arrays
|
||||
std::vector<std::vector<cv::Point2f> > imagePoints1 = points2fFromArrayOfArrays(args[1]);
|
||||
|
||||
// Arg 2, the image points2, another array of arrays =(
|
||||
std::vector<std::vector<cv::Point2f> > imagePoints2 = points2fFromArrayOfArrays(args[2]);
|
||||
|
||||
// Arg 3 is the image size (follows the PYTHON api not the C++ api since all following arguments are optional or outputs)
|
||||
cv::Size imageSize = sizeFromArray(args[3]);
|
||||
|
||||
// Arg 4,5,6,7 is the camera matrix and distortion coefficients (optional but must pass all 4 or none)
|
||||
cv::Mat k1, d1, k2, d2;
|
||||
if(args.Length() >= 8)
|
||||
{
|
||||
k1 = matFromMatrix(args[4]);
|
||||
d1 = matFromMatrix(args[5]);
|
||||
|
||||
k2 = matFromMatrix(args[6]);
|
||||
d2 = matFromMatrix(args[7]);
|
||||
}
|
||||
|
||||
// Last argument is flags, skipping for now
|
||||
|
||||
// Output mats
|
||||
cv::Mat R, t, E, F;
|
||||
|
||||
// Do the stereo calibration
|
||||
cv::stereoCalibrate(objectPoints, imagePoints1, imagePoints2, k1, d1, k2, d2, imageSize, R, t, E, F);
|
||||
|
||||
// make the return value
|
||||
Local<Object> ret = NanNew<Object>();
|
||||
|
||||
// Make the output arguments
|
||||
|
||||
// k1
|
||||
Local<Object> K1MatrixWrap = matrixFromMat(k1);
|
||||
|
||||
// d1
|
||||
Local<Object> d1MatrixWrap = matrixFromMat(d1);
|
||||
|
||||
// k2
|
||||
Local<Object> K2MatrixWrap = matrixFromMat(k2);
|
||||
|
||||
// d2
|
||||
Local<Object> d2MatrixWrap = matrixFromMat(d2);
|
||||
|
||||
// R
|
||||
Local<Object> RMatrixWrap = matrixFromMat(R);
|
||||
|
||||
// t
|
||||
Local<Object> tMatrixWrap = matrixFromMat(t);
|
||||
|
||||
// E
|
||||
Local<Object> EMatrixWrap = matrixFromMat(E);
|
||||
|
||||
// F
|
||||
Local<Object> FMatrixWrap = matrixFromMat(F);
|
||||
|
||||
// Add to return object
|
||||
ret->Set(NanNew<String>("K1"), K1MatrixWrap);
|
||||
ret->Set(NanNew<String>("distortion1"), d1MatrixWrap);
|
||||
ret->Set(NanNew<String>("K2"), K2MatrixWrap);
|
||||
ret->Set(NanNew<String>("distortion2"), d2MatrixWrap);
|
||||
ret->Set(NanNew<String>("R"), RMatrixWrap);
|
||||
ret->Set(NanNew<String>("t"), tMatrixWrap);
|
||||
ret->Set(NanNew<String>("E"), EMatrixWrap);
|
||||
ret->Set(NanNew<String>("F"), FMatrixWrap);
|
||||
|
||||
// Return
|
||||
NanReturnValue(ret);
|
||||
|
||||
} catch (cv::Exception &e) {
|
||||
const char *err_msg = e.what();
|
||||
NanThrowError(err_msg);
|
||||
NanReturnUndefined();
|
||||
}
|
||||
}
|
||||
|
||||
// cv::stereoRectify
|
||||
NAN_METHOD(Calib3D::StereoRectify)
|
||||
{
|
||||
NanEscapableScope();
|
||||
|
||||
try {
|
||||
// Get the arguments
|
||||
|
||||
// Arg0, the first camera matrix
|
||||
cv::Mat K1 = matFromMatrix(args[0]);
|
||||
|
||||
// Arg1, the first distortion coefficients
|
||||
cv::Mat d1 = matFromMatrix(args[1]);
|
||||
|
||||
// Arg2, the second camera matrix
|
||||
cv::Mat K2 = matFromMatrix(args[2]);
|
||||
|
||||
// Arg3, the second distortion coefficients
|
||||
cv::Mat d2 = matFromMatrix(args[3]);
|
||||
|
||||
// Arg4, the image size
|
||||
cv::Size imageSize = sizeFromArray(args[4]);
|
||||
|
||||
// arg5, the intercamera rotation matrix
|
||||
cv::Mat R = matFromMatrix(args[5]);
|
||||
|
||||
// Arg6, the intercamera translation vector
|
||||
cv::Mat t = matFromMatrix(args[6]);
|
||||
|
||||
// Arg8, flags, skipping for now
|
||||
|
||||
// Arg9, freescaling paremeter, skipping for now
|
||||
|
||||
// Arg10, new image size, skipping for now to fix at original image size
|
||||
|
||||
// Make output matrics
|
||||
cv::Mat R1, R2, P1, P2, Q;
|
||||
|
||||
// Do the stereo rectification
|
||||
cv::stereoRectify(K1, d1, K2, d2, imageSize, R, t, R1, R2, P1, P2, Q);
|
||||
|
||||
// Make the return object
|
||||
Local<Object> ret = NanNew<Object>();
|
||||
|
||||
ret->Set(NanNew<String>("R1"), matrixFromMat(R1));
|
||||
ret->Set(NanNew<String>("R2"), matrixFromMat(R2));
|
||||
ret->Set(NanNew<String>("P1"), matrixFromMat(P1));
|
||||
ret->Set(NanNew<String>("P2"), matrixFromMat(P2));
|
||||
ret->Set(NanNew<String>("Q"), matrixFromMat(Q));
|
||||
|
||||
// Return the recification parameters
|
||||
NanReturnValue(ret);
|
||||
|
||||
} catch (cv::Exception &e) {
|
||||
const char *err_msg = e.what();
|
||||
NanThrowError(err_msg);
|
||||
NanReturnUndefined();
|
||||
}
|
||||
}
|
||||
|
||||
// cv::computeCorrespondEpilines
|
||||
NAN_METHOD(Calib3D::ComputeCorrespondEpilines)
|
||||
{
|
||||
NanEscapableScope();
|
||||
|
||||
try {
|
||||
// Get the arguments
|
||||
|
||||
// Arg0, the image points
|
||||
std::vector<cv::Point2f> points = points2fFromArray(args[0]);
|
||||
|
||||
// Arg1, the image index (1 or 2)
|
||||
int whichImage = int(args[1]->ToNumber()->Value());
|
||||
|
||||
// Arg2, the fundamental matrix
|
||||
cv::Mat F = matFromMatrix(args[2]);
|
||||
|
||||
// compute the lines
|
||||
std::vector<cv::Vec3f> lines;
|
||||
cv::computeCorrespondEpilines(points, whichImage, F, lines);
|
||||
|
||||
// Convert the lines to an array of objects (ax + by + c = 0)
|
||||
Local<Array> linesArray = NanNew<Array>(lines.size());
|
||||
for(unsigned int i = 0; i < lines.size(); i++)
|
||||
{
|
||||
Local<Object> line_data = NanNew<Object>();
|
||||
line_data->Set(NanNew<String>("a"), NanNew<Number>(lines[i][0]));
|
||||
line_data->Set(NanNew<String>("b"), NanNew<Number>(lines[i][1]));
|
||||
line_data->Set(NanNew<String>("c"), NanNew<Number>(lines[i][2]));
|
||||
|
||||
linesArray->Set(NanNew<Number>(i), line_data);
|
||||
}
|
||||
|
||||
// Return the lines
|
||||
NanReturnValue(linesArray);
|
||||
|
||||
} catch (cv::Exception &e) {
|
||||
const char *err_msg = e.what();
|
||||
NanThrowError(err_msg);
|
||||
NanReturnUndefined();
|
||||
}
|
||||
}
|
||||
|
||||
// cv::reprojectImageTo3D
|
||||
NAN_METHOD(Calib3D::ReprojectImageTo3D)
|
||||
{
|
||||
NanEscapableScope();
|
||||
|
||||
try {
|
||||
// Get the arguments
|
||||
|
||||
// Arg0, the disparity image
|
||||
cv::Mat disparity = matFromMatrix(args[0]);
|
||||
|
||||
// Arg1, the depth-to-disparity transformation Q
|
||||
cv::Mat Q = matFromMatrix(args[1]);
|
||||
|
||||
// Arg 2, handle missing values, skipped for now
|
||||
|
||||
// Arg3, output bit depth, skipped for now
|
||||
|
||||
// Compute the depth image
|
||||
cv::Mat depthImage;
|
||||
cv::reprojectImageTo3D(disparity, depthImage, Q);
|
||||
|
||||
// Wrap the depth image
|
||||
Local<Object> depthImageMatrix = matrixFromMat(depthImage);
|
||||
|
||||
NanReturnValue(depthImageMatrix);
|
||||
|
||||
|
||||
} catch (cv::Exception &e) {
|
||||
const char *err_msg = e.what();
|
||||
NanThrowError(err_msg);
|
||||
NanReturnUndefined();
|
||||
}
|
||||
}
|
||||
31
src/Calib3D.h
Normal file
31
src/Calib3D.h
Normal file
@ -0,0 +1,31 @@
|
||||
#ifndef __NODE_CALIB3D_H
|
||||
#define __NODE_CALIB3D_H
|
||||
|
||||
#include "OpenCV.h"
|
||||
|
||||
// Implementation of calib3d.hpp functions
|
||||
|
||||
class Calib3D: public node::ObjectWrap {
|
||||
public:
|
||||
static void Init(Handle<Object> target);
|
||||
|
||||
static NAN_METHOD(FindChessboardCorners);
|
||||
|
||||
static NAN_METHOD(DrawChessboardCorners);
|
||||
|
||||
static NAN_METHOD(CalibrateCamera);
|
||||
|
||||
static NAN_METHOD(SolvePnP);
|
||||
|
||||
static NAN_METHOD(GetOptimalNewCameraMatrix);
|
||||
|
||||
static NAN_METHOD(StereoCalibrate);
|
||||
|
||||
static NAN_METHOD(StereoRectify);
|
||||
|
||||
static NAN_METHOD(ComputeCorrespondEpilines);
|
||||
|
||||
static NAN_METHOD(ReprojectImageTo3D);
|
||||
};
|
||||
|
||||
#endif
|
||||
@ -50,7 +50,7 @@ CascadeClassifierWrap::CascadeClassifierWrap(v8::Value* fileName){
|
||||
|
||||
class AsyncDetectMultiScale : public NanAsyncWorker {
|
||||
public:
|
||||
AsyncDetectMultiScale(NanCallback *callback, CascadeClassifierWrap *cc, Matrix* im, double scale, int neighbors, int minw, int minh, int sleep_for) : NanAsyncWorker(callback), cc(cc), im(im), scale(scale), neighbors(neighbors), minw(minw), minh(minh), sleep_for(sleep_for) {}
|
||||
AsyncDetectMultiScale(NanCallback *callback, CascadeClassifierWrap *cc, Matrix* im, double scale, int neighbors, int minw, int minh) : NanAsyncWorker(callback), cc(cc), im(im), scale(scale), neighbors(neighbors), minw(minw), minh(minh) {}
|
||||
~AsyncDetectMultiScale() {}
|
||||
|
||||
void Execute () {
|
||||
@ -103,7 +103,6 @@ class AsyncDetectMultiScale : public NanAsyncWorker {
|
||||
int neighbors;
|
||||
int minw;
|
||||
int minh;
|
||||
int sleep_for;
|
||||
std::vector<cv::Rect> res;
|
||||
|
||||
};
|
||||
@ -141,7 +140,7 @@ NAN_METHOD(CascadeClassifierWrap::DetectMultiScale){
|
||||
|
||||
NanCallback *callback = new NanCallback(cb.As<Function>());
|
||||
|
||||
NanAsyncQueueWorker( new AsyncDetectMultiScale(callback, self, im, scale, neighbors, minw, minh, 1) );
|
||||
NanAsyncQueueWorker( new AsyncDetectMultiScale(callback, self, im, scale, neighbors, minw, minh) );
|
||||
NanReturnUndefined();
|
||||
|
||||
}
|
||||
|
||||
@ -4,6 +4,9 @@
|
||||
#define CONST(C) \
|
||||
obj->Set(NanNew<String>(#C), NanNew<Integer>(C));
|
||||
|
||||
#define CONST_ENUM(C) \
|
||||
obj->Set(NanNew<String>(#C), NanNew<Integer>((int)(cv::C)));
|
||||
|
||||
void
|
||||
Constants::Init(Handle<Object> target) {
|
||||
Persistent<Object> inner;
|
||||
@ -54,6 +57,12 @@ Constants::Init(Handle<Object> target) {
|
||||
CONST(CV_64FC3);
|
||||
CONST(CV_64FC4);
|
||||
|
||||
CONST_ENUM(INTER_NEAREST);
|
||||
CONST_ENUM(INTER_LINEAR);
|
||||
CONST_ENUM(INTER_AREA);
|
||||
CONST_ENUM(INTER_CUBIC);
|
||||
CONST_ENUM(INTER_LANCZOS4);
|
||||
|
||||
target->Set(NanNew("Constants"), obj);
|
||||
}
|
||||
|
||||
|
||||
@ -53,7 +53,13 @@ NamedWindow::NamedWindow(const std::string& name, int f){
|
||||
NAN_METHOD(NamedWindow::Show){
|
||||
SETUP_FUNCTION(NamedWindow)
|
||||
Matrix *im = ObjectWrap::Unwrap<Matrix>(args[0]->ToObject());
|
||||
cv::imshow(self->winname, im->mat);
|
||||
|
||||
try{
|
||||
cv::imshow(self->winname, im->mat);
|
||||
} catch(cv::Exception& e ){
|
||||
const char* err_msg = e.what();
|
||||
NanThrowError(err_msg);
|
||||
}
|
||||
|
||||
NanReturnValue(args.Holder());
|
||||
}
|
||||
|
||||
169
src/ImgProc.cc
Normal file
169
src/ImgProc.cc
Normal file
@ -0,0 +1,169 @@
|
||||
#include "ImgProc.h"
|
||||
#include "Matrix.h"
|
||||
|
||||
void ImgProc::Init(Handle<Object> target)
|
||||
{
|
||||
Persistent<Object> inner;
|
||||
Local<Object> obj = NanNew<Object>();
|
||||
NanAssignPersistent(inner, obj);
|
||||
|
||||
NODE_SET_METHOD(obj, "undistort", Undistort);
|
||||
NODE_SET_METHOD(obj, "initUndistortRectifyMap", InitUndistortRectifyMap);
|
||||
NODE_SET_METHOD(obj, "remap", Remap);
|
||||
|
||||
target->Set(NanNew("imgproc"), obj);
|
||||
}
|
||||
|
||||
// cv::undistort
|
||||
NAN_METHOD(ImgProc::Undistort)
|
||||
{
|
||||
NanEscapableScope();
|
||||
|
||||
try {
|
||||
// Get the arguments
|
||||
|
||||
// Arg 0 is the image
|
||||
Matrix* m0 = ObjectWrap::Unwrap<Matrix>(args[0]->ToObject());
|
||||
cv::Mat inputImage = m0->mat;
|
||||
|
||||
// Arg 1 is the camera matrix
|
||||
Matrix* m1 = ObjectWrap::Unwrap<Matrix>(args[1]->ToObject());
|
||||
cv::Mat K = m1->mat;
|
||||
|
||||
// Arg 2 is the distortion coefficents
|
||||
Matrix* m2 = ObjectWrap::Unwrap<Matrix>(args[2]->ToObject());
|
||||
cv::Mat dist = m2->mat;
|
||||
|
||||
// Make an mat to hold the result image
|
||||
cv::Mat outputImage;
|
||||
|
||||
// Undistort
|
||||
cv::undistort(inputImage, outputImage, K, dist);
|
||||
|
||||
// Wrap the output image
|
||||
Local<Object> outMatrixWrap = NanNew(Matrix::constructor)->GetFunction()->NewInstance();
|
||||
Matrix *outMatrix = ObjectWrap::Unwrap<Matrix>(outMatrixWrap);
|
||||
outMatrix->mat = outputImage;
|
||||
|
||||
// Return the output image
|
||||
NanReturnValue(outMatrixWrap);
|
||||
|
||||
} catch (cv::Exception &e) {
|
||||
const char *err_msg = e.what();
|
||||
NanThrowError(err_msg);
|
||||
NanReturnUndefined();
|
||||
}
|
||||
}
|
||||
|
||||
// cv::initUndistortRectifyMap
|
||||
NAN_METHOD(ImgProc::InitUndistortRectifyMap)
|
||||
{
|
||||
NanEscapableScope();
|
||||
|
||||
try {
|
||||
|
||||
// Arg 0 is the camera matrix
|
||||
Matrix* m0 = ObjectWrap::Unwrap<Matrix>(args[0]->ToObject());
|
||||
cv::Mat K = m0->mat;
|
||||
|
||||
// Arg 1 is the distortion coefficents
|
||||
Matrix* m1 = ObjectWrap::Unwrap<Matrix>(args[1]->ToObject());
|
||||
cv::Mat dist = m1->mat;
|
||||
|
||||
// Arg 2 is the recification transformation
|
||||
Matrix* m2 = ObjectWrap::Unwrap<Matrix>(args[2]->ToObject());
|
||||
cv::Mat R = m2->mat;
|
||||
|
||||
// Arg 3 is the new camera matrix
|
||||
Matrix* m3 = ObjectWrap::Unwrap<Matrix>(args[3]->ToObject());
|
||||
cv::Mat newK = m3->mat;
|
||||
|
||||
// Arg 4 is the image size
|
||||
cv::Size imageSize;
|
||||
if (args[4]->IsArray()) {
|
||||
Local<Object> v8sz = args[4]->ToObject();
|
||||
|
||||
imageSize = cv::Size(v8sz->Get(1)->IntegerValue(), v8sz->Get(0)->IntegerValue());
|
||||
} else {
|
||||
JSTHROW_TYPE("Must pass image size");
|
||||
}
|
||||
|
||||
// Arg 5 is the first map type, skip for now
|
||||
int m1type = args[5]->IntegerValue();
|
||||
|
||||
// Make matrices to hold the output maps
|
||||
cv::Mat map1, map2;
|
||||
|
||||
// Compute the rectification map
|
||||
cv::initUndistortRectifyMap(K, dist, R, newK, imageSize, m1type, map1, map2);
|
||||
|
||||
// Wrap the output maps
|
||||
Local<Object> map1Wrap = NanNew(Matrix::constructor)->GetFunction()->NewInstance();
|
||||
Matrix *map1Matrix = ObjectWrap::Unwrap<Matrix>(map1Wrap);
|
||||
map1Matrix->mat = map1;
|
||||
|
||||
Local<Object> map2Wrap = NanNew(Matrix::constructor)->GetFunction()->NewInstance();
|
||||
Matrix *map2Matrix = ObjectWrap::Unwrap<Matrix>(map2Wrap);
|
||||
map2Matrix->mat = map2;
|
||||
|
||||
// Make a return object with the two maps
|
||||
Local<Object> ret = NanNew<Object>();
|
||||
ret->Set(NanNew<String>("map1"), map1Wrap);
|
||||
ret->Set(NanNew<String>("map2"), map2Wrap);
|
||||
|
||||
// Return the maps
|
||||
NanReturnValue(ret);
|
||||
|
||||
|
||||
} catch (cv::Exception &e) {
|
||||
const char *err_msg = e.what();
|
||||
NanThrowError(err_msg);
|
||||
NanReturnUndefined();
|
||||
}
|
||||
}
|
||||
|
||||
// cv::remap
|
||||
NAN_METHOD(ImgProc::Remap)
|
||||
{
|
||||
NanEscapableScope();
|
||||
|
||||
try {
|
||||
// Get the arguments
|
||||
|
||||
// Arg 0 is the image
|
||||
Matrix* m0 = ObjectWrap::Unwrap<Matrix>(args[0]->ToObject());
|
||||
cv::Mat inputImage = m0->mat;
|
||||
|
||||
// Arg 1 is the first map
|
||||
Matrix* m1 = ObjectWrap::Unwrap<Matrix>(args[1]->ToObject());
|
||||
cv::Mat map1 = m1->mat;
|
||||
|
||||
// Arg 2 is the second map
|
||||
Matrix* m2 = ObjectWrap::Unwrap<Matrix>(args[2]->ToObject());
|
||||
cv::Mat map2 = m2->mat;
|
||||
|
||||
// Arg 3 is the interpolation mode
|
||||
int interpolation = args[3]->IntegerValue();
|
||||
|
||||
// Args 4, 5 border settings, skipping for now
|
||||
|
||||
// Output image
|
||||
cv::Mat outputImage;
|
||||
|
||||
// Remap
|
||||
cv::remap(inputImage, outputImage, map1, map2, interpolation);
|
||||
|
||||
// Wrap the output image
|
||||
Local<Object> outMatrixWrap = NanNew(Matrix::constructor)->GetFunction()->NewInstance();
|
||||
Matrix *outMatrix = ObjectWrap::Unwrap<Matrix>(outMatrixWrap);
|
||||
outMatrix->mat = outputImage;
|
||||
|
||||
// Return the image
|
||||
NanReturnValue(outMatrixWrap);
|
||||
|
||||
} catch (cv::Exception &e) {
|
||||
const char *err_msg = e.what();
|
||||
NanThrowError(err_msg);
|
||||
NanReturnUndefined();
|
||||
}
|
||||
}
|
||||
19
src/ImgProc.h
Normal file
19
src/ImgProc.h
Normal file
@ -0,0 +1,19 @@
|
||||
#ifndef __NODE_IMGPROC_H
|
||||
#define __NODE_IMGPROC_H
|
||||
|
||||
#include "OpenCV.h"
|
||||
|
||||
// Implementation of imgproc.hpp functions
|
||||
|
||||
class ImgProc: public node::ObjectWrap {
|
||||
public:
|
||||
static void Init(Handle<Object> target);
|
||||
|
||||
static NAN_METHOD(Undistort);
|
||||
|
||||
static NAN_METHOD(InitUndistortRectifyMap);
|
||||
|
||||
static NAN_METHOD(Remap);
|
||||
};
|
||||
|
||||
#endif
|
||||
147
src/Matrix.cc
147
src/Matrix.cc
@ -7,7 +7,7 @@ v8::Persistent<FunctionTemplate> Matrix::constructor;
|
||||
|
||||
cv::Scalar setColor(Local<Object> objColor);
|
||||
cv::Point setPoint(Local<Object> objPoint);
|
||||
cv::Rect* setRect(Local<Object> objRect);
|
||||
cv::Rect* setRect(Local<Object> objRect, cv::Rect &result);
|
||||
|
||||
void
|
||||
Matrix::Init(Handle<Object> target) {
|
||||
@ -32,11 +32,13 @@ Matrix::Init(Handle<Object> target) {
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "height", Height);
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "size", Size);
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "clone", Clone);
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "crop", Crop);
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "toBuffer", ToBuffer);
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "toBufferAsync", ToBufferAsync);
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "ellipse", Ellipse);
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "rectangle", Rectangle);
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "line", Line);
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "fillPoly", FillPoly);
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "save", Save);
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "saveAsync", SaveAsync);
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "resize", Resize);
|
||||
@ -68,6 +70,7 @@ Matrix::Init(Handle<Object> target) {
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "drawAllContours", DrawAllContours);
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "goodFeaturesToTrack", GoodFeaturesToTrack);
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "houghLinesP", HoughLinesP);
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "crop", Crop);
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "houghCircles", HoughCircles);
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "inRange", inRange);
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "adjustROI", AdjustROI);
|
||||
@ -81,6 +84,7 @@ Matrix::Init(Handle<Object> target) {
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "equalizeHist", EqualizeHist);
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "floodFill", FloodFill);
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "matchTemplate", MatchTemplate);
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "templateMatches", TemplateMatches);
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "minMaxLoc", MinMaxLoc);
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "pushBack", PushBack);
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "putText", PutText);
|
||||
@ -451,7 +455,7 @@ NAN_METHOD(Matrix::ToBuffer){
|
||||
|
||||
v8::Local<v8::Object> globalObj = NanGetCurrentContext()->Global();
|
||||
v8::Local<v8::Function> bufferConstructor = v8::Local<v8::Function>::Cast(globalObj->Get(NanNew<String>("Buffer")));
|
||||
v8::Handle<v8::Value> constructorArgs[3] = {buf, NanNew<v8::Integer>(vec.size()), NanNew<v8::Integer>(0)};
|
||||
v8::Handle<v8::Value> constructorArgs[3] = {buf, NanNew<v8::Integer>((unsigned)vec.size()), NanNew<v8::Integer>(0)};
|
||||
v8::Local<v8::Object> actualBuffer = bufferConstructor->NewInstance(3, constructorArgs);
|
||||
|
||||
NanReturnValue(actualBuffer);
|
||||
@ -484,7 +488,7 @@ class AsyncToBufferWorker : public NanAsyncWorker {
|
||||
|
||||
v8::Local<v8::Object> globalObj = NanGetCurrentContext()->Global();
|
||||
v8::Local<v8::Function> bufferConstructor = v8::Local<v8::Function>::Cast(globalObj->Get(NanNew<String>("Buffer")));
|
||||
v8::Handle<v8::Value> constructorArgs[3] = {buf, NanNew<v8::Integer>(res.size()), NanNew<v8::Integer>(0)};
|
||||
v8::Handle<v8::Value> constructorArgs[3] = {buf, NanNew<v8::Integer>((unsigned)res.size()), NanNew<v8::Integer>(0)};
|
||||
v8::Local<v8::Object> actualBuffer = bufferConstructor->NewInstance(3, constructorArgs);
|
||||
|
||||
|
||||
@ -682,6 +686,42 @@ NAN_METHOD(Matrix::Line) {
|
||||
NanReturnNull();
|
||||
}
|
||||
|
||||
NAN_METHOD(Matrix::FillPoly) {
|
||||
SETUP_FUNCTION(Matrix)
|
||||
|
||||
if(args[0]->IsArray())
|
||||
{
|
||||
Local<Array> polyArray = Local<Array>::Cast(args[0]->ToObject());
|
||||
|
||||
cv::Point **polygons = new cv::Point*[polyArray->Length()];
|
||||
int *polySizes = new int[polyArray->Length()];
|
||||
for(unsigned int i = 0; i < polyArray->Length(); i++)
|
||||
{
|
||||
Local<Array> singlePoly = Local<Array>::Cast(polyArray->Get(i)->ToObject());
|
||||
polygons[i] = new cv::Point[singlePoly->Length()];
|
||||
polySizes[i] = singlePoly->Length();
|
||||
|
||||
for(unsigned int j = 0; j < singlePoly->Length(); j++)
|
||||
{
|
||||
Local<Array> point = Local<Array>::Cast(singlePoly->Get(j)->ToObject());
|
||||
polygons[i][j].x = point->Get(0)->IntegerValue();
|
||||
polygons[i][j].y = point->Get(1)->IntegerValue();
|
||||
}
|
||||
}
|
||||
|
||||
cv::Scalar color(0, 0, 255);
|
||||
|
||||
if(args[1]->IsArray()) {
|
||||
Local<Object> objColor = args[1]->ToObject();
|
||||
color = setColor(objColor);
|
||||
}
|
||||
|
||||
cv::fillPoly(self->mat, (const cv::Point **)polygons, polySizes, polyArray->Length(), color);
|
||||
}
|
||||
|
||||
NanReturnNull();
|
||||
}
|
||||
|
||||
|
||||
NAN_METHOD(Matrix::Save) {
|
||||
SETUP_FUNCTION(Matrix)
|
||||
@ -1014,7 +1054,12 @@ NAN_METHOD(Matrix::AddWeighted) {
|
||||
float beta = args[3]->NumberValue();
|
||||
int gamma = 0;
|
||||
|
||||
cv::addWeighted(src1->mat, alpha, src2->mat, beta, gamma, self->mat);
|
||||
try{
|
||||
cv::addWeighted(src1->mat, alpha, src2->mat, beta, gamma, self->mat);
|
||||
} catch(cv::Exception& e ){
|
||||
const char* err_msg = e.what();
|
||||
NanThrowError(err_msg);
|
||||
}
|
||||
|
||||
|
||||
NanReturnNull();
|
||||
@ -1309,7 +1354,7 @@ cv::Point setPoint(Local<Object> objPoint) {
|
||||
return cv::Point( objPoint->Get(0)->IntegerValue(), objPoint->Get(1)->IntegerValue() );
|
||||
}
|
||||
|
||||
cv::Rect* setRect(Local<Object> objRect) {
|
||||
cv::Rect* setRect(Local<Object> objRect, cv::Rect &result) {
|
||||
|
||||
if(!objRect->IsArray() || !objRect->Get(0)->IsArray() || !objRect->Get(0)->IsArray() ){
|
||||
printf("error");
|
||||
@ -1318,14 +1363,13 @@ cv::Rect* setRect(Local<Object> objRect) {
|
||||
|
||||
Local<Object> point = objRect->Get(0)->ToObject();
|
||||
Local<Object> size = objRect->Get(1)->ToObject();
|
||||
cv::Rect ret;
|
||||
|
||||
ret.x = point->Get(0)->IntegerValue();
|
||||
ret.y = point->Get(1)->IntegerValue();
|
||||
ret.width = size->Get(0)->IntegerValue();
|
||||
ret.height = size->Get(1)->IntegerValue();
|
||||
result.x = point->Get(0)->IntegerValue();
|
||||
result.y = point->Get(1)->IntegerValue();
|
||||
result.width = size->Get(0)->IntegerValue();
|
||||
result.height = size->Get(1)->IntegerValue();
|
||||
|
||||
return (cv::Rect*) &ret;
|
||||
return &result;
|
||||
}
|
||||
|
||||
|
||||
@ -1713,10 +1757,11 @@ NAN_METHOD(Matrix::FloodFill){
|
||||
|
||||
|
||||
Local<Object> obj = args[0]->ToObject();
|
||||
cv::Rect rect;
|
||||
|
||||
int ret = cv::floodFill(self->mat, setPoint(obj->Get(NanNew<String>("seedPoint"))->ToObject())
|
||||
, setColor(obj->Get(NanNew<String>("newColor"))->ToObject())
|
||||
, obj->Get(NanNew<String>("rect"))->IsUndefined() ? 0 : setRect(obj->Get(NanNew<String>("rect"))->ToObject())
|
||||
, obj->Get(NanNew<String>("rect"))->IsUndefined() ? 0 : setRect(obj->Get(NanNew<String>("rect"))->ToObject(), rect)
|
||||
, setColor(obj->Get(NanNew<String>("loDiff"))->ToObject())
|
||||
, setColor(obj->Get(NanNew<String>("upDiff"))->ToObject())
|
||||
, 4 );
|
||||
@ -1725,6 +1770,84 @@ NAN_METHOD(Matrix::FloodFill){
|
||||
NanReturnValue(NanNew<Number>( ret ));
|
||||
}
|
||||
|
||||
// @author olfox
|
||||
// Returns an array of the most probable positions
|
||||
// Usage: output = input.templateMatches(min_probability, max_probability, limit, ascending, min_x_distance, min_y_distance);
|
||||
NAN_METHOD(Matrix::TemplateMatches){
|
||||
SETUP_FUNCTION(Matrix)
|
||||
|
||||
bool filter_min_probability = (args.Length() >= 1) ? args[0]->IsNumber() : false;
|
||||
bool filter_max_probability = (args.Length() >= 2) ? args[1]->IsNumber() : false;
|
||||
double min_probability = filter_min_probability ? args[0]->NumberValue() : 0;
|
||||
double max_probability = filter_max_probability ? args[1]->NumberValue() : 0;
|
||||
int limit = (args.Length() >= 3) ? args[2]->IntegerValue() : 0;
|
||||
bool ascending = (args.Length() >= 4) ? args[3]->BooleanValue() : false;
|
||||
int min_x_distance = (args.Length() >= 5) ? args[4]->IntegerValue() : 0;
|
||||
int min_y_distance = (args.Length() >= 6) ? args[5]->IntegerValue() : 0;
|
||||
|
||||
cv::Mat_<int> indices;
|
||||
|
||||
if (ascending)
|
||||
cv::sortIdx(self->mat.reshape(0,1), indices, CV_SORT_ASCENDING + CV_SORT_EVERY_ROW);
|
||||
else
|
||||
cv::sortIdx(self->mat.reshape(0,1), indices, CV_SORT_DESCENDING + CV_SORT_EVERY_ROW);
|
||||
|
||||
cv::Mat hit_mask = cv::Mat::zeros(self->mat.size(), CV_64F);
|
||||
v8::Local<v8::Array> probabilites_array = NanNew<v8::Array>(limit);
|
||||
|
||||
cv::Mat_<float>::const_iterator begin = self->mat.begin<float>();
|
||||
cv::Mat_<int>::const_iterator it = indices.begin();
|
||||
cv::Mat_<int>::const_iterator end = indices.end();
|
||||
int index = 0;
|
||||
for (; (limit == 0 || index < limit) && it != end; ++it) {
|
||||
cv::Point pt = (begin + *it).pos();
|
||||
|
||||
float probability = self->mat.at<float>(pt.y, pt.x);
|
||||
|
||||
if (filter_min_probability && probability < min_probability) {
|
||||
if (ascending) continue;
|
||||
else break;
|
||||
}
|
||||
|
||||
if (filter_max_probability && probability > max_probability) {
|
||||
if (ascending) break;
|
||||
else continue;
|
||||
}
|
||||
|
||||
if (min_x_distance != 0 || min_y_distance != 0) {
|
||||
// Check hit mask color for for every corner
|
||||
|
||||
cv::Size maxSize = hit_mask.size();
|
||||
int max_x = maxSize.width - 1;
|
||||
int max_y = maxSize.height - 1;
|
||||
cv::Point top_left = cv::Point(max(0, pt.x - min_x_distance), max(0, pt.y - min_y_distance));
|
||||
cv::Point top_right = cv::Point(min(max_x, pt.x + min_x_distance), max(0, pt.y - min_y_distance));
|
||||
cv::Point bottom_left = cv::Point(max(0, pt.x - min_x_distance), min(max_y, pt.y + min_y_distance));
|
||||
cv::Point bottom_right = cv::Point(min(max_x, pt.x + min_x_distance), min(max_y, pt.y + min_y_distance));
|
||||
if (hit_mask.at<double>(top_left.y, top_left.x) > 0) continue;
|
||||
if (hit_mask.at<double>(top_right.y, top_right.x) > 0) continue;
|
||||
if (hit_mask.at<double>(bottom_left.y, bottom_left.x) > 0) continue;
|
||||
if (hit_mask.at<double>(bottom_right.y, bottom_right.x) > 0) continue;
|
||||
cv::Scalar color(255.0);
|
||||
cv::rectangle(hit_mask, top_left, bottom_right, color, CV_FILLED);
|
||||
}
|
||||
|
||||
Local<Value> x_value = NanNew<Number>(pt.x);
|
||||
Local<Value> y_value = NanNew<Number>(pt.y);
|
||||
Local<Value> probability_value = NanNew<Number>(probability);
|
||||
|
||||
Local<Object> probability_object = NanNew<Object>();
|
||||
probability_object->Set(NanNew<String>("x"), x_value);
|
||||
probability_object->Set(NanNew<String>("y"), y_value);
|
||||
probability_object->Set(NanNew<String>("probability"), probability_value);
|
||||
|
||||
probabilites_array->Set(index, probability_object);
|
||||
index++;
|
||||
}
|
||||
|
||||
NanReturnValue(probabilites_array);
|
||||
}
|
||||
|
||||
// @author ytham
|
||||
// Match Template filter
|
||||
// Usage: output = input.matchTemplate("templateFileString", method);
|
||||
|
||||
@ -35,6 +35,7 @@ class Matrix: public node::ObjectWrap {
|
||||
JSFUNC(Rectangle)
|
||||
JSFUNC(Line)
|
||||
JSFUNC(Empty)
|
||||
JSFUNC(FillPoly)
|
||||
|
||||
JSFUNC(Save)
|
||||
JSFUNC(SaveAsync)
|
||||
@ -96,6 +97,7 @@ class Matrix: public node::ObjectWrap {
|
||||
JSFUNC(FloodFill)
|
||||
|
||||
JSFUNC(MatchTemplate)
|
||||
JSFUNC(TemplateMatches)
|
||||
JSFUNC(MinMaxLoc)
|
||||
|
||||
JSFUNC(PushBack)
|
||||
|
||||
@ -12,7 +12,6 @@ OpenCV::Init(Handle<Object> target) {
|
||||
target->Set(NanNew<String>("version"), NanNew<String>(out, n));
|
||||
|
||||
NODE_SET_METHOD(target, "readImage", ReadImage);
|
||||
|
||||
}
|
||||
|
||||
|
||||
|
||||
@ -55,4 +55,3 @@ class OpenCV: public node::ObjectWrap{
|
||||
|
||||
|
||||
#endif
|
||||
|
||||
|
||||
323
src/Stereo.cc
Normal file
323
src/Stereo.cc
Normal file
@ -0,0 +1,323 @@
|
||||
#include "Stereo.h"
|
||||
#include "Matrix.h"
|
||||
#include <opencv2/legacy/legacy.hpp>
|
||||
|
||||
// Block matching
|
||||
|
||||
v8::Persistent<FunctionTemplate> StereoBM::constructor;
|
||||
|
||||
void
|
||||
StereoBM::Init(Handle<Object> target) {
|
||||
NanScope();
|
||||
|
||||
Local<FunctionTemplate> ctor = NanNew<FunctionTemplate>(StereoBM::New);
|
||||
NanAssignPersistent(constructor, ctor);
|
||||
ctor->InstanceTemplate()->SetInternalFieldCount(1);
|
||||
ctor->SetClassName(NanNew("StereoBM"));
|
||||
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "compute", Compute);
|
||||
|
||||
ctor->Set(NanNew<String>("BASIC_PRESET"), NanNew<Integer>((int)cv::StereoBM::BASIC_PRESET));
|
||||
ctor->Set(NanNew<String>("FISH_EYE_PRESET"), NanNew<Integer>((int)cv::StereoBM::FISH_EYE_PRESET));
|
||||
ctor->Set(NanNew<String>("NARROW_PRESET"), NanNew<Integer>((int)cv::StereoBM::NARROW_PRESET));
|
||||
|
||||
target->Set(NanNew("StereoBM"), ctor->GetFunction());
|
||||
}
|
||||
|
||||
NAN_METHOD(StereoBM::New) {
|
||||
NanScope();
|
||||
|
||||
if (args.This()->InternalFieldCount() == 0)
|
||||
NanThrowTypeError("Cannot instantiate without new");
|
||||
|
||||
StereoBM *stereo;
|
||||
|
||||
if (args.Length() == 0)
|
||||
{
|
||||
stereo = new StereoBM();
|
||||
}
|
||||
else if (args.Length() == 1)
|
||||
{
|
||||
stereo = new StereoBM(args[0]->IntegerValue()); // preset
|
||||
}
|
||||
else if (args.Length() == 2)
|
||||
{
|
||||
stereo = new StereoBM(args[0]->IntegerValue(), args[1]->IntegerValue()); // preset, disparity search range
|
||||
}
|
||||
else
|
||||
{
|
||||
stereo = new StereoBM(args[0]->IntegerValue(), args[1]->IntegerValue(), args[2]->IntegerValue()); // preset, disparity search range, sum of absolute differences window size
|
||||
}
|
||||
|
||||
stereo->Wrap(args.Holder());
|
||||
NanReturnValue(args.Holder());
|
||||
}
|
||||
|
||||
StereoBM::StereoBM(int preset, int ndisparities, int SADWindowSize)
|
||||
: ObjectWrap(), stereo(preset, ndisparities, SADWindowSize)
|
||||
{
|
||||
|
||||
}
|
||||
|
||||
// TODO make this async
|
||||
NAN_METHOD(StereoBM::Compute)
|
||||
{
|
||||
SETUP_FUNCTION(StereoBM)
|
||||
|
||||
try {
|
||||
// Get the arguments
|
||||
|
||||
// Arg 0, the 'left' image
|
||||
Matrix* m0 = ObjectWrap::Unwrap<Matrix>(args[0]->ToObject());
|
||||
cv::Mat left = m0->mat;
|
||||
|
||||
// Arg 1, the 'right' image
|
||||
Matrix* m1 = ObjectWrap::Unwrap<Matrix>(args[1]->ToObject());
|
||||
cv::Mat right = m1->mat;
|
||||
|
||||
// Optional 3rd arg, the disparty depth
|
||||
int type = CV_16S;
|
||||
if(args.Length() > 2)
|
||||
{
|
||||
type = args[2]->IntegerValue();
|
||||
}
|
||||
|
||||
// Compute stereo using the block matching algorithm
|
||||
cv::Mat disparity;
|
||||
self->stereo(left, right, disparity, type);
|
||||
|
||||
// Wrap the returned disparity map
|
||||
Local<Object> disparityWrap = NanNew(Matrix::constructor)->GetFunction()->NewInstance();
|
||||
Matrix *disp = ObjectWrap::Unwrap<Matrix>(disparityWrap);
|
||||
disp->mat = disparity;
|
||||
|
||||
NanReturnValue(disparityWrap);
|
||||
|
||||
} catch (cv::Exception &e) {
|
||||
const char *err_msg = e.what();
|
||||
NanThrowError(err_msg);
|
||||
NanReturnUndefined();
|
||||
}
|
||||
|
||||
};
|
||||
|
||||
// Semi-Global Block matching
|
||||
|
||||
v8::Persistent<FunctionTemplate> StereoSGBM::constructor;
|
||||
|
||||
void
|
||||
StereoSGBM::Init(Handle<Object> target) {
|
||||
NanScope();
|
||||
|
||||
Local<FunctionTemplate> ctor = NanNew<FunctionTemplate>(StereoSGBM::New);
|
||||
NanAssignPersistent(constructor, ctor);
|
||||
ctor->InstanceTemplate()->SetInternalFieldCount(1);
|
||||
ctor->SetClassName(NanNew("StereoSGBM"));
|
||||
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "compute", Compute);
|
||||
|
||||
target->Set(NanNew("StereoSGBM"), ctor->GetFunction());
|
||||
}
|
||||
|
||||
NAN_METHOD(StereoSGBM::New) {
|
||||
NanScope();
|
||||
|
||||
if (args.This()->InternalFieldCount() == 0)
|
||||
NanThrowTypeError("Cannot instantiate without new");
|
||||
|
||||
StereoSGBM *stereo;
|
||||
|
||||
if (args.Length() == 0)
|
||||
{
|
||||
stereo = new StereoSGBM();
|
||||
}
|
||||
else
|
||||
{
|
||||
// If passing arguments, must pass the first 3 at least
|
||||
if (args.Length() >= 3)
|
||||
{
|
||||
switch (args.Length())
|
||||
{
|
||||
case 3:
|
||||
stereo = new StereoSGBM(args[0]->IntegerValue(), args[1]->IntegerValue(), args[2]->IntegerValue());
|
||||
break;
|
||||
|
||||
case 4:
|
||||
stereo = new StereoSGBM(args[0]->IntegerValue(), args[1]->IntegerValue(), args[2]->IntegerValue(), args[3]->IntegerValue());
|
||||
break;
|
||||
|
||||
case 5:
|
||||
stereo = new StereoSGBM(args[0]->IntegerValue(), args[1]->IntegerValue(), args[2]->IntegerValue(), args[3]->IntegerValue(), args[4]->IntegerValue());
|
||||
break;
|
||||
|
||||
case 6:
|
||||
stereo = new StereoSGBM(args[0]->IntegerValue(), args[1]->IntegerValue(), args[2]->IntegerValue(), args[3]->IntegerValue(), args[4]->IntegerValue(), args[5]->IntegerValue());
|
||||
break;
|
||||
|
||||
case 7:
|
||||
stereo = new StereoSGBM(args[0]->IntegerValue(), args[1]->IntegerValue(), args[2]->IntegerValue(), args[3]->IntegerValue(), args[4]->IntegerValue(), args[5]->IntegerValue(), args[6]->IntegerValue());
|
||||
break;
|
||||
|
||||
case 8:
|
||||
stereo = new StereoSGBM(args[0]->IntegerValue(), args[1]->IntegerValue(), args[2]->IntegerValue(), args[3]->IntegerValue(), args[4]->IntegerValue(), args[5]->IntegerValue(), args[6]->IntegerValue(), args[7]->IntegerValue());
|
||||
break;
|
||||
|
||||
case 9:
|
||||
stereo = new StereoSGBM(args[0]->IntegerValue(), args[1]->IntegerValue(), args[2]->IntegerValue(), args[3]->IntegerValue(), args[4]->IntegerValue(), args[5]->IntegerValue(), args[6]->IntegerValue(), args[7]->IntegerValue(), args[8]->IntegerValue());
|
||||
break;
|
||||
|
||||
case 10:
|
||||
stereo = new StereoSGBM(args[0]->IntegerValue(), args[1]->IntegerValue(), args[2]->IntegerValue(), args[3]->IntegerValue(), args[4]->IntegerValue(), args[5]->IntegerValue(), args[6]->IntegerValue(), args[7]->IntegerValue(), args[8]->IntegerValue(), args[9]->IntegerValue());
|
||||
break;
|
||||
|
||||
default:
|
||||
stereo = new StereoSGBM(args[0]->IntegerValue(), args[1]->IntegerValue(), args[2]->IntegerValue(), args[3]->IntegerValue(), args[4]->IntegerValue(), args[5]->IntegerValue(), args[6]->IntegerValue(), args[7]->IntegerValue(), args[8]->IntegerValue(), args[9]->IntegerValue(), args[10]->ToBoolean()->Value());
|
||||
break;
|
||||
}
|
||||
}
|
||||
else
|
||||
{
|
||||
NanThrowError("If overriding default settings, must pass minDisparity, numDisparities, and SADWindowSize");
|
||||
NanReturnUndefined();
|
||||
}
|
||||
}
|
||||
|
||||
stereo->Wrap(args.Holder());
|
||||
NanReturnValue(args.Holder());
|
||||
}
|
||||
|
||||
StereoSGBM::StereoSGBM()
|
||||
: ObjectWrap(), stereo()
|
||||
{
|
||||
|
||||
}
|
||||
|
||||
StereoSGBM::StereoSGBM(int minDisparity, int ndisparities, int SADWindowSize, int p1, int p2, int disp12MaxDiff, int preFilterCap, int uniquenessRatio, int speckleWindowSize, int speckleRange, bool fullDP)
|
||||
: ObjectWrap(), stereo(minDisparity, ndisparities, SADWindowSize, p1, p2, disp12MaxDiff, preFilterCap, uniquenessRatio, speckleWindowSize, speckleRange, fullDP)
|
||||
{
|
||||
|
||||
}
|
||||
|
||||
// TODO make this async
|
||||
NAN_METHOD(StereoSGBM::Compute)
|
||||
{
|
||||
SETUP_FUNCTION(StereoSGBM)
|
||||
|
||||
try {
|
||||
// Get the arguments
|
||||
|
||||
// Arg 0, the 'left' image
|
||||
Matrix* m0 = ObjectWrap::Unwrap<Matrix>(args[0]->ToObject());
|
||||
cv::Mat left = m0->mat;
|
||||
|
||||
// Arg 1, the 'right' image
|
||||
Matrix* m1 = ObjectWrap::Unwrap<Matrix>(args[1]->ToObject());
|
||||
cv::Mat right = m1->mat;
|
||||
|
||||
// Compute stereo using the block matching algorithm
|
||||
cv::Mat disparity;
|
||||
self->stereo(left, right, disparity);
|
||||
|
||||
// Wrap the returned disparity map
|
||||
Local<Object> disparityWrap = NanNew(Matrix::constructor)->GetFunction()->NewInstance();
|
||||
Matrix *disp = ObjectWrap::Unwrap<Matrix>(disparityWrap);
|
||||
disp->mat = disparity;
|
||||
|
||||
NanReturnValue(disparityWrap);
|
||||
|
||||
} catch (cv::Exception &e) {
|
||||
const char *err_msg = e.what();
|
||||
NanThrowError(err_msg);
|
||||
NanReturnUndefined();
|
||||
}
|
||||
|
||||
};
|
||||
|
||||
// Graph cut
|
||||
|
||||
v8::Persistent<FunctionTemplate> StereoGC::constructor;
|
||||
|
||||
void
|
||||
StereoGC::Init(Handle<Object> target) {
|
||||
NanScope();
|
||||
|
||||
Local<FunctionTemplate> ctor = NanNew<FunctionTemplate>(StereoGC::New);
|
||||
NanAssignPersistent(constructor, ctor);
|
||||
ctor->InstanceTemplate()->SetInternalFieldCount(1);
|
||||
ctor->SetClassName(NanNew("StereoGC"));
|
||||
|
||||
NODE_SET_PROTOTYPE_METHOD(ctor, "compute", Compute);
|
||||
|
||||
target->Set(NanNew("StereoGC"), ctor->GetFunction());
|
||||
}
|
||||
|
||||
NAN_METHOD(StereoGC::New) {
|
||||
NanScope();
|
||||
|
||||
if (args.This()->InternalFieldCount() == 0)
|
||||
NanThrowTypeError("Cannot instantiate without new");
|
||||
|
||||
StereoGC *stereo;
|
||||
|
||||
if (args.Length() == 0)
|
||||
{
|
||||
stereo = new StereoGC();
|
||||
}
|
||||
else if (args.Length() == 1)
|
||||
{
|
||||
stereo = new StereoGC(args[0]->IntegerValue()); // numberOfDisparities
|
||||
}
|
||||
else
|
||||
{
|
||||
stereo = new StereoGC(args[0]->IntegerValue(), args[1]->IntegerValue()); // max iterations
|
||||
}
|
||||
|
||||
stereo->Wrap(args.Holder());
|
||||
NanReturnValue(args.Holder());
|
||||
}
|
||||
|
||||
StereoGC::StereoGC(int numberOfDisparities, int maxIters)
|
||||
: ObjectWrap()
|
||||
{
|
||||
stereo = cvCreateStereoGCState(numberOfDisparities, maxIters);
|
||||
}
|
||||
|
||||
// TODO make this async
|
||||
NAN_METHOD(StereoGC::Compute)
|
||||
{
|
||||
SETUP_FUNCTION(StereoGC)
|
||||
|
||||
try {
|
||||
// Get the arguments
|
||||
|
||||
// Arg 0, the 'left' image
|
||||
Matrix* m0 = ObjectWrap::Unwrap<Matrix>(args[0]->ToObject());
|
||||
cv::Mat left = m0->mat;
|
||||
|
||||
// Arg 1, the 'right' image
|
||||
Matrix* m1 = ObjectWrap::Unwrap<Matrix>(args[1]->ToObject());
|
||||
cv::Mat right = m1->mat;
|
||||
|
||||
// Compute stereo using the block matching algorithm
|
||||
CvMat left_leg = left, right_leg = right;
|
||||
CvMat *disp_left = cvCreateMat(left.rows, left.cols, CV_16S), *disp_right = cvCreateMat(right.rows, right.cols, CV_16S);
|
||||
cvFindStereoCorrespondenceGC(&left_leg, &right_leg, disp_left, disp_right, self->stereo, 0);
|
||||
|
||||
cv::Mat disp16 = disp_left;
|
||||
cv::Mat disparity(disp16.rows, disp16.cols, CV_8U);
|
||||
disp16.convertTo(disparity, CV_8U, -16);
|
||||
|
||||
// Wrap the returned disparity map
|
||||
Local<Object> disparityWrap = NanNew(Matrix::constructor)->GetFunction()->NewInstance();
|
||||
Matrix *disp = ObjectWrap::Unwrap<Matrix>(disparityWrap);
|
||||
disp->mat = disparity;
|
||||
|
||||
NanReturnValue(disparityWrap);
|
||||
|
||||
} catch (cv::Exception &e) {
|
||||
const char *err_msg = e.what();
|
||||
NanThrowError(err_msg);
|
||||
NanReturnUndefined();
|
||||
}
|
||||
|
||||
};
|
||||
58
src/Stereo.h
Normal file
58
src/Stereo.h
Normal file
@ -0,0 +1,58 @@
|
||||
#ifndef __NODE_STEREO_H
|
||||
#define __NODE_STEREO_H
|
||||
|
||||
#include "OpenCV.h"
|
||||
|
||||
class StereoBM: public node::ObjectWrap {
|
||||
public:
|
||||
cv::StereoBM stereo;
|
||||
|
||||
static Persistent<FunctionTemplate> constructor;
|
||||
static void Init(Handle<Object> target);
|
||||
static NAN_METHOD(New);
|
||||
|
||||
StereoBM(int preset = cv::StereoBM::BASIC_PRESET, int ndisparities = 0, int SADWindowSize=21);
|
||||
|
||||
JSFUNC(Compute);
|
||||
};
|
||||
|
||||
class StereoSGBM: public node::ObjectWrap {
|
||||
public:
|
||||
cv::StereoSGBM stereo;
|
||||
|
||||
static Persistent<FunctionTemplate> constructor;
|
||||
static void Init(Handle<Object> target);
|
||||
static NAN_METHOD(New);
|
||||
|
||||
StereoSGBM();
|
||||
StereoSGBM(int minDisparity,
|
||||
int ndisparities,
|
||||
int SADWindowSize,
|
||||
int p1 = 0,
|
||||
int p2 = 0,
|
||||
int disp12MaxDiff = 0,
|
||||
int preFilterCap = 0,
|
||||
int uniquenessRatio = 0,
|
||||
int speckleWindowSize = 0,
|
||||
int speckleRange = 0,
|
||||
bool fullDP = false);
|
||||
|
||||
JSFUNC(Compute);
|
||||
};
|
||||
|
||||
struct CvStereoGCState;
|
||||
|
||||
class StereoGC: public node::ObjectWrap {
|
||||
public:
|
||||
CvStereoGCState *stereo;
|
||||
|
||||
static Persistent<FunctionTemplate> constructor;
|
||||
static void Init(Handle<Object> target);
|
||||
static NAN_METHOD(New);
|
||||
|
||||
StereoGC(int numberOfDisparities = 16, int maxIterations = 2);
|
||||
|
||||
JSFUNC(Compute);
|
||||
};
|
||||
|
||||
#endif
|
||||
11
src/init.cc
11
src/init.cc
@ -9,7 +9,9 @@
|
||||
#include "HighGUI.h"
|
||||
#include "FaceRecognizer.h"
|
||||
#include "Constants.h"
|
||||
|
||||
#include "Calib3D.h"
|
||||
#include "ImgProc.h"
|
||||
#include "Stereo.h"
|
||||
|
||||
extern "C" void
|
||||
init(Handle<Object> target) {
|
||||
@ -21,9 +23,14 @@ init(Handle<Object> target) {
|
||||
CascadeClassifierWrap::Init(target);
|
||||
VideoCaptureWrap::Init(target);
|
||||
Contour::Init(target);
|
||||
TrackedObject::Init(target);
|
||||
TrackedObject::Init(target);
|
||||
NamedWindow::Init(target);
|
||||
Constants::Init(target);
|
||||
Calib3D::Init(target);
|
||||
ImgProc::Init(target);
|
||||
StereoBM::Init(target);
|
||||
StereoSGBM::Init(target);
|
||||
StereoGC::Init(target);
|
||||
|
||||
|
||||
#if CV_MAJOR_VERSION >= 2 && CV_MINOR_VERSION >=4
|
||||
|
||||
21
test/examples.js
Normal file
21
test/examples.js
Normal file
@ -0,0 +1,21 @@
|
||||
var test = require('tape')
|
||||
, glob = require('glob')
|
||||
, exec = require('child_process').exec
|
||||
, path = require('path')
|
||||
|
||||
module.exports = function(){
|
||||
|
||||
glob.sync('./examples/*.js').forEach(function(example){
|
||||
test("Example: " + example, function(assert){
|
||||
|
||||
var fullName = path.resolve(example)
|
||||
, examples = path.resolve('./examples')
|
||||
|
||||
exec('node ' + fullName, {cwd: examples}, function(error, stdout, stderr){
|
||||
assert.error(error)
|
||||
assert.end()
|
||||
})
|
||||
})
|
||||
})
|
||||
|
||||
}
|
||||
@ -275,3 +275,7 @@ test("fonts", function(t) {
|
||||
});
|
||||
})
|
||||
|
||||
// Test the examples folder.
|
||||
require('./examples')()
|
||||
|
||||
|
||||
|
||||
13
utils/opencv_x64.pc
Normal file
13
utils/opencv_x64.pc
Normal file
@ -0,0 +1,13 @@
|
||||
# Package Information for pkg-config
|
||||
opencv_prefix=C:/OpenCV249/opencv/build/x64/vc12
|
||||
exec_prefix=${opencv_prefix}/bin
|
||||
libdir=${opencv_prefix}/lib
|
||||
includedir=C:/OpenCV249/opencv/build/include
|
||||
|
||||
Name: OpenCV
|
||||
Description: Open Source Computer Vision Library
|
||||
Version: 2.4.9
|
||||
|
||||
Cflags: ${includedir} ${includedir}/opencv
|
||||
|
||||
Libs: ${libdir}/opencv_calib3d249 ${libdir}/opencv_contrib249 ${libdir}/opencv_core249 ${libdir}/opencv_features2d249 ${libdir}/opencv_flann249 ${libdir}/opencv_gpu249 ${libdir}/opencv_highgui249 ${libdir}/opencv_imgproc249 ${libdir}/opencv_legacy249 ${libdir}/opencv_ml249 ${libdir}/opencv_nonfree249 ${libdir}/opencv_objdetect249 ${libdir}/opencv_ocl249 ${libdir}/opencv_photo249 ${libdir}/opencv_stitching249 ${libdir}/opencv_superres249 ${libdir}/opencv_ts249 ${libdir}/opencv_video249 ${libdir}/opencv_videostab249
|
||||
12
utils/opencv_x86.pc
Normal file
12
utils/opencv_x86.pc
Normal file
@ -0,0 +1,12 @@
|
||||
# Package Information for pkg-config
|
||||
opencv_prefix=C:/OpenCV249/opencv/build/x86/vc12
|
||||
exec_prefix=${opencv_prefix}/bin
|
||||
libdir=${opencv_prefix}/lib
|
||||
includedir=C:/OpenCV249/opencv/build/include
|
||||
|
||||
Name: OpenCV
|
||||
Description: Open Source Computer Vision Library
|
||||
Version: 2.4.9
|
||||
|
||||
Cflags: ${includedir} ${includedir}/opencv
|
||||
Libs: ${libdir}/opencv_calib3d249 ${libdir}/opencv_contrib249 ${libdir}/opencv_core249 ${libdir}/opencv_features2d249 ${libdir}/opencv_flann249 ${libdir}/opencv_gpu249 ${libdir}/opencv_highgui249 ${libdir}/opencv_imgproc249 ${libdir}/opencv_legacy249 ${libdir}/opencv_ml249 ${libdir}/opencv_nonfree249 ${libdir}/opencv_objdetect249 ${libdir}/opencv_ocl249 ${libdir}/opencv_photo249 ${libdir}/opencv_stitching249 ${libdir}/opencv_superres249 ${libdir}/opencv_ts249 ${libdir}/opencv_video249 ${libdir}/opencv_videostab249
|
||||
Loading…
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Reference in New Issue
Block a user