opencv_4

Description:

opencv 4

OpenCV_4
This package contains the implementation of OpenCV modules, the version used is 4.3.0 for both Android and iOS platforms.



















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Table of contents #

About this version
Installing
How to use
Examples

Image Filtering
Miscellaneous Image Transformations
Color Space Conversions
Color Maps


Bugs or Requests
Donate

About this version #
Compatibility #

It is developed for the integration of the OpenCV artificial vision library in its version 4.3.0
It is compatible with Android and iOS.
Easy integration with popular flutter packages like image_picker was kept in mind, to process images from gallery or camera, you can see the implementation example here, in this case you need to configure the flutter project with Nullsafety..
The implemented OpenCV modules are the following:

Image Processing

Image Filtering

bilateralFilter
blur
boxFilter
dilate
erode
filter2D
gaussianBlur
laplacian
medianBlur
morphologyEx
pyrDown
pyrMeanShiftFiltering
pyrUp
scharr
sobel
sqrBoxFilter


Miscellaneous Image Transformations

adaptiveThreshold
distanceTransform
threshold


Color Space Conversions

cvtColor


ColorMaps in OpenCV

applyColorMap







Image processing #

All processing is through the image string path.
Images in flutter through the asset folder configured in the pubspect.yaml file. Default
Images in URLs.
Images from gallery or camera using image_picker

Syntax #

Similar to Python for method calls and image processing constants for example

Cv2.ctvColor
Cv2.COLOR_BGR2GRAY




Installing #
1. Depend on it #
Add this to your package's pubspec.yaml file:
dependencies:
opencv_4: ^1.0.0
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2. Install it #
You can install packages from the command line:
with Flutter:
$ flutter pub get
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3. Import it #
Now in your Dart code, you can use:
import 'package:opencv_4/opencv_4.dart';
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How to use #
Pre requirements #

Android: requires the minimum version 21 in your project android (folder) -> app (folder) -> build.gradle

defaultConfig {
...
minSdkVersion 21
...
}
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If you are going to work with the asset path, flutter does not require permissions in Android and iOS.
If you want to work with images from URLs, no configuration is required.
If the image_picker package is to be used to work with images from the camera and gallery, follow your permission settings for Android and iOS.
Nullsafety If you are going to test the example you need to configure pubspect.yaml

environment:
sdk: ">=2.12.0 <3.0.0"
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Classes #
Cv2: Class that contains the implementation of OpenCV modules
CVPathFrom: Allows you to configure the path to process the images

URL (static constant) configure opencv for web images
GALLERY_CAMERA (static constant) configure opencv for images obtained from the image_picker package
ASSETS (static constant) configure opencv for flutter images in pubspect.yaml --> assets/test.jpg

Module: Image Filtering #
Imagen original




from my behance acount
Some examples
Bilateral Filter #
Must be called within a async function


Uint8List _byte = await Cv2.bilateralFilter(
pathFrom: CVPathFrom.ASSETS,
pathString: 'assets/Test.JPG',
diameter: 20,
sigmaColor: 75,
sigmaSpace: 75,
borderType: Cv2.BORDER_DEFAULT,
);

setState(() {
_byte;
});

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Show result in an image widget
Image.memory(
_byte,
width: 300,
height: 300,
fit: BoxFit.fill,
)
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Note: If you want to process an image from the web you must configure pathFrom: CVPathFrom.URL replace in pathString with a URL, for example. pathString: 'https://mir-s3-cdn-cf.behance.net/project_modules/fs/313f8e114930481.6044f05fcd866.jpeg'
Dilate #



Uint8List _byte = await Cv2.dilate(
pathFrom: CVPathFrom.ASSETS,
pathString: 'assets/Test.JPG',
kernelSize: [3, 3],
);

setState(() {
_byte;
});




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Filter2D #


Uint8List _byte = await Cv2.filter2D(
pathFrom: CVPathFrom.URL,
pathString:
'https://mir-s3-cdn-cf.behance.net/project_modules/max_1200/634dba114930481.6044f05fcb2dd.jpeg',
outputDepth: -1,
kernelSize: [2, 2],
);

setState(() {
_byte;
});

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Median Blur #



Uint8List _byte = await Cv2.medianBlur(
pathFrom: CVPathFrom.URL,
pathString:
'https://mir-s3-cdn-cf.behance.net/project_modules/max_1200/16fe9f114930481.6044f05fca574.jpeg',
kernelSize: 19,
);

setState(() {
_byte;
});

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MorphologyEx #



Uint8List _byte = await Cv2.morphologyEx(
pathFrom: CVPathFrom.URL,
pathString:
'https://mir-s3-cdn-cf.behance.net/project_modules/fs/c7da51114930481.6044f05fcc76a.jpeg',
operation: Cv2.MORPH_TOPHAT,
kernelSize: [5, 5],
);

setState(() {
_byte;
});
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PyrMeanShiftFiltering #




Uint8List _byte = await Cv2.pyrMeanShiftFiltering(
pathFrom: CVPathFrom.ASSETS,
pathString: 'assets/Test.JPG',
spatialWindowRadius: 20,
colorWindowRadius: 20,
);

setState(() {
_byte;
});


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Scharr #



Uint8List _byte = await Cv2.scharr(
pathFrom: CVPathFrom.ASSETS,
pathString: 'assets/Test.JPG',
depth: Cv2.CV_SCHARR,
dx: 0,
dy: 1,
);

setState(() {
_byte;
});


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Module: Miscellaneous Image Transformations #
Threshold #



Uint8List _byte = await Cv2.threshold(
pathFrom: CVPathFrom.ASSETS,
pathString: 'assets/Test.JPG',
thresholdValue: 150,
maxThresholdValue: 200,
thresholdType: Cv2.THRESH_BINARY,
);

setState(() {
_byte;
});


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AdaptiveThreshold #



Uint8List _byte = await Cv2.adaptiveThreshold(
pathFrom: CVPathFrom.ASSETS,
pathString: 'assets/Test.JPG',
maxValue: 125,
adaptiveMethod: Cv2.ADAPTIVE_THRESH_MEAN_C,
thresholdType: Cv2.THRESH_BINARY,
blockSize: 11,
constantValue: 12,
);

setState(() {
_byte;
});
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Module: Color Space Conversions #
CvtColor #



Uint8List _byte = await Cv2.cvtColor(
pathFrom: CVPathFrom.ASSETS,
pathString: 'assets/Test.JPG',
outputType: Cv2.COLOR_BGR2GRAY,
);

setState(() {
_byte;
});


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Module: Color Maps #
ApplyColorMap #



Uint8List _byte = await Cv2.applyColorMap(
pathFrom: CVPathFrom.URL,
pathString:
'https://mir-s3-cdn-cf.behance.net/project_modules/max_1200/16fe9f114930481.6044f05fca574.jpeg?raw=true',
colorMap: Cv2.COLORMAP_JET,
);

setState(() {
_byte;
});


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Bugs or Requests #
Please file feature requests and bugs at the issue tracker.
Donate #
To give you a better solution.


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