The OpenCV SDK for Dart is a powerful and versatile computer vision library that allows developers to integrate OpenCV functionality into their Dart applications. This SDK provides a bridge between Dart and the OpenCV library, enabling you to leverage advanced computer vision techniques seamlessly.
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High-Performance: Benefit from the high-performance capabilities of the OpenCV library directly from your Dart applications.
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Wide Range of Algorithms: Access a comprehensive collection of image processing and computer vision algorithms, including filtering, feature detection, object tracking, and more.
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Easy Integration: The SDK provides a user-friendly interface to easily integrate OpenCV functionalities into your Dart projects.
TODO:
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Image Reading and Writing:
- Read image:
imread() - Write image:
imwrite()
- Read image:
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Image Properties:
- Get image size:
size() - Determine image type:
type() - Access and modify pixel values on the image:
at(),set()
- Get image size:
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Morphological Operation:
- Eroding
- Dilate
- Eroding
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Color Conversions:
- Convert color spaces:
cvtColor()for grayscale - Define constants for color space conversions:
COLOR_*
- Convert color spaces:
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Filtering and Edge Detection:
- Gaussian blur:
GaussianBlur() - Average blur:
Average() - Bileteral blur:
Bileteral() - Average blur:
Average() - Median blur:
medianBlur()
- Gaussian blur:
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Edge Detection:
- Edge detection:
Canny() - Laplace:
Laplace() - Sobel:
Sobel()
- Edge detection:
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Geometric Transformations:
- Perspective transformation:
warpPerspective() - Scaling:
resize() - Rotation:
rotate()
- Perspective transformation:
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Hough Detection Transformations:
- Hough Circle:
- Hough Line:
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Template Matching:
- Template matching operation:
matchTemplate()
- Template matching operation:
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Contour Detection:
- Contour detection:
findContours() - Compute contour properties:
contourArea(),arcLength(),boundingRect()
- Contour detection:
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Object Detection:
- Face detection:
CascadeClassifier() - Object detection:
detectMultiScale()
- Face detection:
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Computational Operations:
- Mathematical operations:
add(),subtract(),multiply(),divide() - Histogram calculation:
calcHist()
- Mathematical operations:
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Image Processing Helpers:
- Bitwise masking operations:
bitwise_and(),bitwise_or(),bitwise_not() - Splitting and merging images:
split(),merge() - Defining Regions of Interest (ROI):
Rect()
- Bitwise masking operations:
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Graphical User Interface (GUI) Helpers:
- Display image on the screen:
imshow() - Detect keyboard or mouse interactions:
waitKey()
- Display image on the screen:
TODO: Include short and useful examples for package users. Add longer examples
to /example folder.