A image library combines OpenCV and NumSharp together. SharpCV returns Mat object with NDArray supported, which makes it easier to do data manipulation like slicing.
Install OpenCV prebuild binary
PM> Install-Package SharpCV
PM> Install-Package OpenCvSharp4.runtime.winImport SharpCV and OpenCV library
using SharpCV;
using static SharpCV.Binding;Interact with NDArray
NDArray kernel = new float[,]
{
{ 0, -1, 0 },
{ -1, 5, -1 },
{ 0, -1, 0 }
};
var mat = new Mat(kernel);
Assert.AreEqual((3, 3), mat.shape);
Assert.AreEqual(kernel[0], mat.data[0]); // { 0, -1, 0 }
Assert.AreEqual(kernel[1], mat.data[1]); // { -1, 5, -1 }
Assert.AreEqual(kernel[2], mat.data[2]); // { 0, -1, 0 }Pixel level access
var img = cv2.imread(imgSolar, IMREAD_COLOR.IMREAD_GRAYSCALE);
byte p = img[8, 8];
Assert.AreEqual(18, p);
img = cv2.imread(imgSolar);
var (b, g, r) = img[8, 8];
Assert.AreEqual((32, 19, 11), (b, g, r));Convert to black and white image
var img = cv2.imread("solar.jpg");
var gray = cv2.cvtColor(img, ColorConversionCodes.COLOR_RGB2GRAY);
var (ret, binary) = cv2.threshold(gray, 0, 255, ThresholdTypes.THRESH_BINARY | ThresholdTypes.THRESH_TRIANGLE);
cv2.imshow("black and white", binary);
cv2.waitKey(0);Video capture from file or camera
var vid = cv2.VideoCapture("road.mp4");
var (loaded, frame) = vid.read();
while (loaded)
{
(loaded, frame) = vid.read();
cv2.imshow("video", frame);
}If you want to learn more about the API implementation, please refer to the official documentation.