2b:null 2c:["$","title",null,{"children":"Hough Circle Transforms | johnwelford | Observable"}] 31:Te2e,circles = { const cv = window.cv; // BUG!!! This will need to be reevaluated after loadOpenCv returns successfully const src = cv.imread(image); // load source const grey = src.clone(); // setup greyscale image const blur = src.clone(); // setup blurred image const canny = src.clone(); // setup canny edge detected image // parameters const ksize = new cv.Size(3, 3); // blurring kernel size const sigma = [0, 0]; // gaussian kernal standard deviation [x, y] const borderType = cv.BORDER_DEFAULT; // blur pixel extrapolation method const method = cv.HOUGH_GRADIENT; // circle detection method, only this one is implemented in OpenCV const dp = 1.1; // Resolution of the accumulator array. Votes cast are binned into squares set by dp size. Set too small and only perfect circles are found, set too high and noise collaborates to vote for non-circles. const minDist = 12; // Minimum distance between the center (x, y) coordinates of detected circles. If the minDist is too small, multiple circles in the same neighborhood as the original may be (falsely) detected. If the minDist is too large, then some circles may not be detected at all. const param1 = 190; // a number forwarded to the Canny edge detector (applied to a grayscale image) that represents the threshold1 passed to Canny(...). Canny uses that number to guide edge detection const param2 = 14; // Accumulator threshold value for the cv2.HOUGH_GRADIENT method. The smaller the threshold is, the more circles will be detected (including false circles). The larger the threshold is, the more circles will potentially be returned. const minRadius = 2; // Minimum size of the radius in pixels. Don't set minRadius and maxRadius far apart unless you want all possible circles that might be found in that range. If unknown, put zero as default. const maxRadius = 14; // Maximum size of the radius (in pixels). Don't set minRadius and maxRadius far apart unless you want all possible circles found in that range. If unknown, put zero as default. // convert input to greyscale cv.cvtColor(src, grey, cv.COLOR_RGBA2GRAY, 0); cv.imshow('greyscale', grey); // blur image cv.GaussianBlur(grey, blur, ksize, sigma[0], sigma[1], borderType); cv.imshow('blur', blur); // perform edge detection (for display only, incorporated within HoughCircles algorithm already) cv.Canny(blur, canny, param1/2, param1, 3, false); cv.imshow('edges', canny); // find circles const circles = new cv.Mat(); // setup circles vector cv.HoughCircles(blur, circles, method, dp, minDist, param1, param2, minRadius, maxRadius); // draw circles const color = [255, 0, 0, 255]; // colour for drawing circles const thickness = 1; // thickness to draw circles, negative values mean filled const lineType = 8; // '8-connected' line const shift = 0; // Number of fractional bits in the coordinates of the center and in the radius value. const dst = cv.Mat.zeros(src.rows, src.cols, cv.CV_8U); // setup output image let circleOut = []; // store circle details for (let i = 0; i < circles.cols; ++i) { let x = circles.data32F[i * 3]; let y = circles.data32F[i * 3 + 1]; let radius = circles.data32F[i * 3 + 2]; let center = new cv.Point(x, y); circleOut.push({x: x, y: y, radius: radius}); cv.circle(src, center, radius, color, thickness, lineType, shift); // outline cv.circle(src, center, 1, [0, 255, 0, 255], -1, lineType, shift); } cv.imshow('output', src); src.delete(); dst.delete(); circles.delete(); grey.delete(); blur.delete(); canny.delete(); return circleOut; }32:[] 2f:{"id":"5fe133f7f6dd5af8","slug":"hough-circle-transforms","title":"Hough Circle Transforms","thumbnail":"8c8eca1955e9f16f63ee3731817ebd1d0a7d787332f8ca2323a51402ac1f64ff","access_level":"public","create_time":"$D2020-06-19T08:16:52.500Z","update_time":"$D2020-06-21T04:14:05.579Z","view_time":null,"first_public_time":"$D2020-06-19T12:31:47.655Z","fork":{"id":"9acacb2d19e303f7","slug":"opencv","title":"OpenCV","owner":{"id":"2a278c3908e45a90","login":"fengyfei","name":"Feng Yifei"}},"stars":0,"starred":false,"owner":{"type":"team","id":"6c1f25ef90c27e9b","login":"johnwelford","name":"","avatar_url":"https://avatars-next.observableusercontent.com/3bfe9ac5315b1340bf914c84d1ed0ae174327f3802f4ba068fcaa4c223cfb471","tier":"starter_2024"},"version":643,"publish_version":643,"role":null,"authored":false,"authors":[{"type":"individual","id":"629158c5ced3958f","login":"johnwelford","name":"","avatar_url":"https://avatars-next.observableusercontent.com/3bfe9ac5315b1340bf914c84d1ed0ae174327f3802f4ba068fcaa4c223cfb471","tier":null}],"members":[{"type":"individual","id":"629158c5ced3958f","login":"johnwelford","name":"","avatar_url":"https://avatars-next.observableusercontent.com/3bfe9ac5315b1340bf914c84d1ed0ae174327f3802f4ba068fcaa4c223cfb471","tier":null,"role":"editor"}],"comments":[],"custom_thumbnail":false,"trashed":false,"lapsed":null,"subscribed":null,"forks":4,"collection":null,"type":"notebook","body":{"title":"Hough Circle Transforms","cells":[{"id":0,"value":"md`# Hough Circle Transforms\n\nUsing OpenCV.\n\nSource image:`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":315,"value":"image = new Promise((resolve, reject) => {\n const image = new Image;\n image.crossOrigin = \"anonymous\";\n image.src = \"https://encrypted-tbn0.gstatic.com/images?q=tbn%3AANd9GcT649X2B1_6s2aEvaKuOpwnUeWr3FA_IMLqOmOBdU4QOwCC3I53&usqp=CAU\";\n image.onload = () => resolve(image);\n image.onerror = reject;\n})","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":229,"value":"html`\n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n \n

Greyscale:	Blur:

Edges:	Output:

`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":378,"value":"$31","pinned":true,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":5,"value":"md`\n## Imports\n`","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"},{"id":19,"value":"loadOpenCv = {\n return new Promise((resolve, reject) => {\n const script = document.createElement('script');\n script.src = 'https://docs.opencv.org/master/opencv.js';\n script.type = 'text/javascript';\n script.async = true;\n\n script.onabort = () => {\n reject('OpenCV Load failed.');\n };\n\n script.onload = () => {\n if (window.cv !== undefined) {\n resolve('OpenCV Load success.');\n }\n };\n document.body.appendChild(script);\n });\n}","pinned":false,"hidden":false,"mode":"ojs","author":"$undefined","summary":"$undefined","output":"$undefined","database":"$undefined"}],"files":"$W32","stdlib":"1","titling":"auto"}} 30:"$2f:body"