31:T485,sample = (background, input, targetId) => { const bg_image = new Image(); bg_image.src = URL.createObjectURL(background); const image = new Image(); image.src = URL.createObjectURL(input); image.onload = function() { const { cv } = window; // Source and destination images const contour_src = new cv.imread(image); const ct_scan = new cv.imread(bg_image); // Convert to binary cv.cvtColor(contour_src, contour_src, cv.COLOR_RGBA2GRAY, 0); cv.threshold(contour_src, contour_src, 120, 200, cv.THRESH_BINARY); // Find contours let contours = new cv.MatVector(); let hierarchy = new cv.Mat(); cv.findContours(contour_src, contours, hierarchy, cv.RETR_CCOMP, cv.CHAIN_APPROX_SIMPLE); // Draw contours on destination image for (let i = 0; i < contours.size(); ++i) { let color = new cv.Scalar(0, 255, 0, 255); cv.drawContours(ct_scan, contours, i, color, 1, cv.LINE_8, hierarchy, 160); } // Show result and clean up cv.imshow(targetId, ct_scan); contour_src.delete(); ct_scan.delete(); contours.delete(); hierarchy.delete(); }; }32:Ted2,surfaceDiceHighlight = (background, input, targetId) => { const bg_image = new Image(); bg_image.src = URL.createObjectURL(background); const image = new Image(); image.src = URL.createObjectURL(input); image.onload = function() { const { cv } = window; // Source and destination images const contour_src = new cv.imread(image); const ct_scan = new cv.imread(bg_image); cv.imshow(targetId, ct_scan); // Convert to binary cv.cvtColor(contour_src, contour_src, cv.COLOR_RGBA2GRAY, 0); cv.threshold(contour_src, contour_src, 120, 200, cv.THRESH_BINARY); // Find contours let contours = new cv.MatVector(); let hierarchy = new cv.Mat(); cv.findContours(contour_src, contours, hierarchy, cv.RETR_CCOMP, cv.CHAIN_APPROX_SIMPLE); // Draw contours on destination image let contour_img_for_distance = cv.Mat.ones(contour_src.cols, contour_src.rows, cv.CV_8UC1); let contour_img_for_coloring = new cv.Mat(contour_src.cols, contour_src.rows, cv.CV_8UC4, new cv.Scalar(0,0,0,255)); let color = new cv.Scalar(0, 255, 0, 255); let color2 = new cv.Scalar(0); let color3 = new cv.Scalar(255, 255, 255, 255); cv.drawContours(ct_scan, contours, -1, color, 1, cv.LINE_8, hierarchy, 160); cv.drawContours(contour_img_for_distance, contours, -1, color2, 1, cv.LINE_8, hierarchy, 160); cv.drawContours(contour_img_for_coloring, contours, -1, color3, 1, cv.LINE_8, hierarchy, 160); // Calculate distance transform let dist = new cv.Mat(contour_src.cols, contour_src.rows, cv.CV_8UC1); console.log('contour_img_for_distance type: ' +type2str(contour_img_for_distance.type())); console.log('dist type before: ' +type2str(dist.type())); cv.distanceTransform(contour_img_for_distance, dist, cv.DIST_L2, 3); console.log('dist type after: ' +type2str(dist.type())); let threshold = new cv.Mat(contour_src.cols, contour_src.rows, cv.CV_8UC1); console.log('threshold type before: ' +type2str(dist.type())); cv.threshold(dist, threshold, distance_threshold, 255, cv.THRESH_BINARY_INV); console.log('threshold type after: ' +type2str(dist.type())); let imgNormalize = new cv.Mat(contour_src.cols, contour_src.rows, cv.CV_8UC1); cv.normalize(threshold, imgNormalize, 0, 1.0, cv.NORM_MINMAX); // console.log(type2str(imgNormalize.type())); console.log('imgNormalize type before: ' + type2str(imgNormalize.type())); cv.cvtColor(imgNormalize, imgNormalize, cv.COLOR_HSV2RGBA); console.log('imgNormalize type after: ' + type2str(imgNormalize.type())); // imgNormalize.convertTo(imgNormalize, cv.CV_8UC4); // console.log(type2str(imgNormalize.type())); // cv.cvtColor(imgNormalize, imgNormalize, cv.COLOR_GRAY2RGB); // console.log(type2str(imgNormalize.type())); let diff = new cv.Mat(contour_src.cols, contour_src.rows, cv.CV_8UC4, new cv.Scalar(0,0,0,255)); // console.log(type2str(contour_img_for_coloring.type())); // cv.cvtColor(contour_img_for_coloring, contour_img_for_coloring, cv.COLOR_RGB2RGBA); // console.log(type2str(contour_img_for_coloring.type())); // cv.cvtColor(imgNormalize, imgNormalize, cv.COLOR_GRAY2RGB); // console.log(type2str(imgNormalize.type())); // cv.absdiff(contour_img_for_coloring, imgNormalize, diff); // Show result and clean up cv.imshow(targetId, imgNormalize); contour_src.delete(); ct_scan.delete(); contours.delete(); hierarchy.delete(); contour_img_for_distance.delete(); dist.delete(); threshold.delete(); imgNormalize.delete(); diff.delete(); // mask.delete(); contour_img_for_coloring.delete(); }; }33:[] 2f:{"title":"Loading local image files examples","cells":[{"id":46,"value":"md`# Loading local image files examples`","pinned":true,"hidden":false,"mode":"ojs"},{"id":33,"value":"md`## Load all files in folder`","pinned":true,"hidden":false,"mode":"ojs"},{"id":298,"value":"viewof multiFiles = html`` //load segmentation slices for this case","pinned":false,"hidden":false,"mode":"ojs"},{"id":300,"value":"multiFileList = Array.from(multiFiles);","pinned":false,"hidden":false,"mode":"ojs"},{"id":303,"value":"multiFileDict = {\n var result = {};\n \n multiFileList.forEach(function(f) { \n var name = f.name;\n var path = f.webkitRelativePath;\n var subdir = f.webkitRelativePath.match(/variations_decathlon_dataset\\/(.*)\\//i)[1];\n var caseNr = parseInt(f.name.match(/Case([0-9]+)_/i)[1]);\n var slice = parseInt(f.name.match(/Case[0-9]+[a-zA-Z_]+([0-9]+)/i)[1]);\n \n if (result[subdir] === undefined) { \n result[subdir] = [];\n }\n if (result[subdir][caseNr] === undefined) {\n result[subdir][caseNr] = [];\n }\n result[subdir][caseNr][slice] = {\n name: name,\n path: subdir,\n file: f\n }; \n })\n return result;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":111,"value":"numberOfCases = Object.keys(multiFileDict[\"images\"]).length","pinned":false,"hidden":false,"mode":"ojs"},{"id":276,"value":"numberOfSlices = Object.keys(multiFileDict[\"images\"][caseNo]).length","pinned":false,"hidden":false,"mode":"ojs"},{"id":194,"value":"viewof caseSlider = html``","pinned":false,"hidden":false,"mode":"ojs"},{"id":311,"value":"caseNo = Object.keys(multiFileDict.images)[caseSlider];","pinned":false,"hidden":false,"mode":"ojs"},{"id":106,"value":"viewof sliceNo = html``","pinned":false,"hidden":false,"mode":"ojs"},{"id":108,"value":"sliceNo\n","pinned":false,"hidden":false,"mode":"ojs"},{"id":460,"value":"canvasses = unsafe_html`\n

\n\n

`","pinned":true,"hidden":false,"mode":"ojs"},{"id":374,"value":"loadImage = function(subDir, caseNo, sliceNo) {\n if (multiFileDict[subDir][caseNo] != undefined &&\n multiFileDict[subDir][caseNo][sliceNo] != undefined) {\n var file = multiFileDict[subDir][caseNo][sliceNo].file;\n if (file != undefined) {\n return file;\n }\n }\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":418,"value":"{\n sample(loadImage(\"images\", caseNo, sliceNo), loadImage(\"segmentations_without_variations\", caseNo, sliceNo), 'swv');\n sample(loadImage(\"images\", caseNo, sliceNo), loadImage(\"segmentations_with_shifts_5\", caseNo, sliceNo), 'sws');\n sample(loadImage(\"images\", caseNo, sliceNo), loadImage(\"segmentations_bottom_over_under_segment_10\", caseNo, sliceNo), 'sbo')\n sample(loadImage(\"images\", caseNo, sliceNo), loadImage(\"segmentations_top_over_under_segment_10\", caseNo, sliceNo), 'sto')\n sample(loadImage(\"images\", caseNo, sliceNo), loadImage(\"segmentations_with_erosion_dilation_5\", caseNo, sliceNo), 'swe')\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":372,"value":"$31","pinned":false,"hidden":false,"mode":"ojs"},{"id":616,"value":"unsafe_html`

`","pinned":true,"hidden":false,"mode":"ojs"},{"id":623,"value":"distance_threshold = 1","pinned":true,"hidden":false,"mode":"ojs"},{"id":619,"value":"surfaceDiceHighlight(loadImage(\"images\", caseNo, sliceNo), loadImage(\"segmentations_without_variations\", caseNo, sliceNo), 'surfaceDice')","pinned":true,"hidden":false,"mode":"ojs"},{"id":612,"value":"$32","pinned":false,"hidden":false,"mode":"ojs"},{"id":715,"value":"type2str = function(type) {\n const { cv } = window;\n \n let r;\n\n let depth = type & cv.CV_MAT_DEPTH_MASK;\n let chans = 1 + (type >> cv.CV_CN_SHIFT);\n\n switch ( depth ) {\n case cv.CV_8U: r = \"8U\"; break;\n case cv.CV_8S: r = \"8S\"; break;\n case cv.CV_16U: r = \"16U\"; break;\n case cv.CV_16S: r = \"16S\"; break;\n case cv.CV_32S: r = \"32S\"; break;\n case cv.CV_32F: r = \"32F\"; break;\n case cv.CV_64F: r = \"64F\"; break;\n default: r = \"User\"; break;\n }\n\n r += \"C\";\n r += (chans+'0');\n\n return r;\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":369,"value":"loadOpenCv = {\n return new Promise((resolve, reject) => {\n const script = document.createElement('script');\n script.src = 'https://docs.opencv.org/master/opencv.js';\n script.type = 'text/javascript';\n script.async = true;\n\n script.onabort = () => {\n reject('OpenCV Load failed.');\n };\n\n script.onload = () => {\n if (window.cv !== undefined) {\n resolve('OpenCV Load success.');\n }\n };\n \n document.body.appendChild(script);\n });\n}","pinned":false,"hidden":false,"mode":"ojs"},{"id":777,"value":"import {html, svg} from \"@observablehq/htl\"","pinned":true,"hidden":false,"mode":"ojs"},{"id":786,"value":"function unsafe_html() {\n const span = document.createElement(\"span\");\n span.innerHTML = String.raw.apply(this, arguments);\n return span;\n}","pinned":true,"hidden":false,"mode":"ojs"}],"files":"$W33","stdlib":"1","titling":"auto"}