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| /* | |
| Magic wand tool (fuzzy selection) by color | |
| @package magic-wand-tool | |
| @author Ryasnoy Paul <[email protected]> | |
| @version 1.1.4 | |
| @license MIT | |
| @copyright (c) 2014-2019, Ryasnoy Paul <[email protected]> | |
| */ | |
| MagicWand = (function () { | |
| var lib = {}; | |
| /** Create a binary mask on the image by color threshold | |
| * Algorithm: Scanline flood fill (http://en.wikipedia.org/wiki/Flood_fill) | |
| * @param {Object} image: {Uint8Array} data, {int} width, {int} height, {int} bytes | |
| * @param {int} x of start pixel | |
| * @param {int} y of start pixel | |
| * @param {int} color threshold | |
| * @param {Uint8Array} mask of visited points (optional) | |
| * @param {boolean} [includeBorders=false] indicate whether to include borders pixels | |
| * @return {Object} mask: {Uint8Array} data, {int} width, {int} height, {Object} bounds | |
| */ | |
| lib.floodFill = function(image, px, py, colorThreshold, mask, includeBorders) { | |
| return includeBorders | |
| ? floodFillWithBorders(image, px, py, colorThreshold, mask) | |
| : floodFillWithoutBorders(image, px, py, colorThreshold, mask); | |
| }; | |
| function floodFillWithoutBorders(image, px, py, colorThreshold, mask) { | |
| var c, x, newY, el, xr, xl, dy, dyl, dyr, checkY, | |
| data = image.data, | |
| w = image.width, | |
| h = image.height, | |
| bytes = image.bytes, // number of bytes in the color | |
| maxX = -1, minX = w + 1, maxY = -1, minY = h + 1, | |
| i = py * w + px, // start point index in the mask data | |
| result = new Uint8Array(w * h), // result mask | |
| visited = new Uint8Array(mask ? mask : w * h); // mask of visited points | |
| if (visited[i] === 1) return null; | |
| i = i * bytes; // start point index in the image data | |
| var sampleColor = [data[i], data[i + 1], data[i + 2], data[i + 3]]; // start point color (sample) | |
| var stack = [{ y: py, left: px - 1, right: px + 1, dir: 1 }]; // first scanning line | |
| do { | |
| el = stack.shift(); // get line for scanning | |
| checkY = false; | |
| for (x = el.left + 1; x < el.right; x++) { | |
| dy = el.y * w; | |
| i = (dy + x) * bytes; // point index in the image data | |
| if (visited[dy + x] === 1) continue; // check whether the point has been visited | |
| // compare the color of the sample | |
| c = data[i] - sampleColor[0]; // check by red | |
| if (c > colorThreshold || c < -colorThreshold) continue; | |
| c = data[i + 1] - sampleColor[1]; // check by green | |
| if (c > colorThreshold || c < -colorThreshold) continue; | |
| c = data[i + 2] - sampleColor[2]; // check by blue | |
| if (c > colorThreshold || c < -colorThreshold) continue; | |
| checkY = true; // if the color of the new point(x,y) is similar to the sample color need to check minmax for Y | |
| result[dy + x] = 1; // mark a new point in mask | |
| visited[dy + x] = 1; // mark a new point as visited | |
| xl = x - 1; | |
| // walk to left side starting with the left neighbor | |
| while (xl > -1) { | |
| dyl = dy + xl; | |
| i = dyl * bytes; // point index in the image data | |
| if (visited[dyl] === 1) break; // check whether the point has been visited | |
| // compare the color of the sample | |
| c = data[i] - sampleColor[0]; // check by red | |
| if (c > colorThreshold || c < -colorThreshold) break; | |
| c = data[i + 1] - sampleColor[1]; // check by green | |
| if (c > colorThreshold || c < -colorThreshold) break; | |
| c = data[i + 2] - sampleColor[2]; // check by blue | |
| if (c > colorThreshold || c < -colorThreshold) break; | |
| result[dyl] = 1; | |
| visited[dyl] = 1; | |
| xl--; | |
| } | |
| xr = x + 1; | |
| // walk to right side starting with the right neighbor | |
| while (xr < w) { | |
| dyr = dy + xr; | |
| i = dyr * bytes; // index point in the image data | |
| if (visited[dyr] === 1) break; // check whether the point has been visited | |
| // compare the color of the sample | |
| c = data[i] - sampleColor[0]; // check by red | |
| if (c > colorThreshold || c < -colorThreshold) break; | |
| c = data[i + 1] - sampleColor[1]; // check by green | |
| if (c > colorThreshold || c < -colorThreshold) break; | |
| c = data[i + 2] - sampleColor[2]; // check by blue | |
| if (c > colorThreshold || c < -colorThreshold) break; | |
| result[dyr] = 1; | |
| visited[dyr] = 1; | |
| xr++; | |
| } | |
| // check minmax for X | |
| if (xl < minX) minX = xl + 1; | |
| if (xr > maxX) maxX = xr - 1; | |
| newY = el.y - el.dir; | |
| if (newY >= 0 && newY < h) { // add two scanning lines in the opposite direction (y - dir) if necessary | |
| if (xl < el.left) stack.push({ y: newY, left: xl, right: el.left, dir: -el.dir }); // from "new left" to "current left" | |
| if (el.right < xr) stack.push({ y: newY, left: el.right, right: xr, dir: -el.dir }); // from "current right" to "new right" | |
| } | |
| newY = el.y + el.dir; | |
| if (newY >= 0 && newY < h) { // add the scanning line in the direction (y + dir) if necessary | |
| if (xl < xr) stack.push({ y: newY, left: xl, right: xr, dir: el.dir }); // from "new left" to "new right" | |
| } | |
| } | |
| // check minmax for Y if necessary | |
| if (checkY) { | |
| if (el.y < minY) minY = el.y; | |
| if (el.y > maxY) maxY = el.y; | |
| } | |
| } while (stack.length > 0); | |
| return { | |
| data: result, | |
| width: image.width, | |
| height: image.height, | |
| bounds: { | |
| minX: minX, | |
| minY: minY, | |
| maxX: maxX, | |
| maxY: maxY | |
| } | |
| }; | |
| } | |
| function floodFillWithBorders(image, px, py, colorThreshold, mask) { | |
| var c, x, newY, el, xr, xl, dy, dyl, dyr, checkY, | |
| data = image.data, | |
| w = image.width, | |
| h = image.height, | |
| bytes = image.bytes, // number of bytes in the color | |
| maxX = -1, minX = w + 1, maxY = -1, minY = h + 1, | |
| i = py * w + px, // start point index in the mask data | |
| result = new Uint8Array(mask ? mask : w * h), // result mask | |
| visited = new Uint8Array(mask ? mask : w * h); // mask of visited points | |
| // console.log('iiiiiiiiiiiiiiii', i); | |
| // console.log('iiiii22222222222', result); | |
| // console.log('iiiii33333333333', visited); | |
| if (visited[i] === 1) { | |
| return null; | |
| // return { | |
| // data: result, | |
| // width: image.width, | |
| // height: image.height, | |
| // bounds: { | |
| // minX: minX, | |
| // minY: minY, | |
| // maxX: maxX, | |
| // maxY: maxY | |
| // } | |
| // }; | |
| } | |
| i = i * bytes; // start point index in the image data | |
| var sampleColor = [data[i], data[i + 1], data[i + 2], data[i + 3]]; // start point color (sample) | |
| var stack = [{ y: py, left: px - 1, right: px + 1, dir: 1 }]; // first scanning line | |
| do { | |
| el = stack.shift(); // get line for scanning | |
| checkY = false; | |
| for (x = el.left + 1; x < el.right; x++) { | |
| dy = el.y * w; | |
| i = (dy + x) * bytes; // point index in the image data | |
| if (visited[dy + x] === 1) continue; // check whether the point has been visited | |
| checkY = true; // if the color of the new point(x,y) is similar to the sample color need to check minmax for Y | |
| result[dy + x] = 1; // mark a new point in mask | |
| visited[dy + x] = 1; // mark a new point as visited | |
| // console.log('3333333333333', data[i + 3]); | |
| if (data[i + 3] === 0) { | |
| continue; | |
| } | |
| // compare the color of the sample | |
| c = data[i] - sampleColor[0]; // check by red | |
| if (c > colorThreshold || c < -colorThreshold) continue; | |
| c = data[i + 1] - sampleColor[1]; // check by green | |
| if (c > colorThreshold || c < -colorThreshold) continue; | |
| c = data[i + 2] - sampleColor[2]; // check by blue | |
| if (c > colorThreshold || c < -colorThreshold) continue; | |
| xl = x - 1; | |
| // walk to left side starting with the left neighbor | |
| while (xl > -1) { | |
| dyl = dy + xl; | |
| i = dyl * bytes; // point index in the image data | |
| if (visited[dyl] === 1) break; // check whether the point has been visited | |
| result[dyl] = 1; | |
| visited[dyl] = 1; | |
| xl--; | |
| if (data[i + 3] === 0) { | |
| break; | |
| } | |
| // compare the color of the sample | |
| c = data[i] - sampleColor[0]; // check by red | |
| if (c > colorThreshold || c < -colorThreshold) break; | |
| c = data[i + 1] - sampleColor[1]; // check by green | |
| if (c > colorThreshold || c < -colorThreshold) break; | |
| c = data[i + 2] - sampleColor[2]; // check by blue | |
| if (c > colorThreshold || c < -colorThreshold) break; | |
| } | |
| xr = x + 1; | |
| // walk to right side starting with the right neighbor | |
| while (xr < w) { | |
| dyr = dy + xr; | |
| i = dyr * bytes; // index point in the image data | |
| if (visited[dyr] === 1) break; // check whether the point has been visited | |
| result[dyr] = 1; | |
| visited[dyr] = 1; | |
| xr++; | |
| if (data[i + 3] === 0) { | |
| break; | |
| } | |
| // compare the color of the sample | |
| c = data[i] - sampleColor[0]; // check by red | |
| if (c > colorThreshold || c < -colorThreshold) break; | |
| c = data[i + 1] - sampleColor[1]; // check by green | |
| if (c > colorThreshold || c < -colorThreshold) break; | |
| c = data[i + 2] - sampleColor[2]; // check by blue | |
| if (c > colorThreshold || c < -colorThreshold) break; | |
| } | |
| // check minmax for X | |
| if (xl < minX) minX = xl + 1; | |
| if (xr > maxX) maxX = xr - 1; | |
| newY = el.y - el.dir; | |
| if (newY >= 0 && newY < h) { // add two scanning lines in the opposite direction (y - dir) if necessary | |
| if (xl < el.left) stack.push({ y: newY, left: xl, right: el.left, dir: -el.dir }); // from "new left" to "current left" | |
| if (el.right < xr) stack.push({ y: newY, left: el.right, right: xr, dir: -el.dir }); // from "current right" to "new right" | |
| } | |
| newY = el.y + el.dir; | |
| if (newY >= 0 && newY < h) { // add the scanning line in the direction (y + dir) if necessary | |
| if (xl < xr) stack.push({ y: newY, left: xl, right: xr, dir: el.dir }); // from "new left" to "new right" | |
| } | |
| } | |
| // check minmax for Y if necessary | |
| if (checkY) { | |
| if (el.y < minY) minY = el.y; | |
| if (el.y > maxY) maxY = el.y; | |
| } | |
| } while (stack.length > 0); | |
| return { | |
| data: result, | |
| width: image.width, | |
| height: image.height, | |
| bounds: { | |
| minX: minX, | |
| minY: minY, | |
| maxX: maxX, | |
| maxY: maxY | |
| } | |
| }; | |
| } | |
| /** Apply the gauss-blur filter to binary mask | |
| * Algorithms: http://blog.ivank.net/fastest-gaussian-blur.html | |
| * http://www.librow.com/articles/article-9 | |
| * http://elynxsdk.free.fr/ext-docs/Blur/Fast_box_blur.pdf | |
| * @param {Object} mask: {Uint8Array} data, {int} width, {int} height, {Object} bounds | |
| * @param {int} blur radius | |
| * @return {Object} mask: {Uint8Array} data, {int} width, {int} height, {Object} bounds | |
| */ | |
| lib.gaussBlur = function(mask, radius) { | |
| var i, k, k1, x, y, val, start, end, | |
| n = radius * 2 + 1, // size of the pattern for radius-neighbors (from -r to +r with the center point) | |
| s2 = radius * radius, | |
| wg = new Float32Array(n), // weights | |
| total = 0, // sum of weights(used for normalization) | |
| w = mask.width, | |
| h = mask.height, | |
| data = mask.data, | |
| minX = mask.bounds.minX, | |
| maxX = mask.bounds.maxX, | |
| minY = mask.bounds.minY, | |
| maxY = mask.bounds.maxY; | |
| // calc gauss weights | |
| for (i = 0; i < radius; i++) { | |
| var dsq = (radius - i) * (radius - i); | |
| var ww = Math.exp(-dsq / (2.0 * s2)) / (2 * Math.PI * s2); | |
| wg[radius + i] = wg[radius - i] = ww; | |
| total += 2 * ww; | |
| } | |
| // normalization weights | |
| for (i = 0; i < n; i++) { | |
| wg[i] /= total; | |
| } | |
| var result = new Uint8Array(w * h), // result mask | |
| endX = radius + w, | |
| endY = radius + h; | |
| //walk through all source points for blur | |
| for (y = minY; y < maxY + 1; y++) | |
| for (x = minX; x < maxX + 1; x++) { | |
| val = 0; | |
| k = y * w + x; // index of the point | |
| start = radius - x > 0 ? radius - x : 0; | |
| end = endX - x < n ? endX - x : n; // Math.min((((w - 1) - x) + radius) + 1, n); | |
| k1 = k - radius; | |
| // walk through x-neighbors | |
| for (i = start; i < end; i++) { | |
| val += data[k1 + i] * wg[i]; | |
| } | |
| start = radius - y > 0 ? radius - y : 0; | |
| end = endY - y < n ? endY - y : n; // Math.min((((h - 1) - y) + radius) + 1, n); | |
| k1 = k - radius * w; | |
| // walk through y-neighbors | |
| for (i = start; i < end; i++) { | |
| val += data[k1 + i * w] * wg[i]; | |
| } | |
| result[k] = val > 0.5 ? 1 : 0; | |
| } | |
| return { | |
| data: result, | |
| width: w, | |
| height: h, | |
| bounds: { | |
| minX: minX, | |
| minY: minY, | |
| maxX: maxX, | |
| maxY: maxY | |
| } | |
| }; | |
| }; | |
| /** Create a border index array of boundary points of the mask with radius-neighbors | |
| * @param {Object} mask: {Uint8Array} data, {int} width, {int} height, {Object} bounds | |
| * @param {int} blur radius | |
| * @param {Uint8Array} visited: mask of visited points (optional) | |
| * @return {Array} border index array of boundary points with radius-neighbors (only points need for blur) | |
| */ | |
| function createBorderForBlur(mask, radius, visited) { | |
| var x, i, j, y, k, k1, k2, | |
| w = mask.width, | |
| h = mask.height, | |
| data = mask.data, | |
| visitedData = new Uint8Array(data), | |
| minX = mask.bounds.minX, | |
| maxX = mask.bounds.maxX, | |
| minY = mask.bounds.minY, | |
| maxY = mask.bounds.maxY, | |
| len = w * h, | |
| temp = new Uint8Array(len), // auxiliary array to check uniqueness | |
| border = [], // only border points | |
| x0 = Math.max(minX, 1), | |
| x1 = Math.min(maxX, w - 2), | |
| y0 = Math.max(minY, 1), | |
| y1 = Math.min(maxY, h - 2); | |
| if (visited && visited.length > 0) { | |
| // copy visited points (only "black") | |
| for (k = 0; k < len; k++) { | |
| if (visited[k] === 1) visitedData[k] = 1; | |
| } | |
| } | |
| // walk through inner values except points on the boundary of the image | |
| for (y = y0; y < y1 + 1; y++) | |
| for (x = x0; x < x1 + 1; x++) { | |
| k = y * w + x; | |
| if (data[k] === 0) continue; // "white" point isn't the border | |
| k1 = k + w; // y + 1 | |
| k2 = k - w; // y - 1 | |
| // check if any neighbor with a "white" color | |
| if (visitedData[k + 1] === 0 || visitedData[k - 1] === 0 || | |
| visitedData[k1] === 0 || visitedData[k1 + 1] === 0 || visitedData[k1 - 1] === 0 || | |
| visitedData[k2] === 0 || visitedData[k2 + 1] === 0 || visitedData[k2 - 1] === 0) { | |
| //if (visitedData[k + 1] + visitedData[k - 1] + | |
| // visitedData[k1] + visitedData[k1 + 1] + visitedData[k1 - 1] + | |
| // visitedData[k2] + visitedData[k2 + 1] + visitedData[k2 - 1] == 8) continue; | |
| border.push(k); | |
| } | |
| } | |
| // walk through points on the boundary of the image if necessary | |
| // if the "black" point is adjacent to the boundary of the image, it is a border point | |
| if (minX == 0) | |
| for (y = minY; y < maxY + 1; y++) | |
| if (data[y * w] === 1) | |
| border.push(y * w); | |
| if (maxX == w - 1) | |
| for (y = minY; y < maxY + 1; y++) | |
| if (data[y * w + maxX] === 1) | |
| border.push(y * w + maxX); | |
| if (minY == 0) | |
| for (x = minX; x < maxX + 1; x++) | |
| if (data[x] === 1) | |
| border.push(x); | |
| if (maxY == h - 1) | |
| for (x = minX; x < maxX + 1; x++) | |
| if (data[maxY * w + x] === 1) | |
| border.push(maxY * w + x); | |
| var result = [], // border points with radius-neighbors | |
| start, end, | |
| endX = radius + w, | |
| endY = radius + h, | |
| n = radius * 2 + 1; // size of the pattern for radius-neighbors (from -r to +r with the center point) | |
| len = border.length; | |
| // walk through radius-neighbors of border points and add them to the result array | |
| for (j = 0; j < len; j++) { | |
| k = border[j]; // index of the border point | |
| temp[k] = 1; // mark border point | |
| result.push(k); // save the border point | |
| x = k % w; // calc x by index | |
| y = (k - x) / w; // calc y by index | |
| start = radius - x > 0 ? radius - x : 0; | |
| end = endX - x < n ? endX - x : n; // Math.min((((w - 1) - x) + radius) + 1, n); | |
| k1 = k - radius; | |
| // walk through x-neighbors | |
| for (i = start; i < end; i++) { | |
| k2 = k1 + i; | |
| if (temp[k2] === 0) { // check the uniqueness | |
| temp[k2] = 1; | |
| result.push(k2); | |
| } | |
| } | |
| start = radius - y > 0 ? radius - y : 0; | |
| end = endY - y < n ? endY - y : n; // Math.min((((h - 1) - y) + radius) + 1, n); | |
| k1 = k - radius * w; | |
| // walk through y-neighbors | |
| for (i = start; i < end; i++) { | |
| k2 = k1 + i * w; | |
| if (temp[k2] === 0) { // check the uniqueness | |
| temp[k2] = 1; | |
| result.push(k2); | |
| } | |
| } | |
| } | |
| return result; | |
| } | |
| /** Apply the gauss-blur filter ONLY to border points with radius-neighbors | |
| * Algorithms: http://blog.ivank.net/fastest-gaussian-blur.html | |
| * http://www.librow.com/articles/article-9 | |
| * http://elynxsdk.free.fr/ext-docs/Blur/Fast_box_blur.pdf | |
| * @param {Object} mask: {Uint8Array} data, {int} width, {int} height, {Object} bounds | |
| * @param {int} blur radius | |
| * @param {Uint8Array} visited: mask of visited points (optional) | |
| * @return {Object} mask: {Uint8Array} data, {int} width, {int} height, {Object} bounds | |
| */ | |
| lib.gaussBlurOnlyBorder = function(mask, radius, visited) { | |
| var border = createBorderForBlur(mask, radius, visited), // get border points with radius-neighbors | |
| ww, dsq, i, j, k, k1, x, y, val, start, end, | |
| n = radius * 2 + 1, // size of the pattern for radius-neighbors (from -r to +r with center point) | |
| s2 = 2 * radius * radius, | |
| wg = new Float32Array(n), // weights | |
| total = 0, // sum of weights(used for normalization) | |
| w = mask.width, | |
| h = mask.height, | |
| data = mask.data, | |
| minX = mask.bounds.minX, | |
| maxX = mask.bounds.maxX, | |
| minY = mask.bounds.minY, | |
| maxY = mask.bounds.maxY, | |
| len = border.length; | |
| // calc gauss weights | |
| for (i = 0; i < radius; i++) { | |
| dsq = (radius - i) * (radius - i); | |
| ww = Math.exp(-dsq / s2) / Math.PI; | |
| wg[radius + i] = wg[radius - i] = ww; | |
| total += 2 * ww; | |
| } | |
| // normalization weights | |
| for (i = 0; i < n; i++) { | |
| wg[i] /= total; | |
| } | |
| var result = new Uint8Array(data), // copy the source mask | |
| endX = radius + w, | |
| endY = radius + h; | |
| //walk through all border points for blur | |
| for (i = 0; i < len; i++) { | |
| k = border[i]; // index of the border point | |
| val = 0; | |
| x = k % w; // calc x by index | |
| y = (k - x) / w; // calc y by index | |
| start = radius - x > 0 ? radius - x : 0; | |
| end = endX - x < n ? endX - x : n; // Math.min((((w - 1) - x) + radius) + 1, n); | |
| k1 = k - radius; | |
| // walk through x-neighbors | |
| for (j = start; j < end; j++) { | |
| val += data[k1 + j] * wg[j]; | |
| } | |
| if (val > 0.5) { | |
| result[k] = 1; | |
| // check minmax | |
| if (x < minX) minX = x; | |
| if (x > maxX) maxX = x; | |
| if (y < minY) minY = y; | |
| if (y > maxY) maxY = y; | |
| continue; | |
| } | |
| start = radius - y > 0 ? radius - y : 0; | |
| end = endY - y < n ? endY - y : n; // Math.min((((h - 1) - y) + radius) + 1, n); | |
| k1 = k - radius * w; | |
| // walk through y-neighbors | |
| for (j = start; j < end; j++) { | |
| val += data[k1 + j * w] * wg[j]; | |
| } | |
| if (val > 0.5) { | |
| result[k] = 1; | |
| // check minmax | |
| if (x < minX) minX = x; | |
| if (x > maxX) maxX = x; | |
| if (y < minY) minY = y; | |
| if (y > maxY) maxY = y; | |
| } else { | |
| result[k] = 0; | |
| } | |
| } | |
| return { | |
| data: result, | |
| width: w, | |
| height: h, | |
| bounds: { | |
| minX: minX, | |
| minY: minY, | |
| maxX: maxX, | |
| maxY: maxY | |
| } | |
| }; | |
| }; | |
| /** Create a border mask (only boundary points) | |
| * @param {Object} mask: {Uint8Array} data, {int} width, {int} height, {Object} bounds | |
| * @return {Object} border mask: {Uint8Array} data, {int} width, {int} height, {Object} offset | |
| */ | |
| lib.createBorderMask = function(mask) { | |
| var x, y, k, k1, k2, | |
| w = mask.width, | |
| h = mask.height, | |
| data = mask.data, | |
| minX = mask.bounds.minX, | |
| maxX = mask.bounds.maxX, | |
| minY = mask.bounds.minY, | |
| maxY = mask.bounds.maxY, | |
| rw = maxX - minX + 1, // bounds size | |
| rh = maxY - minY + 1, | |
| result = new Uint8Array(rw * rh), // reduced mask (bounds size) | |
| x0 = Math.max(minX, 1), | |
| x1 = Math.min(maxX, w - 2), | |
| y0 = Math.max(minY, 1), | |
| y1 = Math.min(maxY, h - 2); | |
| // walk through inner values except points on the boundary of the image | |
| for (y = y0; y < y1 + 1; y++) | |
| for (x = x0; x < x1 + 1; x++) { | |
| k = y * w + x; | |
| if (data[k] === 0) continue; // "white" point isn't the border | |
| k1 = k + w; // y + 1 | |
| k2 = k - w; // y - 1 | |
| // check if any neighbor with a "white" color | |
| if (data[k + 1] === 0 || data[k - 1] === 0 || | |
| data[k1] === 0 || data[k1 + 1] === 0 || data[k1 - 1] === 0 || | |
| data[k2] === 0 || data[k2 + 1] === 0 || data[k2 - 1] === 0) { | |
| //if (data[k + 1] + data[k - 1] + | |
| // data[k1] + data[k1 + 1] + data[k1 - 1] + | |
| // data[k2] + data[k2 + 1] + data[k2 - 1] == 8) continue; | |
| result[(y - minY) * rw + (x - minX)] = 1; | |
| } | |
| } | |
| // walk through points on the boundary of the image if necessary | |
| // if the "black" point is adjacent to the boundary of the image, it is a border point | |
| if (minX == 0) | |
| for (y = minY; y < maxY + 1; y++) | |
| if (data[y * w] === 1) | |
| result[(y - minY) * rw] = 1; | |
| if (maxX == w - 1) | |
| for (y = minY; y < maxY + 1; y++) | |
| if (data[y * w + maxX] === 1) | |
| result[(y - minY) * rw + (maxX - minX)] = 1; | |
| if (minY == 0) | |
| for (x = minX; x < maxX + 1; x++) | |
| if (data[x] === 1) | |
| result[x - minX] = 1; | |
| if (maxY == h - 1) | |
| for (x = minX; x < maxX + 1; x++) | |
| if (data[maxY * w + x] === 1) | |
| result[(maxY - minY) * rw + (x - minX)] = 1; | |
| return { | |
| data: result, | |
| width: rw, | |
| height: rh, | |
| offset: { x: minX, y: minY } | |
| }; | |
| }; | |
| /** Create a border index array of boundary points of the mask | |
| * @param {Object} mask: {Uint8Array} data, {int} width, {int} height | |
| * @return {Array} border index array boundary points of the mask | |
| */ | |
| lib.getBorderIndices = function(mask) { | |
| var x, y, k, k1, k2, | |
| w = mask.width, | |
| h = mask.height, | |
| data = mask.data, | |
| border = [], // only border points | |
| x1 = w - 1, | |
| y1 = h - 1; | |
| // walk through inner values except points on the boundary of the image | |
| for (y = 1; y < y1; y++) | |
| for (x = 1; x < x1; x++) { | |
| k = y * w + x; | |
| if (data[k] === 0) continue; // "white" point isn't the border | |
| k1 = k + w; // y + 1 | |
| k2 = k - w; // y - 1 | |
| // check if any neighbor with a "white" color | |
| if (data[k + 1] === 0 || data[k - 1] === 0 || | |
| data[k1] === 0 || data[k1 + 1] === 0 || data[k1 - 1] === 0 || | |
| data[k2] === 0 || data[k2 + 1] === 0 || data[k2 - 1] === 0) { | |
| //if (data[k + 1] + data[k - 1] + | |
| // data[k1] + data[k1 + 1] + data[k1 - 1] + | |
| // data[k2] + data[k2 + 1] + data[k2 - 1] == 8) continue; | |
| border.push(k); | |
| } | |
| } | |
| // walk through points on the boundary of the image if necessary | |
| // if the "black" point is adjacent to the boundary of the image, it is a border point | |
| for (y = 0; y < h; y++) | |
| if (data[y * w] === 1) | |
| border.push(y * w); | |
| for (x = 0; x < w; x++) | |
| if (data[x] === 1) | |
| border.push(x); | |
| k = w - 1; | |
| for (y = 0; y < h; y++) | |
| if (data[y * w + k] === 1) | |
| border.push(y * w + k); | |
| k = (h - 1) * w; | |
| for (x = 0; x < w; x++) | |
| if (data[k + x] === 1) | |
| border.push(k + x); | |
| return border; | |
| }; | |
| /** Create a compressed mask with a "white" border (1px border with zero values) for the contour tracing | |
| * @param {Object} mask: {Uint8Array} data, {int} width, {int} height, {Object} bounds | |
| * @return {Object} border mask: {Uint8Array} data, {int} width, {int} height, {Object} offset | |
| */ | |
| function prepareMask(mask) { | |
| var x, y, | |
| w = mask.width, | |
| data = mask.data, | |
| minX = mask.bounds.minX, | |
| maxX = mask.bounds.maxX, | |
| minY = mask.bounds.minY, | |
| maxY = mask.bounds.maxY, | |
| rw = maxX - minX + 3, // bounds size +1 px on each side (a "white" border) | |
| rh = maxY - minY + 3, | |
| result = new Uint8Array(rw * rh); // reduced mask (bounds size) | |
| // walk through inner values and copy only "black" points to the result mask | |
| for (y = minY; y < maxY + 1; y++) | |
| for (x = minX; x < maxX + 1; x++) { | |
| if (data[y * w + x] === 1) | |
| result[(y - minY + 1) * rw + (x - minX + 1)] = 1; | |
| } | |
| return { | |
| data: result, | |
| width: rw, | |
| height: rh, | |
| offset: { x: minX - 1, y: minY - 1 } | |
| }; | |
| } | |
| /** Create a contour array for the binary mask | |
| * Algorithm: http://www.sciencedirect.com/science/article/pii/S1077314203001401 | |
| * @param {Object} mask: {Uint8Array} data, {int} width, {int} height, {Object} bounds | |
| * @return {Array} contours: {Array} points, {bool} inner, {int} label | |
| */ | |
| lib.traceContours = function(mask) { | |
| var m = prepareMask(mask), | |
| contours = [], | |
| label = 0, | |
| w = m.width, | |
| w2 = w * 2, | |
| h = m.height, | |
| src = m.data, | |
| dx = m.offset.x, | |
| dy = m.offset.y, | |
| dest = new Uint8Array(src), // label matrix | |
| i, j, x, y, k, k1, c, inner, dir, first, second, current, previous, next, d; | |
| // all [dx,dy] pairs (array index is the direction) | |
| // 5 6 7 | |
| // 4 X 0 | |
| // 3 2 1 | |
| var directions = [[1, 0], [1, 1], [0, 1], [-1, 1], [-1, 0], [-1, -1], [0, -1], [1, -1]]; | |
| for (y = 1; y < h - 1; y++) | |
| for (x = 1; x < w - 1; x++) { | |
| k = y * w + x; | |
| if (src[k] === 1) { | |
| for (i = -w; i < w2; i += w2) { // k - w: outer tracing (y - 1), k + w: inner tracing (y + 1) | |
| if (src[k + i] === 0 && dest[k + i] === 0) { // need contour tracing | |
| inner = i === w; // is inner contour tracing ? | |
| label++; // label for the next contour | |
| c = []; | |
| dir = inner ? 2 : 6; // start direction | |
| current = previous = first = { x: x, y: y }; | |
| second = null; | |
| while (true) { | |
| dest[current.y * w + current.x] = label; // mark label for the current point | |
| // bypass all the neighbors around the current point in a clockwise | |
| for (j = 0; j < 8; j++) { | |
| dir = (dir + 1) % 8; | |
| // get the next point by new direction | |
| d = directions[dir]; // index as direction | |
| next = { x: current.x + d[0], y: current.y + d[1] }; | |
| k1 = next.y * w + next.x; | |
| if (src[k1] === 1) // black boundary pixel | |
| { | |
| dest[k1] = label; // mark a label | |
| break; | |
| } | |
| dest[k1] = -1; // mark a white boundary pixel | |
| next = null; | |
| } | |
| if (next === null) break; // no neighbours (one-point contour) | |
| current = next; | |
| if (second) { | |
| if (previous.x === first.x && previous.y === first.y && current.x === second.x && current.y === second.y) { | |
| break; // creating the contour completed when returned to original position | |
| } | |
| } else { | |
| second = next; | |
| } | |
| c.push({ x: previous.x + dx, y: previous.y + dy }); | |
| previous = current; | |
| dir = (dir + 4) % 8; // next dir (symmetrically to the current direction) | |
| } | |
| if (next != null) { | |
| c.push({ x: first.x + dx, y: first.y + dy }); // close the contour | |
| contours.push({ inner: inner, label: label, points: c }); // add contour to the list | |
| } | |
| } | |
| } | |
| } | |
| } | |
| return contours; | |
| }; | |
| /** Simplify contours | |
| * Algorithms: http://psimpl.sourceforge.net/douglas-peucker.html | |
| * http://neerc.ifmo.ru/wiki/index.php?title=%D0%A3%D0%BF%D1%80%D0%BE%D1%89%D0%B5%D0%BD%D0%B8%D0%B5_%D0%BF%D0%BE%D0%BB%D0%B8%D0%B3%D0%BE%D0%BD%D0%B0%D0%BB%D1%8C%D0%BD%D0%BE%D0%B9_%D1%86%D0%B5%D0%BF%D0%B8 | |
| * @param {Array} contours: {Array} points, {bool} inner, {int} label | |
| * @param {float} simplify tolerant | |
| * @param {int} simplify count: min number of points when the contour is simplified | |
| * @return {Array} contours: {Array} points, {bool} inner, {int} label, {int} initialCount | |
| */ | |
| lib.simplifyContours = function(contours, simplifyTolerant, simplifyCount) { | |
| var lenContours = contours.length, | |
| result = [], | |
| i, j, k, c, points, len, resPoints, lst, stack, ids, | |
| maxd, maxi, dist, r1, r2, r12, dx, dy, pi, pf, pl; | |
| // walk through all contours | |
| for (j = 0; j < lenContours; j++) { | |
| c = contours[j]; | |
| points = c.points; | |
| len = c.points.length; | |
| if (len < simplifyCount) { // contour isn't simplified | |
| resPoints = []; | |
| for (k = 0; k < len; k++) { | |
| resPoints.push({ x: points[k].x, y: points[k].y }); | |
| } | |
| result.push({ inner: c.inner, label: c.label, points: resPoints, initialCount: len }); | |
| continue; | |
| } | |
| lst = [0, len - 1]; // always add first and last points | |
| stack = [{ first: 0, last: len - 1 }]; // first processed edge | |
| do { | |
| ids = stack.shift(); | |
| if (ids.last <= ids.first + 1) // no intermediate points | |
| { | |
| continue; | |
| } | |
| maxd = -1.0; // max distance from point to current edge | |
| maxi = ids.first; // index of maximally distant point | |
| for (i = ids.first + 1; i < ids.last; i++) // bypass intermediate points in edge | |
| { | |
| // calc the distance from current point to edge | |
| pi = points[i]; | |
| pf = points[ids.first]; | |
| pl = points[ids.last]; | |
| dx = pi.x - pf.x; | |
| dy = pi.y - pf.y; | |
| r1 = Math.sqrt(dx * dx + dy * dy); | |
| dx = pi.x - pl.x; | |
| dy = pi.y - pl.y; | |
| r2 = Math.sqrt(dx * dx + dy * dy); | |
| dx = pf.x - pl.x; | |
| dy = pf.y - pl.y; | |
| r12 = Math.sqrt(dx * dx + dy * dy); | |
| if (r1 >= Math.sqrt(r2 * r2 + r12 * r12)) dist = r2; | |
| else if (r2 >= Math.sqrt(r1 * r1 + r12 * r12)) dist = r1; | |
| else dist = Math.abs((dy * pi.x - dx * pi.y + pf.x * pl.y - pl.x * pf.y) / r12); | |
| if (dist > maxd) { | |
| maxi = i; // save the index of maximally distant point | |
| maxd = dist; | |
| } | |
| } | |
| if (maxd > simplifyTolerant) // if the max "deviation" is larger than allowed then... | |
| { | |
| lst.push(maxi); // add index to the simplified list | |
| stack.push({ first: ids.first, last: maxi }); // add the left part for processing | |
| stack.push({ first: maxi, last: ids.last }); // add the right part for processing | |
| } | |
| } while (stack.length > 0); | |
| resPoints = []; | |
| len = lst.length; | |
| lst.sort(function(a, b) { return a - b; }); // restore index order | |
| for (k = 0; k < len; k++) { | |
| resPoints.push({ x: points[lst[k]].x, y: points[lst[k]].y }); // add result points to the correct order | |
| } | |
| result.push({ inner: c.inner, label: c.label, points: resPoints, initialCount: c.points.length }); | |
| } | |
| return result; | |
| }; | |
| return lib; | |
| })(); | |
| module.exports = MagicWand; | |
| //# sourceMappingURL=magic-wand.js.map |
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