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https://github.com/ColonelParrot/jscanify.git
synced 2025-12-30 22:31:52 +00:00
fix skipped tests with before()
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b4e68b12c9
commit
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@ -39,21 +39,30 @@ function setup() {
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})
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})
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}
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}
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console.log("=== beginning tests ===");
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let scanner;
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console.log("loading OpenCV.js...");
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let cv;
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const scanner = new jscanify();
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before(function (done) {
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scanner.loadOpenCV(function (cv) {
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console.log("=== beginning tests ===");
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console.log("loading OpenCV.js...");
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scanner = new jscanify();
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scanner.loadOpenCV(function (loadedCv) {
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cv = loadedCv;
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console.log("Finished loading OpenCV.js");
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console.log("Finished loading OpenCV.js");
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console.log("Writing test images to: " + OUTPUT_FOLDER);
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console.log("Writing test images to: " + OUTPUT_FOLDER);
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setup()
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done();
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});
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});
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/**
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/**
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* tests an individual image
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* tests an individual image
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*/
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*/
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function test(testImage, imageCount) {
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function test(testImage, imageCount) {
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describe("image #" + imageCount, function () {
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describe("image #" + imageCount, function () {
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it("should highlight paper", function (done) {
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it("should highlight paper", function () {
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const highlighted = scanner.highlightPaper(testImage);
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const highlighted = scanner.highlightPaper(testImage);
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const higlightedOutputPath = OUTPUT_FOLDER + "highlighted-" + imageCount + ".jpg";
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const higlightedOutputPath = OUTPUT_FOLDER + "highlighted-" + imageCount + ".jpg";
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writeFileSync(
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writeFileSync(
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@ -62,10 +71,9 @@ scanner.loadOpenCV(function (cv) {
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);
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);
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assert.ok(existsSync(higlightedOutputPath));
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assert.ok(existsSync(higlightedOutputPath));
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done();
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});
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});
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it("should extract paper", function (done) {
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it("should extract paper", function () {
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const extracted = scanner.extractPaper(testImage, 386, 500);
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const extracted = scanner.extractPaper(testImage, 386, 500);
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const extractedOutputPath = OUTPUT_FOLDER + "extracted-" + imageCount + ".jpg";
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const extractedOutputPath = OUTPUT_FOLDER + "extracted-" + imageCount + ".jpg";
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@ -75,10 +83,9 @@ scanner.loadOpenCV(function (cv) {
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);
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);
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assert.ok(existsSync(extractedOutputPath));
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assert.ok(existsSync(extractedOutputPath));
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done();
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});
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});
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it("should label corner points", function (done) {
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it("should label corner points", function () {
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const parsedImage = cv.imread(testImage);
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const parsedImage = cv.imread(testImage);
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const paperContour = scanner.findPaperContour(parsedImage);
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const paperContour = scanner.findPaperContour(parsedImage);
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const {
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const {
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@ -111,27 +118,23 @@ scanner.loadOpenCV(function (cv) {
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writeFileSync(cornerPointsOutputPath, canvas.toBuffer("image/jpeg"));
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writeFileSync(cornerPointsOutputPath, canvas.toBuffer("image/jpeg"));
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assert.ok(existsSync(cornerPointsOutputPath));
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assert.ok(existsSync(cornerPointsOutputPath));
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done();
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});
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});
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});
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});
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}
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}
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setup();
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let imageCount = 1;
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let imageCount = 1;
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/*
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/*
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* go through all images in test image directory
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* go through all images in test image directory
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*/
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*/
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readdirSync(TEST_IMAGE_DIRECTORY).forEach((file) => {
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readdirSync(TEST_IMAGE_DIRECTORY).forEach((file) => {
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const TEST_IMAGE_PATH = path.join(TEST_IMAGE_DIRECTORY, file);
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const TEST_IMAGE_PATH = path.join(TEST_IMAGE_DIRECTORY, file);
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if(!file.endsWith("-sized.png")){ // these images are for the website, not testing
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if (!file.endsWith("-sized.png")) { // these images are for the website, not testing
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let tempCount = imageCount++;
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let tempCount = imageCount++;
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loadImage(TEST_IMAGE_PATH).then(function (image) {
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loadImage(TEST_IMAGE_PATH).then(function (image) {
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test(image, tempCount);
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test(image, tempCount);
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});
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});
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}
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}
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})
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})
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});
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