fixed wrong paths in typescript examples

Author: justadudewhohacks

examples/dnn/loadFacenet.js

@@ -5,7 +5,7 @@ const {
 } = require('../utils');
 
 module.exports = function () {
-  const modelPath = '../../data/dnn/facenet';
+  const modelPath = path.resolve(__dirname, '../../data/dnn/facenet');
 
   const prototxt = path.resolve(modelPath, 'facenet.prototxt');
   const modelFile = path.resolve(modelPath, 'res10_300x300_ssd_iter_140000.caffemodel');

examples/faceRecognition1.js

@@ -41,9 +41,13 @@ const lbph = new cv.LBPHFaceRecognizer();
 lbph.train(trainImgs, labels);
 
 const twoFacesImg = cv.imread(path.resolve(basePath, 'daryl-rick.jpg'));
-const faces = classifier.detectMultiScale(twoFacesImg.bgrToGray()).objects;
+const result = classifier.detectMultiScale(twoFacesImg.bgrToGray());
 
-faces.forEach((faceRect) => {
+const minDetections = 10;
+result.objects.forEach((faceRect, i) => {
+  if (result.numDetections[i] < minDetections) {
+    return;
+  }
   const faceImg = twoFacesImg.getRegion(faceRect).bgrToGray();
   const who = nameMappings[lbph.predict(faceImg).label];
 

examples/typed/dnn/loadFacenet.ts

@@ -3,7 +3,7 @@ import * as path from 'path';
 import * as cv from '../../../';
 
 export function loadFacenet (): cv.Net {
-  const modelPath = '../../../data/dnn/facenet';
+  const modelPath = path.resolve(__dirname, '../../../data/dnn/facenet');
 
   const prototxt = path.resolve(modelPath, 'facenet.prototxt');
   const modelFile = path.resolve(modelPath, 'res10_300x300_ssd_iter_140000.caffemodel');

examples/typed/dnnSSDCoco.ts

@@ -13,7 +13,7 @@ if (!cv.xmodules.dnn) {
 }
 
 // replace with path where you unzipped inception model
-const ssdcocoModelPath = '../data/dnn/coco-SSD_300x300';
+const ssdcocoModelPath = '../../data/dnn/coco-SSD_300x300';
 
 const prototxt = path.resolve(ssdcocoModelPath, 'deploy.prototxt');
 const modelFile = path.resolve(ssdcocoModelPath, 'VGG_coco_SSD_300x300_iter_400000.caffemodel');
@@ -54,7 +54,7 @@ const makeDrawClassDetections = (predictions: Prediction[]) =>
   };
 
 const runDetectDishesExample = () => {
-  const img = cv.imread('../data/dishes.jpg');
+  const img = cv.imread('../../data/dishes.jpg');
   const minConfidence = 0.2;
 
   const predictions = classifyImg(img).filter(res => res.confidence > minConfidence);
@@ -92,7 +92,7 @@ const runDetectDishesExample = () => {
 };
 
 const runDetectPeopleExample = () => {
-  const img = cv.imread('../data/cars.jpeg');
+  const img = cv.imread('../../data/cars.jpeg');
   const minConfidence = 0.4;
 
   const predictions = classifyImg(img).filter(res => res.confidence > minConfidence);

examples/typed/dnnTensorflowInception.ts

@@ -61,19 +61,19 @@ const classifyImg = (img: cv.Mat) => {
 
 const testData = [
   {
-    image: '../data/banana.jpg',
+    image: '../../data/banana.jpg',
     label: 'banana'
   },
   {
-    image: '../data/husky.jpg',
+    image: '../../data/husky.jpg',
     label: 'husky'
   },
   {
-    image: '../data/car.jpeg',
+    image: '../../data/car.jpeg',
     label: 'car'
   },
   {
-    image: '../data/lenna.png',
+    image: '../../data/lenna.png',
     label: 'lenna'
   }
 ];

examples/typed/faceRecognition1.ts

@@ -6,7 +6,7 @@ if (!cv.xmodules.face) {
   throw new Error('exiting: opencv4nodejs compiled without face module');
 }
 
-const basePath = '../data/face-recognition';
+const basePath = '../../data/face-recognition';
 const imgsPath = path.resolve(basePath, 'imgs');
 const nameMappings = ['daryl', 'rick', 'negan'];
 
@@ -41,9 +41,14 @@ const lbph = new cv.LBPHFaceRecognizer();
 lbph.train(trainImgs, labels);
 
 const twoFacesImg = cv.imread(path.resolve(basePath, 'daryl-rick.jpg'));
-const faces = classifier.detectMultiScale(twoFacesImg.bgrToGray()).objects;
+const result = classifier.detectMultiScale(twoFacesImg.bgrToGray());
+
+const minDetections = 10;
+result.objects.forEach((faceRect, i) => {
+  if (result.numDetections[i] < minDetections) {
+    return;
+  }
 
-faces.forEach((faceRect) => {
   const faceImg = twoFacesImg.getRegion(faceRect).bgrToGray();
   const who = nameMappings[lbph.predict(faceImg).label];
 

examples/typed/handGestureRecognition0.ts

@@ -125,7 +125,7 @@ const red = new cv.Vec3(0, 0, 255);
 
 // main
 const delay = 20;
-grabFrames('../data/hand-gesture.mp4', delay, (frame) => {
+grabFrames('../../data/hand-gesture.mp4', delay, (frame) => {
   const resizedImg = frame.resizeToMax(640);
 
   const handMask = makeHandMask(resizedImg);

examples/typed/machineLearningOCR.ts

@@ -7,9 +7,9 @@ import {
   saveConfusionMatrix
 } from './OCRTools';
 
-const trainDataPath = '../data/ocr/traindata';
-const testDataPath = '../data/ocr/testdata';
-const outPath = '../data/ocr';
+const trainDataPath = '../../data/ocr/traindata';
+const testDataPath = '../../data/ocr/testdata';
+const outPath = '../../data/ocr';
 const SVMFile = 'lcletters.xml';
 
 const hog = new cv.HOGDescriptor({

examples/typed/matchFeatures.ts

@@ -32,8 +32,8 @@ const matchFeatures = (
   );
 };
 
-const img1 = cv.imread('../data/s0.jpg');
-const img2 = cv.imread('../data/s1.jpg');
+const img1 = cv.imread('../../data/s0.jpg');
+const img2 = cv.imread('../../data/s1.jpg');
 
 // check if opencv compiled with extra modules and nonfree
 if (cv.xmodules.xfeatures2d) {

examples/typed/plotHist.ts

@@ -1,6 +1,6 @@
 import * as cv from '../../';
 
-const img = cv.imread('../data/Lenna.png');
+const img = cv.imread('../../data/Lenna.png');
 
 // single axis for 1D hist
 const getHistAxis = (channel: number) => ([