TypeError when calling cv.NMSBoxes with opencvjs from React.js

ivan-ngchakming · May 25, 2022, 4:42pm

Hello, I am trying to use the cv.NMSBoxes function to run the nms algorithm from opencv.js. But can’t seem to make it work, I keep getting the following error. Anyone can offer some insight as to why this is happening? Thanks a lot!

TypeError: _techstark_opencv_js__WEBPACK_IMPORTED_MODULE_2___default(...).NMSBoxes is not a function

This is how I am calling the function, everything should match the types specified in the API docs (OpenCV: Deep Neural Network module).

cv.NMSBoxes(
  bboxRects,  // cv.RectVector
  scoreVector,  // cv.FloatVector
  scoreThreshold,  // js number
  nmsThreshold,  // js number
  finalIdxs  // cv.IntVector
);

berak · May 25, 2022, 4:55pm

im almost sure, that noone bothered yet to add it to the js api
(you can only use, what’s in the “whitelist”):

github.com

opencv/opencv/blob/08c270f65af6725b77b0299967a2fa48b6b960e3/platforms/js/opencv_js.config.py#L132

      
        
                    'findTransformECC',
                    'meanShift',
                ],
                'BackgroundSubtractorMOG2': ['BackgroundSubtractorMOG2', 'apply'],
                'BackgroundSubtractor': ['apply', 'getBackgroundImage'],
                # issue #21070: 'Tracker': ['init', 'update'],
                'TrackerMIL': ['create'],
                'TrackerMIL_Params': [],
            }
            
            
dnn = {'dnn_Net': ['setInput', 'forward', 'setPreferableBackend'],
                   '': ['readNetFromCaffe', 'readNetFromTensorflow', 'readNetFromTorch', 'readNetFromDarknet',
                        'readNetFromONNX', 'readNet', 'blobFromImage']}
            
            
features2d = {'Feature2D': ['detect', 'compute', 'detectAndCompute', 'descriptorSize', 'descriptorType', 'defaultNorm', 'empty', 'getDefaultName'],
                          'BRISK': ['create', 'getDefaultName'],
                          'ORB': ['create', 'setMaxFeatures', 'setScaleFactor', 'setNLevels', 'setEdgeThreshold', 'setFirstLevel', 'setWTA_K', 'setScoreType', 'setPatchSize', 'getFastThreshold', 'getDefaultName'],
                          'MSER': ['create', 'detectRegions', 'setDelta', 'getDelta', 'setMinArea', 'getMinArea', 'setMaxArea', 'getMaxArea', 'setPass2Only', 'getPass2Only', 'getDefaultName'],
                          'FastFeatureDetector': ['create', 'setThreshold', 'getThreshold', 'setNonmaxSuppression', 'getNonmaxSuppression', 'setType', 'getType', 'getDefaultName'],
                          'AgastFeatureDetector': ['create', 'setThreshold', 'getThreshold', 'setNonmaxSuppression', 'getNonmaxSuppression', 'setType', 'getType', 'getDefaultName'],
                          'GFTTDetector': ['create', 'setMaxFeatures', 'getMaxFeatures', 'setQualityLevel', 'getQualityLevel', 'setMinDistance', 'getMinDistance', 'setBlockSize', 'getBlockSize', 'setHarrisDetector', 'getHarrisDetector', 'setK', 'getK', 'getDefaultName'],

(yea i know it’s crucial to use yolo nns and whatnot)

are you able to rebuild it locally ? just add it there, and give it a try …

berak · May 25, 2022, 5:12pm

hmm, there might be troubles, otherwise ppl would not have reinvented wheel here:

github.com

opencv/opencv/blob/4.x/doc/js_tutorials/js_assets/js_object_detection.html#L157

      
        
                        scores: scores,
                        classId: classId,
                        confidence: confidence,
                        bounding: [left, top, width, height],
                        toDraw: true
                    }
                    boxes.push(box);
                }
            }
            
            
// NMS(Non Maximum Suppression) algorithm
            let boxNum = boxes.length;
            let tmp_boxes = [];
            let sorted_boxes = [];
            for (let c = 0; c < classNum; ++c) {
                for (let i = 0; i < boxes.length; ++i) {
                    tmp_boxes[i] = [boxes[i], i];
                }
                sorted_boxes = tmp_boxes.sort((a, b) => { return (b[0].scores[c] - a[0].scores[c]); });
                for (let i = 0; i < boxNum; ++i) {
                    if (sorted_boxes[i][0].scores[c] === 0) continue;

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TypeError when calling cv.NMSBoxes with opencvjs from React.js

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