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in opencv.js function cv.findTransformECC what is inputMask?

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How do you represent "inputMask=None" 6th argument in Javascript? "null" does not work. The argument IS NOT optional as it outlines in docs. [findTransformECC] (https://docs.opencv.org/master/dc/d6b/group__video__track.html#ga1aa357007eaec11e9ed03500ecbcbe47) has 2 optional parameter (inputMask and gaussFiltSize) but if you don't include them you get an error. so what should be used for inputMask? "null" does not work. function Align_img(){ let image_baseline = cv.imread(imgElement_Baseline); let image = cv.imread('imageChangeup'); let im1_gray = new cv.Mat(); let im2_gray = new cv.Mat(); let im2_aligned = new cv.Mat(); //get size of baseline image var width1 = image_baseline.cols; var height1 = image_baseline.rows; //resize image to baseline image let dim1 = new cv.Size(width1, height1); cv.resize(image, image, dim1, cv.INTER_AREA); // Convert images to grayscale cv.cvtColor(image_baseline, im1_gray, cv.COLOR_BGR2GRAY); cv.cvtColor(image, im2_gray, cv.COLOR_BGR2GRAY); // Find size of image1 let dsize = new cv.Size(image_baseline.rows, image_baseline.cols); // Define the motion model const warp_mode = cv.MOTION_HOMOGRAPHY; // Define 3x3 matrix and initialize the matrix to identity let warp_matrix = cv.Mat.eye(3, 3, cv.CV_8U); // Specify the number of iterations. const number_of_iterations = 5000; // Specify the threshold of the increment in the correlation coefficient between two iterations const termination_eps = 0.0000000001; //1e-10; // Define termination criteria //const criteria = (cv.TERM_CRITERIA_EP | cv.TERM_CRITERIA_COUNT, number_of_iterations, termination_eps); let criteria = new cv.TermCriteria(cv.TERM_CRITERIA_EP | cv.TERM_CRITERIA_COUNT, number_of_iterations, termination_eps); //Run the ECC algorithm. The results are stored in warp_matrix. //let inputMask = new cv.Mat.zeros(im1_gray.size(), cv.CV_8UC3); //uint8 cv.findTransformECC(im1_gray, im2_gray, warp_matrix, warp_mode, criteria, null, 5); // Use warpPerspective for Homography cv.warpPerspective (image, im2_aligned, warp_matrix, dsize, cv.INTER_LINEAR + cv.WARP_INVERSE_MAP); cv.imshow('imageChangeup', im2_aligned); im1_gray.delete(); im2_gray.delete(); im2_aligned.delete(); };

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