Some of the functions include operations, such as generating a random point cloud, converting PCD file to PNG format, and downsampling a cloud using pcl. The participants have enabled calls to 41 functions of PCL from Scilab. The Point Cloud Library (PCL) is an open-source library of algorithms for point cloud processing tasks and 3D geometry processing, such as that occur in three-dimensional computer vision. Team STH105: Point Cloud Library (PCL) Toolbox for Scilab A total of 42 teams completed the work in the allotted time of 2-3 weeks, as shown in the chart below.Ī brief write up on the Champion toolboxes is given below: Proposals from about 150 teams were considered to be suitable for toolbox development. More than 700 students and professionals from different parts of India expressed interest to participate in the Scilab Toolbox Hackathon, coordinated through. Eight toolboxes created through this hackathon are now available on the Atom page, mentioned above. The method proposed for the hackathon was validated by the FOSSEE team while building the Optimization Toolbox, created by calling the routines in the open source repository COIN-OR. These can also be located in Scilab's Atom page and searching by the phrase FOSSEE. The FOSSEE team has already created a few toolboxes, available through. As there are lots of extremely useful open source software, it should be possible to increase the number of toolboxes in Scilab through this activity. One of the shortcomings of Scilab is that it does not have an extensive collection of toolboxes. The reason to initiate this activity was to increase the number of toolboxes available in Scilab. The objective of this hackathon was to make available useful open source software as a toolbox within Scilab. For example, through Scilab Textbook Companion, available at, FOSSEE coordinated the work of about 1,000 students from about 500 colleges to produce Scilab code for 75,000 solved examples of 625 standard textbooks of science and engineering. The FOSSEE team has been actively promoting Scilab as an alternative to the extremely popular, but also very expensive (especially to the industry), software, Matlab. FOSSEE, IIT Bombay (), conducted a Scilab Toolbox Hackathon in May-June 2020, just after the onset of the pandemic. gaussnewton ( gauss_dissym, Xdef, Ydef. ^ 2 )) endfunction function = gaussnewton (f, X, Yexp, A0, imax, epsilon ) // A : jeu de paramètres optimisé par régression (vecteur) // R : liste des facteurs de qualité de la régression // pour chaque étape (vecteur) // X : variable explicative (vecteur) // Yexp : variable expliquée, valeurs mesurées (vecteur) // A0 : paramètres d'initialisation du modèle (vecteur) // epsilon : valeur d'arrêt (scalaire) k = 1 // facteur d'amortissement initial, 0.1 ) // teste la divergence sur 1 étape deltap = k * deltap0 Bnouveau = B + deltap ' Ycal = f ( Bnouveau, X ) R ( i ) = res ( Yexp, Ycal ) / e0 drapeau2 = ( R ( i ) > = R ( i - 1 )) // vrai si diverge if drapeau2 then k = k * 0.75 // atténue si diverge else k0 = k // pour affichage de la valeur k = ( 1 + k ) / 2 // réduit l'atténuation si converge end end B = Bnouveau drapeau = abs ( R ( i - 1 ) - R ( i )) > epsilon clf subplot ( 2, 1, 1 ) plot2d ( X, Yexp, rect =) plot ( X, Ycal, "-r" ) xstring ( - 2.8, - 1.5, string ( B )) subplot ( 2, 1, 2 ) plot2d ( R, rect =) xstring ( 1.2, 0.1, 'α = ' + string ( k0 ) + ' R = ' + string ( R ( i ))) nom = 'picassym' + string ( i ) + '.gif' xs2gif ( 0, nom ) // disp('i = '+string(i)+' k = '+string(k0)+' R = '+string(R(i))) end A = B endfunction // ********** // Programme principal // ********** // lecture des données donnees = read ( 'pic_gauss_dissym_bruite.txt', - 1, 2 ) // carcatéristiques des données Xdef = donnees (:, 1 ) Ydef = donnees (:, 2 ) // Ainit = Ainit = // Régression tic () =. ********** // Constantes et initialisation // ********** clear clf chdir ( 'monchemin/' ) // Paramètres de Newton-Raphson precision = 1e-7 // condition d'arrêt itermax = 60 // idem // Précision de la linéarisation approchée epsilon = 1e-6 // ********** // Fonctions // ********** exec ( 'fonctions_communes.sce', - 1 ) function = res (Yexp, Ycal ) e = sqrt ( sum (( Yexp - Ycal ).
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