{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Henger illesztés RANSAC eljárással\n",
"\n",
"Az előzőekben már megvizsgáltuk a gömb illesztés megoldását a RANSAC eljárással. Most adott pontokra egyenes körhengert szeretnénk illeszteni. A pontok koordinátái a `dat\\cyl.dat` [állományban](./dat/cyl.dat) találhatók.\n",
"\n",
"A henger illesztés esetében a legnehezebb feladat az 5 megadott koordinátájú ponton átmenő henger(ek) paramétereinek kiszámítása. Meg lehet ugyanis mutatni, hogy 4 pont még nem elég, viszont 5 pont esetében páros számú (0, 2, 4, 6) megoldás található. \n",
"\n",
"Az általunk követett megoldás Paul Zsombor-Murray, Sawsan El Fashny (2006) [cikkén](http://www.heldermann-verlag.de/jgg/jgg10/j10h2zsom.pdf) alapul. Sajnos a cikkben két képlet is hibásan jelent meg, így ezeket is meg kellett keresnünk és ki kellett javítanunk. Szerencsére a cikkben közölt 2.1-es számpélda segítségével és számítógépes algebrai rendszer alkalmazásával ez végül is sikerült. Az egyik hibás kifejezés az (5) összefüggés második egyenlete, amelynek második tagja $p_1a_2^2$ helyett helyesen $p_1^2a_2^2$. A másik hiba a (10) egyenlet $d_5$ együtthatójában van. Az együtthatóra vonatkozó kifejezés harmadik tagja $-b_1c_1$ helyett $-b_1c_2$. Az említett cikkben közölt eljárás egyébként 6-odfokú algebrai egyenlet megoldásán alapul, így viszonylag gyors számítási eljárásról van szó, ami a RANSAC szempontjából fontos, hiszen ezt az eljárást sokszor kell majd alkalmazni.\n",
"\n",
"A számítás a következő lépésekből áll:\n",
"* egy adott speciális koordináta-rendszerbe transzformáljuk az 5 pontot\n",
"* felírunk egy hatodfokú polinomot a henger irányvektorának egyik komponensére a henger pontjainak alapegyenletéből kiindulva\n",
"* a másik komponens ezután lineáris egyenletből kiszámítható\n",
"\n",
"A henger pontjainak alapegyenlete a következő:\n",
"\n",
"$$(\\mathbf{x}\\times\\mathbf{a})^2 -2\\mathbf{a}^2(\\mathbf{x}\\cdot\\mathbf{a}) = 0 ,$$\n",
"\n",
"ahol $\\mathbf{x}$ a henger tetszőleges pontjának helyvektora, $\\mathbf{a}$ a henger tengelyének irányába mutató vektor. Az $\\mathbf{f}$ vektor az $O$ kezdőpontból a henger tengelyének egy pontjába mutat és merőleges az $\\mathbf{a}$ vektorra ($\\mathbf{a}\\cdot\\mathbf{f}=0$).\n",
"\n",
"Minden megadott pontra fel tudunk írni egy ilyen egyenletet, de mivel a koordináta-rendszerünk $O$ kezdőpontját tetszőlegesen vehetjük fel (például azonos lesz az első ponttal), ezért csak 4 ilyen egyenletünk lesz a 6 ismeretlenre (ezek az $\\mathbf{a}$ és $\\mathbf{f}$ vektorok összetevői). A merőlegességi feltétel az 5. egyenlet.\n",
"\n",
"Mivel az $\\mathbf{a}$ vektor hossza tetszőleges (például legyen egységnyi, $\\mathbf{a}^2=1$; csak az iránya lényeges), ezért csupán 5 ismeretlen van, így 5 egyenlet valóban elég. Megemlítjük még, hogy a kapott $\\mathbf{f}$ vektor hossza adja meg a henger sugarát.\n",
"\n",
"Először megírjuk az 5 pont alapján egyenes körhenger paramétereinek a meghatározását végző Python függvényt. A függvény bemenő adatai az 5 pont koordinátái, az eredmény pedig egy olyan mátrix, amelynek oszlopaiban szerepelnek az egyes megoldások paraméterei: az $r$ sugár, valamint az $\\mathbf{a}$ és $\\mathbf{f}$ vektorok összetevői."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"\n",
"def cyl5fit(X1,X2,X3,X4,X5):\n",
" ## cyl5fit(X1,...,X5) hengereket illeszt az X1..X5 pontokra\n",
" ## Hivatkozás: Paul(2006): A Cylinder of revolution on Five Points\n",
"\n",
" ## eltolás O-ba:\n",
" o=X1-X1\n",
" pt=X2-X1\n",
" qt=X3-X1\n",
" rt=X4-X1\n",
" st=X5-X1\n",
"\n",
" ## elforgatás úgy, hogy OP=x, OQ=xy-síkban\n",
" ## transzformált x\n",
" x = pt/np.linalg.norm(pt)\n",
" ## transzformált y\n",
" y = qt-(np.inner(qt,pt))/np.linalg.norm(pt)*x\n",
" y = y/np.linalg.norm(y)\n",
" ## transzformált z\n",
" z = np.array([(x[1]*y[2]-x[2]*y[1]),(x[2]*y[0]-x[0]*y[2]),(x[0]*y[1]-x[1]*y[0])])\n",
" R = np.zeros((3,3))\n",
" R[0,:] = x\n",
" R[1,:] = y\n",
" R[2,:] = z\n",
" p = R.dot(pt)\n",
" q = R.dot(qt)\n",
" r = R.dot(rt)\n",
" s = R.dot(st)\n",
"\n",
" p1=p[0];q1=q[0];q2=q[1];r1=r[0];r2=r[1];r3=r[2]\n",
" s1=s[0];s2=s[1];s3=s[2]\n",
"\n",
" ## Eq. 11.\n",
" b1=2*q2*r2*(q1-r1); \n",
" b2=q2*r3*(p1-2*q1)\n",
" b3=q2*r3*(p1-2*r1)\n",
" b4=q2*(r1*(r1-p1)+r2*(r2-q2))+q1*r2*(p1-q1)\n",
" b5=r3*(q2*(q2-2*r2)+q1*(q1-p1)); b6=q2**2*r3\n",
" b7=q1*r3*(q1-p1)\n",
" b8=q2*(r2*(r2-q2)+r3**2)\n",
" b9=q2*(r1*(r1-p1)+r3**2)+q1*r2*(p1-q1)\n",
" ##\n",
" c1=q2*(r2*s3*(r2-q2)+r3*s2*(q2-s2)+r3*s3*(r3-s3))\n",
" c2=q2*r3*s3*(r3-s3)+q1**2*(r3*s2-r2*s3)+p1*(q2*(r3*s1-r1*s3)+q1*(r2*s3-r3*s2)) \\\n",
" +q2*(r1**2*s3-r3*s1**2)\n",
" c3=q2*(p1*(s1*r3-s3*r1)-r3*(s1**2+s2**2)+s3*(r1**2+r2**2)) \\\n",
" +(r2*s3-r3*s2)*(q1*(p1-q1)-q2**2)\n",
" c4=2*q2*r3*s3*(s2-r2); c5=2*q2*r3*s3*(s1-r1)\n",
" c6=2*q2*(r3*s2*(s1-q1)+r2*s3*(q1-r1))\n",
"\n",
" ## Eq. 10.\n",
" d1=c1*b2-b6*c6; d2=c6*b7-b2*c2; d3=c1*b7-b6*c2; d4=c1*b1-b8*c6-b6*c5\n",
" d5=c5*b7+c6*b9-b1*c2-b2*c4; d6=c5*b9+c6*b5-b3*c2-b1*c4-b2*c3\n",
" d7=c1*b5-b8*c4-b6*c3; d8=c1*b9-b8*c2-b6*c4; d9=c1*b3-b8*c5\n",
" d10=c5*b5+c6*b4-b3*c4-b1*c3; d11=c1*b4-b8*c3; d12=c5*b4-b3*c3\n",
"\n",
" ## Eq. 9.\n",
" D1=d1*d2-d3**2; D2=d4*d2+d1*d5-2*d8*d3; D3=d9*d2+d4*d5+d1*d6-2*d7*d3-d8**2\n",
" D4=d9*d5+d4*d6+d1*d10-2*d11*d3-2*d7*d8\n",
" D5=d9*d6+d4*d10+d1*d12-2*d11*d8-d7**2\n",
" D6=d9*d10+d4*d12-2*d11*d7; D7=d9*d12-d11**2\n",
"\n",
" ## Eq. 8.\n",
" pol6=np.array([D1,D2,D3,D4,D5,D6,D7])\n",
" r6=np.roots(pol6)\n",
"\n",
" ## valós gyökök\n",
" a2 = r6.real[np.abs(r6.imag)<1e-12]\n",
"\n",
" ## számuk\n",
" n = a2.shape[0]\n",
" ## nincs megoldás: \n",
" if n == 0:\n",
" return 0\n",
" \n",
" ## a1 számítása\n",
" e1=c1*(b2*a2**2+b1*a2+b3)-(b6*a2+b8)*(c6*a2+c5)\n",
" e2=c1*(b7*a2**3+b9*a2**2+b5*a2+b4)-(b6*a2+b8)*(c2*a2**2+c4*a2+c3)\n",
" a1=-e2/e1\n",
" a = np.vstack((a1,a2,np.ones((1,n)))) \n",
" norma = np.sqrt(a[0,:]**2+a[1,:]**2+a[2,:]**2)\n",
" \n",
" ## f vektor számítása (5) egyenletekből\n",
" asq = a1**2+a2**2+1\n",
" ##\"f1, f2, f3\"\n",
" f1=p1*(1+a2**2)/asq/2\n",
" f2=(q1**2+q2**2+(q1*a2-q2*a1)**2)/2/asq\n",
" f2=(f2-q1*f1)/q2\n",
" f3=-(a1*f1+a2*f2)\n",
" f = np.vstack((f1,f2,f3))\n",
" ## az f vektor hossza a henger sugara: r=norm(f)\n",
" radius = np.sqrt(f[0,:]**2+f[1,:]**2+f[2,:]**2)\n",
"\n",
" ## visszatranszformálás - forgatás\n",
" a = (R.T).dot(a)\n",
" f = (R.T).dot(f)\n",
" ## f vektor végpontjának eltolása\n",
" f = (f.T + X1).T\n",
"\n",
" return np.vstack((radius,a/norma,f))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Egy ilyen bonyolult függvényt feltétlenül tesztelnünk kell. Nézzük meg Paul Zsombor-Murray, Sawsan El Fashny (2006) említett cikkében szereplő 2.1 példa adataival:"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"A henger illesztési 1. teszt eredménye:\n",
"[[ 1.55079 1.52273]\n",
" [ 0.01138 -0.32165]\n",
" [ 0.36146 -0.01544]\n",
" [ 0.93232 0.94673]\n",
" [ 1.49981 1.34481]\n",
" [ 0.36118 0.54156]\n",
" [-0.15834 0.46572]]\n"
]
}
],
"source": [
"## Paul Zsombor-Murray (2009): A Cylinder of Revolution on Five Points 2.1 példája\n",
"O=np.array([0,0,0]); P=np.array([3,0,0]); Q=np.array([2,2,0]); R=np.array([0,2,4]); S=np.array([2,0,3]); \n",
"cyl=cyl5fit(O,P,Q,R,S)\n",
"print( \"A henger illesztési 1. teszt eredménye:\")\n",
"np.set_printoptions(precision=5)\n",
"np.set_printoptions(suppress=True)\n",
"print( cyl)\n",
"# A henger illesztési teszt eredménye:"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"A cikkben csak az $\\mathbf{a}$ vektorok vannak megadva, és nem 1-re normalizálva, hanem úgy, hogy az $a_3$ összetevők értéke 1. Ezért átszámoljuk a megoldásunkban található $\\mathbf{a}$ vektorokat úgy, hogy a 3. komponens legyen 1. A cikkben ezek az értékek találhatók (számunkra most csak a 2 valós megoldás érdekes):\n",
"\n",
"\n",
"A vektorok átszámítását és kiíratását így végezhetjük el:"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"A mi megoldásunk: \n",
"[[ 1. 0.3876994216 0.0122101721]\n",
" [ 1. -0.0163069808 -0.339744343 ]]\n"
]
}
],
"source": [
"a = cyl[1:4,:]; an = a/a[2,:]\n",
"np.set_printoptions(precision=10)\n",
"print( \"A mi megoldásunk: \")\n",
"print( np.fliplr(an.T))"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Ahogy látjuk, az eredményeink megegyeznek a cikkben található példa eredményeivel."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Ahogy már említettük, a [scikit-image](http://scikit-image.org/) eljáráskönyvtárban található, és az\n",
"```python\n",
"import skimage.measure as sm\n",
"```\n",
"utasítás kiadása után a programban már használható. A RANSAC-hoz szükséges eljárásokat az `sm.py` modulba gyűjtöttük, igy elég azt importálni:\n",
"```python\n",
"import sm\n",
"```\n",
"Az\n",
"```python\n",
"sm.ransac(data, model_class, min_samples, residual_threshold) \n",
"```\n",
"függvénynek négy kötelező paramétere van. \n",
"1. Az adatok `data(N, D)` méretű tömbje, ahol `N` az adatok száma, `D` az adatok dimenziója,\n",
"2. a modellt megvalósító Python osztály (class), aminek kötelező tagfüggvényei a `success = estimate(*data)` és a `residuals(*data)`,\n",
"3. a `min_samples` egész szám, ami az előzőekben említett $n$.\n",
"4. a `residual_threshold`, a leírás alapján az adatpontnak az a maximális távolsága, amíg még konform, a modellhez illeszkedő adatnak számít.\n",
"\n",
"Elsőként a modellt megvalósító osztályt írjuk meg."
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### A CylModel Python osztály\n",
"\n",
"A RANSAC eljáráshoz szükséges osztályt (`CylModel`) most is csak egy egyszerű konstruktor és a két szükséges tagfüggvény (`estimate` és `residuals`) alkotja. A `params` 7 elemű vektor tagváltozó a henger paramétereit tárolja."
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"class CylModel:\n",
" \"\"\"egyenes körhenger illesztési modell \n",
" \"\"\"\n",
"\n",
" def __init__(self):\n",
" self.params = np.zeros(7)\n",
"\n",
" def estimate(self, X):\n",
" \"\"\"\n",
" cyl5fit(X) hengert illeszt 5, az X mátrix soraiban megadott pontra\n",
" Hivatkozás: Paul(2006): A Cylinder of revolution on Five Points\n",
" Eredmény: paraméter 7 elemű vektorban params: [r,ax,ay,az,fx,fy,fz], ahol:\n",
" r: a henger sugara\n",
" ax,ay,az: a henger tengelyének irányába mutató egységvektor\n",
" fx,fy,fz: a henger tengelyének egy pontja\n",
" Megjegyzés: Ha nincs jó megoldás, akkor a függvény visszatérési értéke False\n",
" \"\"\"\n",
"\n",
" ## eltolás O-ba:\n",
" o=X[0,:]-X[0,:]\n",
" pt=X[1,:]-X[0,:]\n",
" qt=X[2,:]-X[0,:]\n",
" rt=X[3,:]-X[0,:]\n",
" st=X[4,:]-X[0,:]\n",
"\n",
" ## elforgatás úgy, hogy OP=x, OQ=xy-síkban\n",
" x = pt/np.linalg.norm(pt)\n",
" y = qt-(np.inner(qt,pt))/np.linalg.norm(pt)*x\n",
" y = y/np.linalg.norm(y)\n",
" z = np.array([(x[1]*y[2]-x[2]*y[1]),(x[2]*y[0]-x[0]*y[2]),(x[0]*y[1]-x[1]*y[0])])\n",
" R = np.zeros((3,3))\n",
" R[0,:] = x; R[1,:] = y; R[2,:] = z\n",
" p = R.dot(pt)\n",
" q = R.dot(qt)\n",
" r = R.dot(rt)\n",
" s = R.dot(st)\n",
"\n",
" p1=p[0];q1=q[0];q2=q[1];r1=r[0];r2=r[1];r3=r[2]\n",
" s1=s[0];s2=s[1];s3=s[2]\n",
"\n",
" ## Eq. 11.\n",
" b1=2*q2*r2*(q1-r1); \n",
" b2=q2*r3*(p1-2*q1)\n",
" b3=q2*r3*(p1-2*r1)\n",
" b4=q2*(r1*(r1-p1)+r2*(r2-q2))+q1*r2*(p1-q1)\n",
" b5=r3*(q2*(q2-2*r2)+q1*(q1-p1)); b6=q2**2*r3\n",
" b7=q1*r3*(q1-p1)\n",
" b8=q2*(r2*(r2-q2)+r3**2)\n",
" b9=q2*(r1*(r1-p1)+r3**2)+q1*r2*(p1-q1)\n",
" ##\n",
" c1=q2*(r2*s3*(r2-q2)+r3*s2*(q2-s2)+r3*s3*(r3-s3))\n",
" c2=q2*r3*s3*(r3-s3)+q1**2*(r3*s2-r2*s3)+p1*(q2*(r3*s1-r1*s3)+q1*(r2*s3-r3*s2)) \\\n",
" +q2*(r1**2*s3-r3*s1**2)\n",
" c3=q2*(p1*(s1*r3-s3*r1)-r3*(s1**2+s2**2)+s3*(r1**2+r2**2)) \\\n",
" +(r2*s3-r3*s2)*(q1*(p1-q1)-q2**2)\n",
" c4=2*q2*r3*s3*(s2-r2); c5=2*q2*r3*s3*(s1-r1)\n",
" c6=2*q2*(r3*s2*(s1-q1)+r2*s3*(q1-r1))\n",
"\n",
" ## Eq. 10.\n",
" d1=c1*b2-b6*c6; d2=c6*b7-b2*c2; d3=c1*b7-b6*c2; d4=c1*b1-b8*c6-b6*c5\n",
" d5=c5*b7+c6*b9-b1*c2-b2*c4; d6=c5*b9+c6*b5-b3*c2-b1*c4-b2*c3\n",
" d7=c1*b5-b8*c4-b6*c3; d8=c1*b9-b8*c2-b6*c4; d9=c1*b3-b8*c5\n",
" d10=c5*b5+c6*b4-b3*c4-b1*c3; d11=c1*b4-b8*c3; d12=c5*b4-b3*c3\n",
"\n",
" ## Eq. 9.\n",
" D1=d1*d2-d3**2; D2=d4*d2+d1*d5-2*d8*d3; D3=d9*d2+d4*d5+d1*d6-2*d7*d3-d8**2\n",
" D4=d9*d5+d4*d6+d1*d10-2*d11*d3-2*d7*d8\n",
" D5=d9*d6+d4*d10+d1*d12-2*d11*d8-d7**2\n",
" D6=d9*d10+d4*d12-2*d11*d7; D7=d9*d12-d11**2\n",
"\n",
" ## Eq. 8.\n",
" pol6=np.array([D1,D2,D3,D4,D5,D6,D7])\n",
" r6=np.roots(pol6)\n",
"\n",
" ## valós gyökök\n",
" a2 = r6.real[np.abs(r6.imag)<1e-12]\n",
"\n",
" ## számuk\n",
" n = a2.shape[0]\n",
" ## nincs megoldás: \n",
" if n == 0:\n",
" return False\n",
"\n",
" ## a1 számítása\n",
" e1=c1*(b2*a2**2+b1*a2+b3)-(b6*a2+b8)*(c6*a2+c5)\n",
" e2=c1*(b7*a2**3+b9*a2**2+b5*a2+b4)-(b6*a2+b8)*(c2*a2**2+c4*a2+c3)\n",
" a1=-e2/e1\n",
" a = np.vstack((a1,a2,np.ones((1,n)))) \n",
" norma = np.sqrt(a[0,:]**2+a[1,:]**2+a[2,:]**2)\n",
" \n",
" ## f vektor számítása (5) egyenletekből\n",
" asq = a1**2+a2**2+1\n",
" ##\"f1, f2, f3\"\n",
" f1=p1*(1+a2**2)/asq/2\n",
" f2=(q1**2+q2**2+(q1*a2-q2*a1)**2)/2/asq\n",
" f2=(f2-q1*f1)/q2\n",
" f3=-(a1*f1+a2*f2)\n",
" f = np.vstack((f1,f2,f3))\n",
" ## az f vektor hossza a henger sugara: r=norm(f)\n",
" radius = np.sqrt(f[0,:]**2+f[1,:]**2+f[2,:]**2)\n",
"\n",
" ## visszatranszformálás - forgatás\n",
" a = (R.T).dot(a)\n",
" f = (R.T).dot(f)\n",
" ## f vektor végpontjának eltolása\n",
" f = (f.T + X[0,:]).T\n",
" ## az összes megoldás\n",
" p = np.vstack((radius,a/norma,f))\n",
" ## csak az első megoldást használjuk\n",
" self.params = p[:,0]\n",
"\n",
" return True\n",
" \n",
" def residuals(self, X, pos=1):\n",
" \"\"\"\n",
" residuals(X) az X pontok távolságát számítja ki a cyl hengertől\n",
" params: 7-elemű vektor: [r, a, f]\n",
" r: a henger sugara\n",
" a: henger tengely egységvektora\n",
" f: a henger tengely egy pontjának helyvektora\n",
" X: (n,3) mátrix, az n db. pont koordinátái\n",
" pos: ha pos=0, előjeles távolságokat számít ki, egyébként nem\n",
" \"\"\"\n",
" r = self.params[0]\n",
" a = self.params[1:4]\n",
" f = self.params[4:]\n",
" xf = X-f\n",
" # norma négyzete\n",
" nxf = xf[:,0]**2+xf[:,1]**2+xf[:,2]**2\n",
" if pos==1:\n",
" dist = np.abs(np.sqrt(nxf - ((X-f).dot(a))**2) - r)\n",
" else:\n",
" dist = np.sqrt(nxf - ((X-f).dot(a))**2) - r\n",
" return dist"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Teszt adatok\n",
"\n",
"Az alábbi teszt [adatokat](./dat/cyl.dat) használjuk fel. Először ezeket beolvassuk, majd a beolvasott pontfelhőt kirajzoltatjuk."
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [
{
"data": {
"image/png": 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\n",
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