How to get a list of points inside a polygon in python?

Question

I searched a lot and could not find a practical answer to my question. I have a polygon. For example:

    [(86, 52), (85, 52), (81, 53), (80, 52), (79, 48), (81, 49), (86, 53),
     (85, 51), (82, 54), (84, 54), (83, 49), (81, 52), (80, 50), (81, 48),
     (85, 50), (86, 54), (85, 54), (80, 48), (79, 50), (85, 49), (80, 51),
     (85, 53), (82, 49), (83, 54), (82, 53), (84, 49), (79, 49)]

I want to get a list of all the points inside this border polygon. I heard a lot about polygon triangulation methods or linear / flood / intersection / ... fill algorithms. but I cannot find an effective way to implement this. This poly is small, imagine a polygon with 1 billion points. Now I use the PIL polygon to fill the poly red color and the loops inside it to find the red dots. This is a terribly slow technique:

def render(poly, z):
    xs = [i[0] for i in poly]
    ys = [i[1] for i in poly]
    minx, maxx = min(xs), max(xs)
    miny, maxy = min(ys), max(ys)
    X = maxx - minx + 1
    Y = maxy - miny + 1
    newPoly = [(x - minx, y - miny) for (x, y) in polygons]
    i = Image.new("RGB", (X, Y))
    draw = ImageDraw.Draw(i)
    draw.polygon(newPoly, fill="red")
    # i.show()
    tiles = list()
    w, h = i.size
    print w, h
    for x in range(w):
        for y in range(h):
            data = i.getpixel((x, y))
            if data != (0, 0, 0):
                tiles.append((x + minx, y + miny))

    return tiles

I am looking for a Pythonic method to solve this problem. Thanks to everyone.

Answer 1

matplotlib contains_points()

from matplotlib.path import Path

tupVerts=[(86, 52), (85, 52), (81, 53), (80, 52), (79, 48), (81, 49), (86, 53),
 (85, 51), (82, 54), (84, 54), (83, 49), (81, 52), (80, 50), (81, 48),
 (85, 50), (86, 54), (85, 54), (80, 48), (79, 50), (85, 49), (80, 51),
 (85, 53), (82, 49), (83, 54), (82, 53), (84, 49), (79, 49)]


x, y = np.meshgrid(np.arange(300), np.arange(300)) # make a canvas with coordinates
x, y = x.flatten(), y.flatten()
points = np.vstack((x,y)).T 

p = Path(tupVerts) # make a polygon
grid = p.contains_points(points)
mask = grid.reshape(300,300) # now you have a mask with points inside a polygon

Answer 2

, - , - , C. RGB-, - numpy.where(), , .

mahotas fill_polygon, numpy.

( minx maxx), , , dev.

import numpy as np
import mahotas

def render(poly, z):
    xs = [i[0] for i in poly]
    ys = [i[1] for i in poly]
    minx, maxx = min(xs), max(xs)
    miny, maxy = min(ys), max(ys)
    X = maxx - minx + 1
    Y = maxy - miny + 1
    newPoly = [(x - minx, y - miny) for (x, y) in polygons]

    grid = np.zeros((X, Y), dtype=np.int8)
    mahotas.polygon.fill_polygon(newPoly, grid)

    return [(x + minx, y + miny) for (x, y) in np.where(grid)]

Answer 3

numpy, ​​ , Opencv, , , 1 , , L x H,

L=max(x) - min (x)
H=max(y) - min (y)

(x, y), , poly, :

import numpy as np
matrix =np.zeros((L,H),dtype=np.int32) # you can use np.uint8 if unsigned x ,y

, L x H, 0, 1

,

matrix[poly]=1  # which will put 1 at each (x,y) of the list **poly**

(-) , ,

import cv2 # opencv import
ContoursListe,hierarchy = cv2.findContours(self.thresh,cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_NONE)
poly2=ContoursListe[0] # we take the first only contour

: poly2 , , , , !! cv2.CHAIN_APPROX_SIMPLE, poly2, , :) : poly2 - numpy, (n, 1,2) not (n, 2)

() :)

cv2.drawContours(matrix,[poly2],-1,(1),thickness=-1) thickness=-1

, , , 1, " = -1" , = 1, , , offset (xtran, ytrans)

,

list_of_points_indices=numpy.nonzero(matrix)

---

2

, (poly) (poly2)

poly2=poly.reshape(-1,1,2).astype(np.int32)

matrix =np.zeros((L,H),dtype=np.int32)

cv2.drawContours(matrix,[poly2],-1,(1),thickness=-1)

:

list_of_points_indices=numpy.nonzero(matrix)

, , . 1 .

Answer 4

RemcoGerlich, :

import numpy as np
import mahotas

def render(poly):
    """Return polygon as grid of points inside polygon.

    Input : poly (list of lists)
    Output : output (list of lists)
    """
    xs, ys = zip(*poly)
    minx, maxx = min(xs), max(xs)
    miny, maxy = min(ys), max(ys)

    newPoly = [(int(x - minx), int(y - miny)) for (x, y) in poly]

    X = maxx - minx + 1
    Y = maxy - miny + 1

    grid = np.zeros((X, Y), dtype=np.int8)
    mahotas.polygon.fill_polygon(newPoly, grid)

    return [(x + minx, y + miny) for (x, y) in zip(*np.nonzero(grid))]

:

poly = [
    [0, 0],
    [0, 10],
    [10, 10],
    [10, 0]
]

plt.figure(None, (5, 5))
x, y = zip(*render(poly))
plt.scatter(x, y)
x, y = zip(*poly)
plt.plot(x, y, c="r")
plt.show()

Answer 5

. poly_coords - , - , , .

def testP(coord, poly_coords):
    """
    The coordinates should be in the form of list of x and y
    """
    test1 = n.array(poly_coords)
    test2 = n.vstack((poly_coords[1:], poly_coords[:1]))
    test  = test2-test1
    m = test[:,1]/test[:,0]
    c = test1[:,1]-m*test1[:,0]
    xval = (coord[1]-c)/m
    print 'xVal:\t'; print xval
    print (test1[:,0]-xval)*(test2[:,0]-xval)
    check = n.where((xval>=coord[0])&((test1[:,0]-xval)*(test2[:,0]-xval)<0))[0]
    print check
    print len(check)
    if len(check)%2==0:
        return False
    else:
        return True

, , , , , "map". - :

test1 = n.array( your polygon)
test2 = n.vstack((test1[1:], test1[:1]))
test  = test2-test1
m = test[:,1]/test[:,0]
c = test1[:,1]-m*test1[:,0]

def testP(coord):
    """
    The coordinates should be in the form of list of x and y
    """
    global test, test1, test2, m,c
    xval = (coord[1]-c)/m
    check = n.where((xval>=coord[0])&((test1[:,0]-xval)*(test2[:,0]-xval)<0))[0]
    if len(check)%2==0:
        return False
    else:
        return True
coords = n.array(( your coords in x,y ))
map (testP, coords)

"print", . python 2.7