CODEWITHSUNDEEP
pythonopencvdrawing
DaveA
DaveA

Reputation: 1287

What does the python interface to opencv2.fillPoly want as input?

I'm trying to draw a polygon using the python interface to opencv, cv2. I've created an empty image, just a 640x480 numpy array. I have a list of polygons (four point quadrilaterals) that I want to draw on the image, however, I can't seem to get the formate right to instruct cv2 where the quadrilaterals should be, and I keep getting this error:

OpenCV Error: Assertion failed (points.checkVector(2, CV_32S) >= 0) in fillConvexPoly, file .../OpenCV-2.4.0/modules/core/src/drawing.cpp, line 2017

My code consists of essentially the following:

binary_image = np.zeros(image.shape,dtype='int8')
for rect in expected:
    print(np.array(rect['boundary']))
    cv2.fillConvexPoly(binary_image, np.array(rect['boundary']), 255)
fig = pyplot.figure(figsize=(16, 14))
ax = fig.add_subplot(111)
ax.imshow(binary_image)
pyplot.show()

where my list of rects in expected has the 'boundary' containing the value of a list of (x,y) points. The code prints:

[[ 91 233]
 [419 227]
 [410 324]
 [ 94 349]]

I figured that this is the list of points for a polygon, but apparently that list has an invalid points.checkvector, whatever that is. A google search for that error turned up nothing useful.

Upvotes: 37

Views: 64950

Answers (5)

AlwaysAStudent
AlwaysAStudent

Reputation: 1

Here is an example that might help.

def region_of_interest(image):
    height = image.shape[0]
    polygons = np.array([
      [(200,height),(1100,height ),(550,250)]])
    mask = np.zeros_like(image)
    cv2.fillPoly(mask, polygons, 255)
    return mask

Upvotes: -1

stackoverflowuser2010
stackoverflowuser2010

Reputation: 40969

Here's an example with annotated points. You can specify the polygon vertices in either clockwise or counter-clockwise order, as long as they follow the same direction.

import numpy as np
import matplotlib.pyplot as plt
import cv2

A = np.array([125,50])
B = np.array([50,50])
C = np.array([50,175])
D = np.array([150,150])

pts = np.array( [ A, B, C, D ] ) # counter-clockwise
#pts = np.array( [ A, D, C, B ] ) # clockwise

print(pts.shape) # (4, 2)

image = np.zeros((200,200), dtype=np.uint8)
image = np.dstack((image, image, image)) # Create three channels.

cv2.fillPoly(image, pts=[pts], color =(0,255,0))

for pt in pts:
    x = pt[0]
    y = pt[1]
    _ = plt.annotate(s='%d, %d' % (x, y), xy=(x, y), color='red', fontsize=20)

print(image.shape) # (200, 200, 3)

plt.imshow(image)
plt.grid(True)
plt.show()

enter image description here

What happens if your vertices are rearranged so that they don't follow the same direction?

pts = np.array( [ A, B, D, C ] )

You get this:

enter image description here

Upvotes: 2

themadmax
themadmax

Reputation: 2404

import numpy as np
import cv2
import matplotlib.pyplot as plt

a3 = np.array( [[[10,10],[100,10],[100,100],[10,100]]], dtype=np.int32 )
im = np.zeros([240,320],dtype=np.uint8)
cv2.fillPoly( im, a3, 255 )

plt.imshow(im)
plt.show()

result display

Check on colab.research.google.com

Upvotes: 40

adrien g
adrien g

Reputation: 186

The AssertionError is telling you that OpenCV wants a signed, 32-bit integer. The array of polygon points should have that particular data type (e.g. points = numpy.array(A,dtype='int32') ). You could also just cast it for the function call (i.e. my_array.astype('int32') ) or as a friend put it once...

" Changing

   cv2.fillConvexPoly(binary_image, np.array(rect['boundary']), 255) to

   cv2.fillConvexPoly(binary_image, np.array(rect['boundary'], 'int32'), 255) "

Upvotes: 17

Cheaster
Cheaster

Reputation: 71

I have tried in opencv 2.4.2 and python 2.7. From the c++ interface 

void fillPoly(Mat& img, 
              const Point** pts, 
              const int* npts, 
              int ncontours, 
              const Scalar& color, 
              int lineType=8, 
              int shift=0, 
              Point offset=Point() 
             )

we know the pts is the array of array of points, so you should change like this

cv2.fillConvexPoly(binary_image, np.array([rect['boundary']], 'int32'), 255)

add [ ] to the rect['boundary'].

Upvotes: 7

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