Cropping Concave polygon from Image using Opencv python

Question

How can I crop a concave polygon from an image. My Input image look like .

and the coordinates of closed polygon are [10,150],[150,100],[300,150],[350,100],[310,20],[35,10]. I want region bounded by concave polygon to be cropped using opencv. I searched for other similar questions but I did not able to find correct answer. That's why I am asking it ? Can you help me.

Any help would be highly appreciated.!!!

Answer 1

Steps

1. find region using the poly points
2. create mask using the poly points
3. do mask op to crop
4. add white bg if needed

The code:

# 2018.01.17 20:39:17 CST
# 2018.01.17 20:50:35 CST
import numpy as np
import cv2

img = cv2.imread("test.png")
pts = np.array([[10,150],[150,100],[300,150],[350,100],[310,20],[35,10]])

## (1) Crop the bounding rect
rect = cv2.boundingRect(pts)
x,y,w,h = rect
croped = img[y:y+h, x:x+w].copy()

## (2) make mask
pts = pts - pts.min(axis=0)

mask = np.zeros(croped.shape[:2], np.uint8)
cv2.drawContours(mask, [pts], -1, (255, 255, 255), -1, cv2.LINE_AA)

## (3) do bit-op
dst = cv2.bitwise_and(croped, croped, mask=mask)

## (4) add the white background
bg = np.ones_like(croped, np.uint8)*255
cv2.bitwise_not(bg,bg, mask=mask)
dst2 = bg+ dst


cv2.imwrite("croped.png", croped)
cv2.imwrite("mask.png", mask)
cv2.imwrite("dst.png", dst)
cv2.imwrite("dst2.png", dst2)

---

Source image:

Result:

Answer 2

You can do it in 3 steps:

1. Create a mask out of the image

   mask = np.zeros((height, width)) points = np.array([[[10,150],[150,100],[300,150],[350,100],[310,20],[35,10]]]) cv2.fillPoly(mask, points, (255))

2. Apply mask to original image

   res = cv2.bitwise_and(img,img,mask = mask)

3. Optionally you can remove the crop the image to have a smaller one

   rect = cv2.boundingRect(points) # returns (x,y,w,h) of the rect cropped = res[rect[1]: rect[1] + rect[3], rect[0]: rect[0] + rect[2]]

With this you should have at the end the image cropped

UPDATE

For the sake of completeness here is the complete code:

import numpy as np
import cv2

img = cv2.imread("test.png")
height = img.shape[0]
width = img.shape[1]

mask = np.zeros((height, width), dtype=np.uint8)
points = np.array([[[10,150],[150,100],[300,150],[350,100],[310,20],[35,10]]])
cv2.fillPoly(mask, points, (255))

res = cv2.bitwise_and(img,img,mask = mask)

rect = cv2.boundingRect(points) # returns (x,y,w,h) of the rect
cropped = res[rect[1]: rect[1] + rect[3], rect[0]: rect[0] + rect[2]]

cv2.imshow("cropped" , cropped )
cv2.imshow("same size" , res)
cv2.waitKey(0)

---

For the colored background version use the code like this:

import numpy as np
import cv2

img = cv2.imread("test.png")
height = img.shape[0]
width = img.shape[1]

mask = np.zeros((height, width), dtype=np.uint8)
points = np.array([[[10,150],[150,100],[300,150],[350,100],[310,20],[35,10]]])
cv2.fillPoly(mask, points, (255))

res = cv2.bitwise_and(img,img,mask = mask)

rect = cv2.boundingRect(points) # returns (x,y,w,h) of the rect
im2 = np.full((res.shape[0], res.shape[1], 3), (0, 255, 0), dtype=np.uint8 ) # you can also use other colors or simply load another image of the same size
maskInv = cv2.bitwise_not(mask)
colorCrop = cv2.bitwise_or(im2,im2,mask = maskInv)
finalIm = res + colorCrop
cropped = finalIm[rect[1]: rect[1] + rect[3], rect[0]: rect[0] + rect[2]]

cv2.imshow("cropped" , cropped )
cv2.imshow("same size" , res)
cv2.waitKey(0)

Answer 3

For the blured image background version use the code like this:

    img = cv2.imread(img_path)
    box = <box points>

    # -- background
    blur_bg = cv2.blur(img, (h, w))
    mask1 = np.zeros((h, w, 3), np.uint8)
    mask2 = np.ones((h, w, 3), np.uint8) * 255
    cv2.fillPoly(mask1, box, (255, 255, 255))

    # -- indexing
    img_idx = np.where(mask1 == mask2)
    bg_idx = np.where(mask1 != mask2)
    
    # -- fill box
    res = np.zeros((h, w, 3), np.int64)
    res[img_idx] = img[img_idx]
    res[bg_idx] = blur_bg[bg_idx]
    res = res[y1:y2, x1:x2, :]