问题
I am new to opencv. I have multiple images. One of sample image as shown below at top left corner. Basically I want to separate background and foreground so that edges are clear and I can detect contours properly.
I have tried many filter and of course thresholds using various parameters.
Finally when I was looking on photoshop filters gallery I noticed a filter called Stamp which is giving me desired result(top-right corner). It makes edges clear and I guess use some amount of blur to soft corners.
I am not sure how I can obtain same operation as photoshop's stamp filter using python CV2?
Any help or suggestions will be grateful.
Original Untouched Image
Attempt 1: -- Code
import cv2
import numpy as np
from matplotlib import pyplot as plt
input_img = cv2.imread('images/Tas/t3.bmp')
desired_img = cv2.imread('images/stamp.jpg')
# gray scale
gray = cv2.cvtColor(input_img, cv2.COLOR_BGR2GRAY)
kernel = np.ones((3,3),np.uint8)
thresh1 = cv2.threshold(input_img,80,255,cv2.THRESH_BINARY)[1]
erosion1 = cv2.erode(thresh1,kernel,iterations = 1)
dilation1 = cv2.dilate(erosion1,kernel,iterations = 1)
thresh2 = cv2.threshold(input_img,120,255,cv2.THRESH_BINARY)[1]
erosion2 = cv2.erode(thresh2,kernel,iterations = 1)
dilation2 = cv2.dilate(erosion2,kernel,iterations = 1)
titles = ['Original', 'Desired','thresh1', 'erosion1','dilation1','thresh2','erosion2','dilation2']
images = [input_img, desired_img, thresh1, erosion1,dilation1, thresh2,erosion2, dilation2]
for i in xrange(8):
plt.subplot(2,4,i+1),plt.imshow(images[i])
plt.title(titles[i])
plt.xticks([]),plt.yticks([])
plt.show()
Output:
回答1:
It might help to add yourself a couple of sliders for Gaussian Blur and Threshold filtering and you can get pretty decent results:
and here's the basic snippet I used to generate it:
import numpy as np
import cv2
import cv2.cv as cv
from matplotlib import pyplot as plt
# slider callbacks
def printThreshold(x):
print "threshold",x
def printGaussianBlur(x):
print "gaussian blur kernel size",x
# make a window to add sliders/preview to
cv2.namedWindow('processed')
#make some sliders
cv2.createTrackbar('threshold','processed',60,255,printThreshold)
cv2.createTrackbar('gaussian blur','processed',3,10,printGaussianBlur)
# load image
img = cv2.imread('cQMgT.png',0)
# continously process for quick feedback
while 1:
# exit on ESC key
k = cv2.waitKey(1) & 0xFF
if k == 27:
break
# Gaussian Blur ( x2 +1 = odd number for kernel size)
kernelSize = ((cv2.getTrackbarPos('gaussian blur','processed') * 2) + 1)
blur = cv2.GaussianBlur(img,(kernelSize,kernelSize),0)
# Threshold
ret,thresh = cv2.threshold(blur,cv2.getTrackbarPos('threshold','processed',),255,0)
# show result
cv2.imshow('processed ',thresh)
# exit
cv2.destroyAllWindows()
Feel free to add other filters to the mix and experiment with sliders.
来源:https://stackoverflow.com/questions/43758096/opencv-python-stamp-filter-photoshop