def myputText(img,text,font,scale,origin,color,thickness,lineType):
thickness=int(thickness)
scale=int(scale)
color=Point.point_int(color)
font = cv2.FONT_HERSHEY_SIMPLEX
if linetype == 8 :
cv2.putText(img,text,org,font,scale,color, thickness,lineType=8)
def blur(img,kernel_size):
if img is None:
print 'Error in input Image'
return 0
kernel_size=Point.point_int(kernel_size)
blurimage = cv2.blur(img,kernel_size)
return blurimage
def kernel(kernel_type,array_size):
size=Point.point_int(array_size)
kernel_type=int(kernel_type)
if kernel_type==1:
kernel=cv2.getStructuringElement(cv2.MORPH_RECT,size)
if kernel_type==2:
kernel=cv2.getStructuringElement(cv2.MORPH_ELLIPSE,size)
if kernel_type==3:
kernel=cv2.getStructuringElement(cv2.MORPH_CROSS,size)
return kernel
def ORB(image,features,scaleFactor,color,displayimage):
color=Point.point_int(color)
features=int(features)
scaleFactor=int(scaleFactor)
if image is None:
print 'Error in input Image'
return 0,0
orb = cv2.ORB(features,scaleFactor)
kp, des = orb.detectAndCompute(image,None)
img2 = cv2.drawKeypoints(image,kp,color, flags=0)
if displayimage==1:
cv2.imshow("image",img2)
cv2.waitKey(0)
return (kp,des)
def grabcut(image,mask,bgdModel,fgdModel,rect,iterations,mode):
iterations=int(iterations)
rect = Point.point_int(rect)
if mode ==1:
cv2.grabCut(image,mask,rect,bgdModel,fgdModel,iterations,cv2.GC_INIT_WITH_RECT)
mask2 = np.where((mask==2)|(mask==0),0,1).astype('uint8')
image = image*mask2[:,:,np.newaxis]
elif mode==2:
newmask=mask
mask[newmask == 0] = 0
mask[newmask == 255] = 1
mask, bgdModel, fgdModel = cv2.grabCut(image,mask,None,bgdModel,fgdModel,iterations,cv2.GC_INIT_WITH_MASK)
mask = np.where((mask==2)|(mask==0),0,1).astype('uint8')
image = image*mask[:,:,np.newaxis]
else:
print "Please check the mode"
return image
def gaussianFilter(image, kernel_type,kernel_size, sigmaX, sigmaY):
if image is None:
print 'Error in input Image'
return 0
kernel_size=Point.point_int(kernel_size)
if sigmaY==0 and sigmaX==0:
sigmaX=kernel_size[0]
sigmaY=kernel_size[1]
kernel=Kernel.kernel(kernel_type,kernel_size)
sigmaColor = int(sigmaX)
sigmaSpace = int(sigmaY)
if kernel_size[0]%2==0 and kernel_size[1]%2==0:
print 'The kernel size should be odd'
return 0
image=cv2.GaussianBlur(image,kernel_size , sigmaColor, sigmaSpace)
return image
import cv2
import numpy as np
import Point
def rect(img,start,end,color,linetype,thickness):
thickness=int(thickness)
color=Point.point_int(color)
start=Point.point_int(start)
end=Point.point_int(end)
if linetype == 8 :
cv2.rectangle(img,start,end,color,thickness,lineType=8)
elif linetype == 4 :
cv2.rectangle(img,start,end,color,thickness,lineType=4)
else:
cv2.rectangle(img,start,end,color,thickness,lineType=CV_AA)
return img
