def processImage(self, curframe):
cv.Smooth(curframe, curframe) #Remove false positives
if not self.absdiff_frame: #For the first time put values in difference, temp and moving_average
self.absdiff_frame = cv.CloneImage(curframe)
self.previous_frame = cv.CloneImage(curframe)
cv.Convert(
curframe, self.average_frame
) #Should convert because after runningavg take 32F pictures
else:
cv.RunningAvg(curframe, self.average_frame,
0.05) #Compute the average
cv.Convert(self.average_frame,
self.previous_frame) #Convert back to 8U frame
cv.AbsDiff(curframe, self.previous_frame,
self.absdiff_frame) # moving_average - curframe
cv.CvtColor(
self.absdiff_frame, self.gray_frame,
cv.CV_RGB2GRAY) #Convert to gray otherwise can't do threshold
cv.Threshold(self.gray_frame, self.gray_frame, 50, 255,
cv.CV_THRESH_BINARY)
cv.Dilate(self.gray_frame, self.gray_frame, None,
15) #to get object blobs
cv.Erode(self.gray_frame, self.gray_frame, None, 10)
def __produce_gradient_image(self, i, scale):
size = cv.GetSize(i)
grey_image = cv.CreateImage(size, 8, 1)
size = [s/scale for s in size]
grey_image_small = cv.CreateImage(size, 8, 1)
cv.CvtColor(i, grey_image, cv.CV_RGB2GRAY)
df_dx = cv.CreateImage(cv.GetSize(i), cv.IPL_DEPTH_16S, 1)
cv.Sobel( grey_image, df_dx, 1, 1)
cv.Convert(df_dx, grey_image)
cv.Resize(grey_image, grey_image_small)#, interpolation=cv.CV_INTER_NN)
cv.Resize(grey_image_small, grey_image)#, interpolation=cv.CV_INTER_NN)
return grey_image
def FFT(image,flag = 0):
w = image.width
h = image.height
iTmp = cv.CreateImage((w,h),cv.IPL_DEPTH_32F,1)
cv.Convert(image,iTmp)
iMat = cv.CreateMat(h,w,cv.CV_32FC2)
mFFT = cv.CreateMat(h,w,cv.CV_32FC2)
for i in range(h):
for j in range(w):
if flag == 0:
num = -1 if (i+j)%2 == 1 else 1
else:
num = 1
iMat[i,j] = (iTmp[i,j]*num,0)
cv.DFT(iMat,mFFT,cv.CV_DXT_FORWARD)
return mFFT
def applyEffect(self, image, width, height):
ipl_img = cv2.cv.CreateImageHeader((image.shape[1], image.shape[0]), cv.IPL_DEPTH_8U, 3)
cv2.cv.SetData(ipl_img, image.tostring(), image.dtype.itemsize * 3 * image.shape[1])
gray = cv.CreateImage((width, height), 8, 1) # tuple as the first arg
dst_img = cv.CreateImage(cv.GetSize(ipl_img), cv.IPL_DEPTH_8U, 3) # _16S => cv2.cv.iplimage
if self.effect == 'dilate':
cv.Dilate(ipl_img, dst_img, None, 5)
elif self.effect == 'laplace':
cv.Laplace(ipl_img, dst_img, 3)
elif self.effect == 'smooth':
cv.Smooth(ipl_img, dst_img, cv.CV_GAUSSIAN)
elif self.effect == 'erode':
cv.Erode(ipl_img, dst_img, None, 1)
cv.Convert(dst_img, ipl_img)
return self.ipl2tk_image(dst_img)