I want to use edge detection algorithms from opencv library. Here is a piece of python code:
from opencv.cv import *
from opencv.highgui import *
img = cvLoadImage ('xxx.jpg')
cvNamedWindow ('img')
cvShowImage ('img', img)
cvWaitKey ()
canny = cvCreateImage (cvSize (img.width, img.height), 8, 3)
cvCanny (img, canny, 50, 200)
harris = cvCreateImage (cvSize (img.width, img.height), 8, 3)
cvCornerHarris (img, harris, 5, 5, 0.1)
Loading and showing image works fine, but canny and harris transformations fail.
cvCanny
fails with:
RuntimeError: openCV Error:
Status=Unsupported format or combination of formats
function name=cvCanny
error message=
file_name=cv/cvcanny.cpp
line=72
and cvCornerHarris
fails with this error:
RuntimeError: openCV Error:
Status=Assertion failed
function name=cvCornerHarris
开发者_如何学Python error message=src.size() == dst.size() && dst.type() == CV_32FC1
file_name=cv/cvcorner.cpp
line=370
From this messages I can infer that loaded image has invalid format. But I don't understand how to convert it.
Here are values of someimg
fields:
img.type = 1111638032
img.nChannels = 3
img.depth = 8
For other folks interested in the same type of problem I recommend checking out http://simplecv.org
Here is a bit of code I wrote that does line detection on an image acquired from a webcam. It will even display the image over http.
import SimpleCV
import time
c = SimpleCV.Camera(1)
js = SimpleCV.JpegStreamer()
while(1):
img = c.getImage()
img = img.smooth()
lines = img.findLines(threshold=25,minlinelength=20,maxlinegap=20)
[line.draw(color=(255,0,0)) for line in lines]
#find the avg length of the lines
sum = 0
for line in lines:
sum = line.length() + sum
if sum:
print sum / len(lines)
else:
print "No lines found!"
img.save(js.framebuffer)
time.sleep(0.1)
Check out the project I made this for at http://labs.radiantmachines.com/beard/ It will detect how long your neck beard is :)
Here's fixed code. See comments inline. Long story short: your data types were wrong. Read the API.
try:
from opencv.cv import *
from opencv.highgui import *
except:
#
# Different OpenCV installs name their packages differently.
#
from cv import *
if __name__ == '__main__':
import sys
#
# 1 = Force the image to be loaded as RGB
#
img = LoadImage (sys.argv[1], 1)
NamedWindow ('img')
ShowImage ('img', img)
WaitKey ()
#
# Canny and Harris expect grayscale (8-bit) input.
# Convert the image to grayscale. This is a two-step process:
# 1. Convert to 3-channel YCbCr image
# 2. Throw away the chroma (Cb, Cr) and keep the luma (Y)
#
yuv = CreateImage(GetSize(img), 8, 3)
gray = CreateImage(GetSize(img), 8, 1)
CvtColor(img, yuv, CV_BGR2YCrCb)
Split(yuv, gray, None, None, None)
canny = CreateImage(GetSize(img), 8, 1)
Canny(gray, canny, 50, 200)
NamedWindow ('canny')
ShowImage ('canny', canny)
WaitKey()
#
# The Harris output must be 32-bit float.
#
harris = CreateImage (GetSize(img), IPL_DEPTH_32F, 1)
CornerHarris(gray, harris, 5, 5, 0.1)
You can convert an image to grayscale in a single step instead of two:
gray = cv.CreateMat(img.height, img.width, cv.CV_8UC1)
cv.CvtColor(img, gray, cv.CV_BGR2GRAY)
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