Does anyone have any examples of using OpenCV with python for descriptor extraction?

Question

I'm trying to use OpenCV to extract SURF descriptors from an image. I'm using OpenCV 2.4 and Python 2.7, but am struggling to find any documentation that provides any information about how to use the functions. I've been able to use the following code to extract features, but I can't find any sensible way to extract descriptors:

import cv2

img = cv2.imread("im1.jpg")
img2 = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

surf = cv2.FeatureDetector_create('SURF')
detector = cv2.GridAdaptedFeatureDetector(surf, 50) # max number of features
fs = detector.detect(img2)

The code I tried for extracting descriptors is:

import cv2
img = cv2.imread("im3.jpg")
sd = cv2.FeatureDetector_create("SURF")
surf = cv2.DescriptorExtractor_create("SURF")
keypoints = []
fs = surf.compute(img, keypoints) # returns empty result
sd.detect(img) # segmentation faults

Does anyone have any sample code that does this kind of thing, or pointers to any documentation that provides samples?

Answer 1

Here's an example of some code I've written for extracting SURF features using Python 2.7 and OpenCV 2.4.

im2 = cv2.imread(imgPath)
im = cv2.cvtColor(im2, cv2.COLOR_BGR2GRAY)
surfDetector = cv2.FeatureDetector_create("SURF")
surfDescriptorExtractor = cv2.DescriptorExtractor_create("SURF")
keypoints = surfDetector.detect(im)
(keypoints, descriptors) = surfDescriptorExtractor.compute(im,keypoints)

This works and returns a set of descriptors. Unfortunately since cv2.SURF() doesn't work in 2.4, you have to go through this tedious process.

Answer 2

Here is a simple bit of code I did for uni fairly recently. It captures the image from a camera and displays the detected keypoints on the output image in real-time. I hope it is of use to you.

There is some documentation here.

Code:

import cv2

#Create object to read images from camera 0
cam = cv2.VideoCapture(0)

#Initialize SURF object
surf = cv2.SURF(85)

#Set desired radius
rad = 2

while True:
    #Get image from webcam and convert to greyscale
    ret, img = cam.read()
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    #Detect keypoints and descriptors in greyscale image
    keypoints, descriptors = surf.detect(gray, None, False)

    #Draw a small red circle with the desired radius
    #at the (x, y) location for each feature found
    for kp in keypoints:
        x = int(kp.pt[0])
        y = int(kp.pt[1])
        cv2.circle(img, (x, y), rad, (0, 0, 255))

    #Display colour image with detected features
    cv2.imshow("features", img)

    #Sleep infinite loop for ~10ms
    #Exit if user presses <Esc>
    if cv2.waitKey(10) == 27:
        break

Answer 3

Using open cv 2.4.3, you can do the following:

import cv2
surf = cv2.SURF()
keypoints, descriptors = surf.detectAndCompute(img,None,useProvidedKeypoints = True)

Answer 4

todofixthis I follow your code and I get this

import cv2
img = cv2.imread("im3.jpg")
sd = cv2.FeatureDetector_create("SURF")
surf = cv2.DescriptorExtractor_create("SURF")
keypoints = sd.detect(img) # segmentation faults
l,d = surf.compute(img, keypoints) # returns empty result

where

l = keypoints

d = descriptor