python opencv SIFT doesn't work for 8 bit images (JPEG)

问题:

I used SIFT for all my other 24 bit JPEG images without any problems, however, the 8 bit one always give me this following error.

image is empty or has incorrect depth (!=CV_8U) in function cv::SIFT::operator ()

Does anyone know how to deal with it?

Here is my code:

import cv2  import numpy as np  import os  import glob import scipy.cluster os.chdir('\mydirectory') images = []  for infile in glob.glob('./*.jpg'):   pic = cv2.imread(infile,0)   images.append(pic)  my_set = images descriptors = np.array([]) feaL=np.array([])  for pic in my_set:   kp, des = cv2.SIFT().detectAndCompute(pic, None)   feaL=np.append(feaL,des.shape[0])   descriptors = np.append(descriptors, des) 

Then the error "image is empty or has incorrect depth (!=CV_8U) in function cv::SIFT::operator ()" pops up.

回答1:

EDIT: After typing this I just saw the grayscale flag on imread. Try printing the images as they are read in, it sounds like imread may be silently failing and leaving you with empty Mats.

cv2.SIFT.detectAndCompute never takes anything other than 8-bit grayscale, so I'm not sure that you actually did use SIFT on a 24 bit image without problems.

cv2.SIFT.detectAndCompute

Python: cv2.SIFT.detectAndCompute(image, mask[, descriptors[, useProvidedKeypoints]]) → keypoints, descriptors 

So to change to 8 bit grayscale immediately prior to detection and extraction:

for pic in my_set:     pic = cv2.cvtColor(pic, cv2.COLOR_BGR2GRAY)     kp, des = cv2.SIFT().detectAndCompute(pic, None) 

Of course that is a dumb place to put it, but it's up to you to figure out if you need to keep the BGR originals or not, etc.

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