Am making use of sliding/rolling window technique to devide the input image into equal chunks of given size so for that am making use of following function to devide image into specified window size.
[Edited below fun. defination]
def rolling_window(base_cord,test_image, window):
"""Very basic multi dimensional rolling window. window should be the shape of
of the desired subarrays. Window is either a scalar or a tuple of same size
as `arr.shape`.
"""
rest_c_ls = []
windowsize_r = window[0]
windowsize_c = window[1]
chunk_arr = {}
for r in range(0, test_image.shape[0] - windowsize_r, windowsize_r):
for c in range(0, test_image.shape[1] - windowsize_c, windowsize_c):
win = test_image[r:r + windowsize_r, c:c + windowsize_c]
cord = (r+base_cord[0], c+base_cord[1])
rest_c_ls.append(cord[1])
chunk_arr[cord] = win
else:
rest_c = (test_image.shape[1] - windowsize_c)
rest_c_ls.append(rest_c)
win = test_image[r:r + windowsize_r, rest_c:rest_c + windowsize_c]
cord = (r + base_cord[0], rest_c + base_cord[1])
chunk_arr[cord] = win
#print test_image.shape[1] - windowsize_c
else:
for rest_c in rest_c_ls:
rest_r = (test_image.shape[0] - windowsize_r)
win = test_image[rest_r:rest_r + windowsize_r, rest_c:rest_c + windowsize_c]
cord = (rest_r + base_cord[0], rest_c + base_cord[1])
chunk_arr[cord] = win
#print 'else'+str(test_image.shape[0] - windowsize_r)
#test_image[r:r + windowsize_r, c:c + windowsize_c]
return chunk_arr
So, this function returns me the window of specified size lets say
50x50 along with its base cordinates in dictionary format.
But problem is suppose I pass down the image of any odd size like 968x885 then spliting equal size chunks of size 50x50 will left some odd boundary pixels at the end of the image , the resuling image after first round of sliding window looks something like below.
As we can see above , the pixels at right side are not chunked into window coz it's < 50x50 window size.
So what i want is to modify rolling_window function in order to form seperate window chunk for remaining pixels in every possible row/column. So how to achieve this.
Also, I have updated this question as have a function to calculate 3D histogram for given image window , so after updating the above window function I am able to get all the remaining chunks of the windows but it thows me exception while calculating the 3D histogram, here function.
def extract_color_histogram(image, bins=(8, 8, 8)):
# extract a 3D color histogram from the HSV color space using
# the supplied number of `bins` per channel
hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
hist = cv2.calcHist([hsv], [0, 1, 2], None, bins,
[0, 180, 0, 256, 0, 256])
# handle normalizing the histogram if we are using OpenCV 2.4.X
if imutils.is_cv2():
hist = cv2.normalize(hist)
# otherwise, perform "in place" normalization in OpenCV 3 (I
# personally hate the way this is done
else:
cv2.normalize(hist, hist)
# return the flattened histogram as the feature vector
return hist.flatten()
#except Exception as e:
# print e
Now it's throwing exception at this line :
hist = cv2.calcHist([hsv], [0, 1, 2], None, bins,
[0, 180, 0, 256, 0, 256])
OpenCV Error: Assertion failed (j <
nimages) in histPrepareImages, file
/tmp/yaourt-tmp-swap/aur-opencv2/src/opencv-2.4.13/modules/imgproc/src/histogram.cpp,
line 148 Traceback (most recent call
last): File
"/run/media/swap/a673bea3-9088-494e-bad5-5b80d6870b9b/home/swap/openCV/Satellite
Image Processing/svm/svm_predict.py",
line 253, in <module>
round2(rolling_window(c,w, step_size)) File
"/run/media/swap/a673bea3-9088-494e-bad5-5b80d6870b9b/home/swap/openCV/Satellite
Image Processing/svm/svm_predict.py",
line 100, in round2
pixels = extract_color_histogram(win) File
"/run/media/swap/a673bea3-9088-494e-bad5-5b80d6870b9b/home/swap/openCV/Satellite
Image Processing/svm/svm_predict.py",
line 50, in extract_color_histogram
[0, 180, 0, 256, 0, 256]) cv2.error:
/tmp/yaourt-tmp-swap/aur-opencv2/src/opencv-2.4.13/modules/imgproc/src/histogram.cpp:148:
error: (-215) j < nimages in function
histPrepareImages
Any help would be greatly appreciated!