python opencv TypeError: Layout of the output array incompatible with cv::Mat

Question

I'm using the selective search here: http://koen.me/research/selectivesearch/ This gives possible regions of interest where an object might be. I want to do some processing and retain only some of the regions, and then remove duplicate bounding boxes to have a final neat collection of bounding boxes. To discard unwanted/duplicated bounding boxes regions, I'm using the grouprectangles function of opencv for pruning.

Once I get the interesting regions from Matlab from the "selective search algorithm" in the link above, I save the results in a .mat file and then retrieve them in a python program, like this:

 import scipy.io as sio
 inboxes = sio.loadmat('C:\\PATH_TO_MATFILE.mat')
 candidates = np.array(inboxes['boxes'])
 # candidates is 4 x N array with each row describing a bounding box like this: 
 # [rowBegin colBegin rowEnd colEnd]
 # Now I will process the candidates and retain only those regions that are interesting
 found = [] # This is the list in which I will retain what's interesting
 for win in candidates: 
     # doing some processing here, and if some condition is met, then retain it:
     found.append(win)

# Now I want to store only the interesting regions, stored in 'found', 
# and prune unnecessary bounding boxes

boxes = cv2.groupRectangles(found, 1, 2) # But I get an error here

The error is:

    boxes = cv2.groupRectangles(found, 1, 2)
TypeError: Layout of the output array rectList is incompatible with cv::Mat (step[ndims-1] != elemsize or step[1] != elemsize*nchannels)

What's wrong? I did something very similar in another piece of code which gave no errors. This was the error-free code:

inboxes = sio.loadmat('C:\\PATH_TO_MY_FILE\\boxes.mat')
boxes = np.array(inboxes['boxes'])
pruned_boxes = cv2.groupRectangles(boxes.tolist(), 100, 300)

The only difference I can see is that boxes was a numpy array which I then converted to a list. But in my problematic code, found is already a list.

Answer 1

My own solution was simply to ask a copy of original array...(god & gary bradski knows why...)

im = dbimg[i]
bb = boxes[i]  
m = im.transpose((1, 2, 0)).astype(np.uint8).copy() 
pt1 = (bb[0],bb[1])
pt2 = (bb[0]+bb[2],bb[1]+bb[3])  
cv2.rectangle(m,pt1,pt2,(0,255,0),2)  

Answer 2

Another reason may be that the array is not contiguous. Making it contiguous would also solve the issue

image = np.ascontiguousarray(image, dtype=np.uint8)

Answer 3

The solution was to convert found first to a numpy array, and then to recovert it into a list:

found = np.array(found)
boxes = cv2.groupRectangles(found.tolist(), 1, 2)