The function works as follows:

# Import the cv2 library
import cv2
# Read the image you want connected components of
src = cv2.imread('/directorypath/image.bmp')
# Threshold it so it becomes binary
ret, thresh = cv2.threshold(src,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU)
# You need to choose 4 or 8 for connectivity type
connectivity = 4  
# Perform the operation
output = cv2.connectedComponentsWithStats(thresh, connectivity, cv2.CV_32S)
# Get the results
# The first cell is the number of labels
num_labels = output[0]
# The second cell is the label matrix
labels = output[1]
# The third cell is the stat matrix
stats = output[2]
# The fourth cell is the centroid matrix
centroids = output[3]

Labels is a matrix the size of the input image where each element has a value equal to its label.

Stats is a matrix of the stats that the function calculates. It has a length equal to the number of labels and a width equal to the number of stats. It can be used with the OpenCV documentation for it:

Statistics output for each label, including the background label, see below for available statistics. Statistics are accessed via stats[label, COLUMN] where available columns are defined below.

• cv2.CC_STAT_LEFT The leftmost (x) coordinate which is the inclusive start of the bounding box in the horizontal direction.
• cv2.CC_STAT_TOP The topmost (y) coordinate which is the inclusive start of the bounding box in the vertical direction.
• cv2.CC_STAT_WIDTH The horizontal size of the bounding box
• cv2.CC_STAT_HEIGHT The vertical size of the bounding box
• cv2.CC_STAT_AREA The total area (in pixels) of the connected component

Centroids is a matrix with the x and y locations of each centroid. The row in this matrix corresponds to the label number.

'connectedComponentsWithStats' method is only usable on opencv3.x.

Connected component actually works on background-foreground property, where the black colour is considered as background and white as foreground. This is actually a standard and if you ask me also seems natural. Its the duty of the user to do appropriate inversion if they want to do connected component labelling of black(background) region.

The function works as follows:

# Import the cv2 library import cv2 # Read the image you want connected components of src = cv2.imread('/directorypath/image.bmp') # Threshold it so it becomes binary ret, thresh = cv2.threshold(src,0,255,cv2.THRESH_BINARY+cv2.THRESH_OTSU) # You need to choose 4 or 8 for connectivity type connectivity = 4   # Perform the operation output = cv2.connectedComponentsWithStats(thresh, connectivity, cv2.CV_32S) # Get the results # The first cell is the number of labels num_labels = output[0] # The second cell is the label matrix labels = output[1] # The third cell is the stat matrix stats = output[2] # The fourth cell is the centroid matrix centroids = output[3] 

Labels is a matrix the size of the input image where each element has a value equal to its label.

Stats is a matrix of the stats that the function calculates. It has a length equal to the number of labels and a width equal to the number of stats. It can be used with the OpenCV documentation for it:

Statistics output for each label, including the background label, see below for available statistics. Statistics are accessed via stats[label, COLUMN] where available columns are defined below.

• cv2.CC_STAT_LEFT The leftmost (x) coordinate which is the inclusive start of the bounding box in the horizontal direction.
• cv2.CC_STAT_TOP The topmost (y) coordinate which is the inclusive start of the bounding box in the vertical direction.
• cv2.CC_STAT_WIDTH The horizontal size of the bounding box
• cv2.CC_STAT_HEIGHT The vertical size of the bounding box
• cv2.CC_STAT_AREA The total area (in pixels) of the connected component

Centroids is a matrix with the x and y locations of each centroid. The row in this matrix corresponds to the label number.