plot_colors.py

# Courtesy of https://www.pyimagesearch.com/2014/05/26/opencv-python-k-means-color-clustering/
def plot_colors(hist, centroids):
    # initialize the bar chart representing the relative frequency
    # of each of the colors
    bar = np.zeros((50, 300, 3), dtype="uint8")
    startX = 0

    # Sort the centroids to form a gradient color look
    centroids = sorted(centroids, key=lambda x: sum(x))

    # loop over the percentage of each cluster and the color of
    # each cluster
    for (percent, color) in zip(hist, centroids[offset:]):
        # plot the relative percentage of each cluster
        # endX = startX + (percent * 300)

        # Instead of plotting the relative percentage,
        # we will make a n=clusters number of color rectangles
        # we will also seperate them by a margin
        new_length = 300 - margin * (clusters - 1)
        endX = startX + new_length/clusters
        cv2.rectangle(bar, (int(startX), 0), (int(endX), 50),
                      color.astype("uint8").tolist(), -1)
        cv2.rectangle(bar, (int(endX), 0), (int(endX + margin), 50),
                      (255, 255, 255), -1)
        startX = endX + margin

    # return the bar chart
    return bar