ColorDescriptor.py

import numpy as np
import cv2
import imutils

class ColorDescriptor:
    def __init__(self):
        # store the number of bins for the 3D histogram
        self.bins = (16, 24, 5)

    def histogram(self, image, mask):
        # extract a 3D color histogram from the masked region of the
        # image, using the supplied number of bins per channel
        hist = cv2.calcHist([image], [0, 1, 2], mask, self.bins,[0, 180, 0, 256, 0, 256])
        # normalize the histogram if we are using OpenCV 2.4
        if imutils.is_cv2():
            cv2.normalize(hist, hist)
            hist.flatten()
        # otherwise handle for OpenCV 3+
        else:
            hist = cv2.normalize(hist, hist).flatten()
        # return the histogram
        return hist

    def describe(self, image):
        # convert the image to the HSV color space and initialize
		# the features used to quantify the image
        image = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
        features = []
        # grab the dimensions and compute the center of the image
        (h, w) = image.shape[:2]
        (cX, cY) = (int(w * 0.5), int(h * 0.5))
        # divide the image into four rectangles/segments (top-left,
        # top-right, bottom-right, bottom-left)
        segments = [(0, cX, 0, cY), (cX, w, 0, cY), (cX, w, cY, h),
			(0, cX, cY, h)]
        # construct an elliptical mask representing the center of the
        # image
        (axesX, axesY) = (int(w * 0.75) // 2, int(h * 0.75) // 2)
        ellipMask = np.zeros(image.shape[:2], dtype = "uint8")
        cv2.ellipse(ellipMask, (cX, cY), (axesX, axesY), 0, 0, 360, 255, -1)
        # loop over the segments
        """for (startX, endX, startY, endY) in segments:
            # construct a mask for each corner of the image, subtracting
            # the elliptical center from it
            cornerMask = np.zeros(image.shape[:2], dtype = "uint8")
            cv2.rectangle(cornerMask, (startX, startY), (endX, endY), 255, -1)
            cornerMask = cv2.subtract(cornerMask, ellipMask)
            # extract a color histogram from the image, then update the
            # feature vector
            hist = self.histogram(image, cornerMask)
            features.extend(hist)"""
        # extract a color histogram from the elliptical region and
        # update the feature vector
        hist = self.histogram(image, ellipMask)
        features.extend(hist)
        # return the feature vector
        return features