Add: Added Integral Channel Features implmentation

features/icf.py

@@ -0,0 +1,76 @@
+import cv2 as cv
+import numpy as np
+
+
+def get_LUV_features(image):
+    '''
+    Args:
+        image(numpy.ndarray): Image from which LUV channels are extracted
+
+    Returns:
+        List of L,U,V channels respectively
+    '''
+    luv = cv.cvtColor(image, cv.COLOR_BGR2LUV)
+    return cv.split(luv)
+
+
+def get_gradient_matrix(image):
+    '''
+    Calculates gradient magnitude and angles matrices of given image
+
+    Args:
+        image(numpy.ndarray): Image from which matricies are calculated
+
+    Returns:
+        mag(numpy.ndarray): matrix of gradient magnitudes
+        angles(numpy.ndarray): matrix of gradient angles
+    '''
+    gx = cv.Sobel(image, cv.CV_32F, 1, 0,)
+    gy = cv.Sobel(image, cv.CV_32F, 0, 1,)
+    mag, angles = cv.cartToPolar(gx, gy, angleInDegrees=True)
+    return mag, angles
+
+
+def get_oriented_gradients(angles, mag, bins, bin_size):
+    '''
+    Calculate oriented gradients from angles and magnitude
+
+    Args:
+        angles(numpy.ndarray): Matrix of gradient directions
+                               (angles from <0, 360>)
+        mag(numpy.ndarray): Matrix of gradient magnitudes
+        bins(list): List of angles
+        bins(int): Range of individual angle
+
+    Returns:
+        (numpy.ndarray): Array of idividual oriented gradient channels
+    '''
+    channels = []
+    angles %= 180
+    for b in bins:
+        orient = ((b - bin_size) < angles) & (angles < (b + bin_size))
+        channel = cv.bitwise_and(mag, mag, mask=orient.astype('uint8'))
+        channels.append(channel)
+    return np.asarray(channels)
+
+
+def icf(image, bins, bin_size):
+    '''
+    Calculate integral channel features
+
+    Args:
+        image(numpy.ndarray): Image from which calculate ICF
+        bins(list): List of angles
+        bins(int): Range of individual angle
+
+    Returns:
+        (numpy.ndarray): Integral channel features
+    '''
+    channels = get_LUV_features(image)
+    gray = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
+    gray = cv.GaussianBlur(gray, (3, 3), 0)
+    mag, angles = get_gradient_matrix(gray)
+    mag = cv.convertScaleAbs(mag)
+    channels.append(mag)
+    channels.extend(get_oriented_gradients(angles, mag, bins, bin_size))
+    return map(lambda ch: cv.integral(ch), channels)