def inspect_best_features(best_features, win_name='HaarFeatures'):
features = load_feature_meta()
cv2.namedWindow(win_name, cv2.WINDOW_NORMAL)
# base_img = np.empty(shape=(24, 24), dtype=np.uint8)
# base_img.fill(128)
base_img = cv2.imread('face0008.jpg', 0)
for feat in best_features:
min_feature_num, min_error, error_rate, threshold, parity, alpha = feat
stop_inspection = False
img = np.copy(base_img)
f = features[min_feature_num]
print
print '{:s}'.format(f)
print 'W. Error = {:0.6f}'.format(min_error)
print 'Error = {:0.6f}'.format(error_rate)
print 'Threshold = {:0.6f}'.format(threshold)
print 'Parity = {:0.6f}'.format(parity)
print 'Alpha = {:0.6f}'.format(alpha)
height, width = f.type
x, y = f.loc
l, w = f.shape
img[x : x + l, y : y + w] = 255
# plot the feature
if height == 2 and width == 1:
img[x + l // 2 : x + l, y : y + w] = 0
# if feature is type (1, 2),
# feature value = sum(right rectangle) - sum(left rectangle)
elif height == 1 and width == 2:
img[x : x + l, y + w // 2 : y + w] = 0
# if feature is type (3, 1),
# feature value = sum(middle rectangle) - sum(top rectangle) - sum(bottom rectangle)
elif height == 3 and width == 1:
img[x + l // 3 : x + 2 * l // 3, y : y + w] = 0
# if feature is type (1, 3),
# feature value = sum of (middle rectangle) - sum (left rectangle) - sum(right rectangle)
elif height == 1 and width == 3:
img[x : x + l, y + w // 3 : y + 2 * w // 3] = 0
# if feature is type (2, 2),
# feature value = sum of (top right rectangle) + sum (bottom left rectangle)
# - sum (top left rectangle) + sum(bottom right rectangle)
elif height == 2 and width == 2:
img[x : x + l // 2, y + w // 2 : y + w] = 0
img[x + l // 2 : x + l, y : y + w // 2] = 0
while True:
key = cv2.waitKey(10)
if key == 27:
stop_inspection = True
break
if key == ord('n'):
break
cv2.imshow(win_name, img)
if stop_inspection:
break
cv2.destroyAllWindows()
def inspect_features(ls_features=range(162336), win_name='HaarFeatures'):
features = load_feature_meta()
cv2.namedWindow(win_name, cv2.WINDOW_NORMAL)
# base_img = np.empty(shape=(24, 24), dtype=np.uint8)
# base_img.fill(128)
base_img = cv2.imread('face0002.jpg', 0)
for feat in ls_features:
stop_inspection = False
img = np.copy(base_img)
f = features[feat]
print '{:s}'.format(f)
height, width = f.type
x, y = f.loc
l, w = f.shape
img[x : x + l, y : y + w] = 255
# plot the feature
if height == 2 and width == 1:
img[x + l // 2 : x + l, y : y + w] = 0
# if feature is type (1, 2),
# feature value = sum(right rectangle) - sum(left rectangle)
elif height == 1 and width == 2:
img[x : x + l, y + w // 2 : y + w] = 0
# if feature is type (3, 1),
# feature value = sum(middle rectangle) - sum(top rectangle) - sum(bottom rectangle)
elif height == 3 and width == 1:
img[x + l // 3 : x + 2 * l // 3, y : y + w] = 0
# if feature is type (1, 3),
# feature value = sum of (middle rectangle) - sum (left rectangle) - sum(right rectangle)
elif height == 1 and width == 3:
img[x : x + l, y + w // 3 : y + 2 * w // 3] = 0
# if feature is type (2, 2),
# feature value = sum of (top right rectangle) + sum (bottom left rectangle)
# - sum (top left rectangle) + sum(bottom right rectangle)
elif height == 2 and width == 2:
img[x : x + l // 2, y + w // 2 : y + w] = 0
img[x + l // 2 : x + l, y : y + w // 2] = 0
while True:
key = cv2.waitKey(10)
if key == 27:
stop_inspection = True
break
if key == ord('n'):
break
cv2.imshow(win_name, img)
if stop_inspection:
break
cv2.destroyAllWindows()
