saliency.py
def sumNormalizedFeatures(features, levels=9, startSize=(1983*8, 1088*8)):
	"""
		Normalizes the feature maps in argument features and combines them into one.
		Arguments:
			features	: list of feature maps (images)
			levels		: the levels of the Gaussian pyramid used to
							calculate the feature maps.
			startSize	: the base size of the Gaussian pyramit used to
							calculate the feature maps.
		returns:
			a combined feature map.
	"""
	commonWidth = startSize[0] / 2**(levels/2 - 1)
	commonHeight = startSize[1] / 2**(levels/2 - 1)
	commonSize = commonWidth, commonHeight
	logger.info("Size of conspicuity map: %s", commonSize)
	consp = N(cv2.resize(features[0][1], commonSize))
	for f in features[1:]:
		resized = N(cv2.resize(f[1], commonSize))
		consp = cv2.add(consp, resized)
	return consp

		Normalizes the feature maps in argument features and combines them into one.
		Arguments:
			features	: list of feature maps (images)
			levels		: the levels of the Gaussian pyramid used to
							calculate the feature maps.
			startSize	: the base size of the Gaussian pyramit used to
							calculate the feature maps.
		returns:
			a combined feature map.
	
Normalizes the feature maps in argument features and combines them into one.
Normalizes the feature maps in argument features and combines them into one .
def sumNormalizedFeatures(features, levels=9, startSize=(1983*8, 1088*8)):
	commonWidth = startSize[0] / 2**(levels/2 - 1)
	commonHeight = startSize[1] / 2**(levels/2 - 1)
	commonSize = commonWidth, commonHeight
	logger.info("Size of conspicuity map: %s", commonSize)
	consp = N(cv2.resize(features[0][1], commonSize))
	for f in features[1:]:
		resized = N(cv2.resize(f[1], commonSize))
		consp = cv2.add(consp, resized)
	return consp
def sumNormalizedFeatures ( features , levels = 9 , startSize = ( 1983 * 8 , 1088 * 8 ) ) : commonWidth = startSize [ 0 ] / 2 ** ( levels / 2 - 1 ) commonHeight = startSize [ 1 ] / 2 ** ( levels / 2 - 1 ) commonSize = commonWidth , commonHeight logger . info ( "Size of conspicuity map: %s" , commonSize ) consp = N ( cv2 . resize ( features [ 0 ] [ 1 ] , commonSize ) ) for f in features [ 1 : ] : resized = N ( cv2 . resize ( f [ 1 ] , commonSize ) ) consp = cv2 . add ( consp , resized ) return consp
Normalizes the feature maps in argument features and combines them into one.
Normalizes the feature maps in argument features and combines them into one .
"""
		Normalizes the feature maps in argument features and combines them into one.
		Arguments:
			features	: list of feature maps (images)
			levels		: the levels of the Gaussian pyramid used to
							calculate the feature maps.
			startSize	: the base size of the Gaussian pyramit used to
							calculate the feature maps.
		returns:
			a combined feature map.
	"""
features
levels
startSize
features        
list of feature maps (images)
list of feature maps ( images )
levels          
the levels of the Gaussian pyramid used to
calculate the feature maps.
the levels of the Gaussian pyramid used to calculate the feature maps .
startSize       
the base size of the Gaussian pyramit used to
calculate the feature maps.
the base size of the Gaussian pyramit used to calculate the feature maps .