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440 lines
17 KiB
440 lines
17 KiB
2 years ago
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"""
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Programmer : EOF
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Date : 2016.01.16
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E-mail : jasonleaster@163.com
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File : haarFeature.py
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Description:
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Types of Haar-like rectangle features
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--- ---
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|-------|
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| - |
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-------
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I
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--- ---
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--- ---
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II
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-- -- --
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|- | +| -|
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-- -- --
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III
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--- ---
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|___-___|
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|___+___|
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|___-___|
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IV
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--- ---
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|___|___|
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|___|___|
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V
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For each feature pattern, the start point(x, y) is at
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the most left-up pixel in that window. The size of that
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window is @width * @height
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"""
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import numpy
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from config import HAAR_FEATURE_TYPE_I
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from config import HAAR_FEATURE_TYPE_II
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from config import HAAR_FEATURE_TYPE_III
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from config import HAAR_FEATURE_TYPE_IV
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from config import HAAR_FEATURE_TYPE_V
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from image import Image
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class Feature:
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def __init__(self, img_Width, img_Height):
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self.featureName = "Haar Feature"
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self.img_Width = img_Width
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self.img_Height = img_Height
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self.tot_pixels = img_Width * img_Height
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self.featureTypes = (HAAR_FEATURE_TYPE_I,
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HAAR_FEATURE_TYPE_II,
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HAAR_FEATURE_TYPE_III,
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HAAR_FEATURE_TYPE_IV,
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HAAR_FEATURE_TYPE_V)
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self.features = self._evalFeatures_total()
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self.featuresNum = len(self.features)
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#self.featureMat = numpy.zeros((self.tot_pixels, self.featuresNum),
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# dtype=numpy.float16)
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# just for running faster and save RAM. allocate once and use many times.
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self.vector = numpy.zeros(self.featuresNum, dtype=numpy.float32)
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self.idxVector_tmp_0 = numpy.zeros(self.tot_pixels, dtype = numpy.int8)
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self.idxVector_tmp_1 = numpy.zeros(self.tot_pixels, dtype = numpy.int8)
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self.idxVector_tmp_2 = numpy.zeros(self.tot_pixels, dtype = numpy.int8)
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self.idxVector_tmp_3 = numpy.zeros(self.tot_pixels, dtype = numpy.int8)
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def vecRectSum(self, idxVector, x, y, width, height):
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idxVector *= 0 # reset this vector
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if x == 0 and y == 0:
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idxVector[width * height + 2] = +1
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elif x == 0:
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idx1 = self.img_Height * ( width - 1) + height + y - 1
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idx2 = self.img_Height * ( width - 1) + y - 1
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idxVector[idx1] = +1
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idxVector[idx2] = -1
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elif y == 0:
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idx1 = self.img_Height * (x + width - 1) + height - 1
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idx2 = self.img_Height * (x - 1) + height - 1
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idxVector[idx1] = +1
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idxVector[idx2] = -1
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else:
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idx1 = self.img_Height * (x + width - 1) + height + y - 1
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idx2 = self.img_Height * (x + width - 1) + y - 1
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idx3 = self.img_Height * (x - 1) + height + y - 1
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idx4 = self.img_Height * (x - 1) + y - 1
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assert idx1 < self.tot_pixels and idx2 < self.tot_pixels
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assert idx3 < self.tot_pixels and idx4 < self.tot_pixels
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idxVector[idx1] = + 1
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idxVector[idx2] = - 1
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idxVector[idx3] = - 1
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idxVector[idx4] = + 1
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return idxVector
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def VecFeatureTypeI(self, vecImg, x, y, width, height):
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vec1 = self.vecRectSum(self.idxVector_tmp_0, x, y , width, height)
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vec2 = self.vecRectSum(self.idxVector_tmp_1, x, y + height, width, height)
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featureSize = width * height * 2
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return (vec1.dot(vecImg) - vec2.dot(vecImg))/featureSize
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def VecFeatureTypeII(self, vecImg, x, y, width, height):
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vec1 = self.vecRectSum(self.idxVector_tmp_0, x + width, y, width, height)
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vec2 = self.vecRectSum(self.idxVector_tmp_1, x , y, width, height)
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featureSize = width * height * 2
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return (vec1.dot(vecImg) - vec2.dot(vecImg))/featureSize
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def VecFeatureTypeIII(self,vecImg, x, y, width, height):
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vec1 = self.vecRectSum(self.idxVector_tmp_0, x + width, y, width, height)
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vec2 = self.vecRectSum(self.idxVector_tmp_1, x , y, width, height)
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vec3 = self.vecRectSum(self.idxVector_tmp_2, x + 2*width, y, width, height)
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featureSize = width * height * 3
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return (vec1.dot(vecImg) - vec2.dot(vecImg)
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- vec3.dot(vecImg))/featureSize
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def VecFeatureTypeIV(self,vecImg, x, y, width, height):
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vec1 = self.vecRectSum(self.idxVector_tmp_0, x, y + height, width, height)
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vec2 = self.vecRectSum(self.idxVector_tmp_1, x, y , width, height)
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vec3 = self.vecRectSum(self.idxVector_tmp_2, x, y + 2*height, width, height)
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featureSize = width * height * 3
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return (vec1.dot(vecImg) - vec2.dot(vecImg)
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- vec3.dot(vecImg))/featureSize
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def VecFeatureTypeV(self, vecImg, x, y, width, height):
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vec1 = self.vecRectSum(self.idxVector_tmp_0, x + width, y, width, height)
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vec2 = self.vecRectSum(self.idxVector_tmp_1, x , y, width, height)
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vec3 = self.vecRectSum(self.idxVector_tmp_2, x , y + height, width, height)
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vec4 = self.vecRectSum(self.idxVector_tmp_3, x + width, y + height, width, height)
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featureSize = width * height * 4
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return (vec1.dot(vecImg) - vec2.dot(vecImg) +
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vec3.dot(vecImg) - vec4.dot(vecImg))/featureSize
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def _evalFeatures_total(self):
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win_Height = self.img_Height
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win_Width = self.img_Width
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height_Limit = {HAAR_FEATURE_TYPE_I : win_Height//2 - 1,
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HAAR_FEATURE_TYPE_II : win_Height - 1,
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HAAR_FEATURE_TYPE_III : win_Height - 1,
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HAAR_FEATURE_TYPE_IV : win_Height//3 - 1,
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HAAR_FEATURE_TYPE_V : win_Height//2 - 1}
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width_Limit = {HAAR_FEATURE_TYPE_I : win_Width - 1,
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HAAR_FEATURE_TYPE_II : win_Width//2 - 1,
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HAAR_FEATURE_TYPE_III : win_Width//3 - 1,
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HAAR_FEATURE_TYPE_IV : win_Width - 1,
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HAAR_FEATURE_TYPE_V : win_Width//2 - 1}
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features = []
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for types in self.featureTypes:
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for w in range(1, width_Limit[types]):
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for h in range(1, height_Limit[types]):
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if w == 1 and h == 1:
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continue
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if types == HAAR_FEATURE_TYPE_I:
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x_limit = win_Width - w
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y_limit = win_Height - 2*h
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for x in range(1, x_limit):
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for y in range(1, y_limit):
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features.append( (types, x, y, w, h))
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elif types == HAAR_FEATURE_TYPE_II:
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x_limit = win_Width - 2*w
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y_limit = win_Height - h
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for x in range(1, x_limit):
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for y in range(1, y_limit):
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features.append( (types, x, y, w, h))
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elif types == HAAR_FEATURE_TYPE_III:
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x_limit = win_Width - 3*w
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y_limit = win_Height - h
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for x in range(1, x_limit):
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for y in range(1, y_limit):
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features.append( (types, x, y, w, h))
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elif types == HAAR_FEATURE_TYPE_IV:
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x_limit = win_Width - w
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y_limit = win_Height - 3*h
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for x in range(1, x_limit):
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for y in range(1, y_limit):
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features.append( (types, x, y, w, h))
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elif types == HAAR_FEATURE_TYPE_V:
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x_limit = win_Width - 2*w
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y_limit = win_Height - 2*h
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for x in range(1, x_limit):
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for y in range(1, y_limit):
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features.append( (types, x, y, w, h))
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return features
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def calFeatureForImg(self, img):
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assert isinstance(img, Image)
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assert img.img.shape[0] == self.img_Height
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assert img.img.shape[1] == self.img_Width
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for i in range(self.featuresNum):
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type, x, y, w, h = self.features[i]
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if type == HAAR_FEATURE_TYPE_I:
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self.vector[i] = self.VecFeatureTypeI(img.vecImg, x, y, w, h)
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elif type == HAAR_FEATURE_TYPE_II:
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self.vector[i] = self.VecFeatureTypeII(img.vecImg, x, y, w, h)
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elif type == HAAR_FEATURE_TYPE_III:
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self.vector[i] = self.VecFeatureTypeIII(img.vecImg, x, y, w, h)
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elif type == HAAR_FEATURE_TYPE_IV:
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self.vector[i] = self.VecFeatureTypeIV(img.vecImg, x, y, w, h)
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elif type == HAAR_FEATURE_TYPE_V:
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self.vector[i] = self.VecFeatureTypeV(img.vecImg, x, y, w, h)
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else:
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raise Exception("unknown feature type")
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return self.vector
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def makeFeaturePic(self, feature):
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from matplotlib import pyplot
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from config import BLACK
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from config import WHITE
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import pylab
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(types, x, y, width, height) = feature
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assert x >= 0 and x < self.img_Width
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assert y >= 0 and y < self.img_Height
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assert width > 0 and height > 0
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image = numpy.array([[125. for i in range(self.img_Width)]
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for j in range(self.img_Height)])
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if types == HAAR_FEATURE_TYPE_I:
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for i in range(y, y + height * 2):
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for j in range(x, x + width):
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if i < y + height:
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image[i][j] = BLACK
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else:
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image[i][j] = WHITE
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elif types == HAAR_FEATURE_TYPE_II:
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for i in range(y, y + height):
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for j in range(x, x + width * 2):
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if j < x + width:
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image[i][j] = WHITE
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else:
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image[i][j] = BLACK
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elif types == HAAR_FEATURE_TYPE_III:
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for i in range(y, y + height):
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for j in range(x, x + width * 3):
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if j >= (x + width) and j < (x + width * 2):
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image[i][j] = BLACK
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else:
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image[i][j] = WHITE
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elif types == HAAR_FEATURE_TYPE_IV:
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for i in range(y, y + height*3):
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for j in range(x, x + width):
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if i >= (y + height) and i < (y + height * 2):
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image[i][j] = BLACK
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else:
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image[i][j] = WHITE
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elif types == HAAR_FEATURE_TYPE_V:
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for i in range(y, y + height * 2):
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for j in range(x, x + width * 2):
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if (j < x + width and i < y + height) or\
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(j >= x + width and i >= y + height):
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image[i][j] = BLACK
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else:
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image[i][j] = WHITE
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pyplot.matshow(image, cmap = "gray")
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pylab.show()
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"""
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old version. Don't use this.
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def _evalFeatures(self):
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win_Height = self.img_Height
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win_Width = self.img_Width
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height_Limit = {HAAR_FEATURE_TYPE_I : win_Height/2 - 1,
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HAAR_FEATURE_TYPE_II : win_Height - 1,
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HAAR_FEATURE_TYPE_III : win_Height - 1,
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HAAR_FEATURE_TYPE_IV : win_Height/2 - 1}
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width_Limit = {HAAR_FEATURE_TYPE_I : win_Width - 1,
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HAAR_FEATURE_TYPE_II : win_Width/2 - 1,
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HAAR_FEATURE_TYPE_III : win_Width/3 - 1,
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HAAR_FEATURE_TYPE_IV : win_Width/2 - 1}
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features = []
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for types in self.featureTypes:
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for w in range(1, width_Limit[types]):
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for h in range(1, height_Limit[types]):
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y_start = None
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if types == HAAR_FEATURE_TYPE_I:
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x_limit = win_Width - w
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y_limit = win_Height - 2*h
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for x in range(1, x_limit):
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for y in range(1, y_limit, 2):
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features.append( (types, x, y, w, h))
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elif types == HAAR_FEATURE_TYPE_II:
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x_limit = win_Width - 2*w
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y_limit = win_Height - h
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for x in range(1, x_limit):
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|
if h % 2 == 1:
|
||
|
|
if x % 2 == 1:
|
||
|
|
y_start = 1
|
||
|
|
else:
|
||
|
|
y_start = 2
|
||
|
|
else:
|
||
|
|
y_start = 1
|
||
|
|
|
||
|
|
for y in range(y_start, y_limit, 2):
|
||
|
|
features.append( (types, x, y, w, h))
|
||
|
|
|
||
|
|
elif types == HAAR_FEATURE_TYPE_III:
|
||
|
|
x_limit = win_Width - 3*w
|
||
|
|
y_limit = win_Height - h
|
||
|
|
for x in range(1, x_limit):
|
||
|
|
if w == 1:
|
||
|
|
if h % 2 == 1:
|
||
|
|
if (h + 1)/2 % 2 == 1:
|
||
|
|
if x % 2 == 1:
|
||
|
|
y_start = 1
|
||
|
|
else:
|
||
|
|
y_start = 2
|
||
|
|
else:
|
||
|
|
if x % 2 == 1:
|
||
|
|
y_start = 2
|
||
|
|
else:
|
||
|
|
y_start = 1
|
||
|
|
else:
|
||
|
|
if (h/2) % 2 == 1:
|
||
|
|
y_start = 2
|
||
|
|
else:
|
||
|
|
y_start = 1
|
||
|
|
elif w == 2:
|
||
|
|
if h % 2 == 1:
|
||
|
|
if x % 2 == 1:
|
||
|
|
y_start = 2
|
||
|
|
else:
|
||
|
|
y_start = 1
|
||
|
|
else:
|
||
|
|
y_start = 2
|
||
|
|
|
||
|
|
elif w == 3:
|
||
|
|
if h % 2 == 1:
|
||
|
|
if (h+1)/2 % 2 == 1:
|
||
|
|
if x % 2 == 1:
|
||
|
|
y_start = 2
|
||
|
|
else:
|
||
|
|
y_start = 1
|
||
|
|
else:
|
||
|
|
if x % 2 == 1:
|
||
|
|
y_start = 1
|
||
|
|
else:
|
||
|
|
y_start = 2
|
||
|
|
else:
|
||
|
|
if (h/2) % 2 == 1:
|
||
|
|
y_start = 1
|
||
|
|
else:
|
||
|
|
y_start = 2
|
||
|
|
#elif w == 4:
|
||
|
|
else:
|
||
|
|
if h % 2 == 1:
|
||
|
|
if x % 2 == 1:
|
||
|
|
y_start = 1
|
||
|
|
else:
|
||
|
|
y_start = 2
|
||
|
|
else:
|
||
|
|
y_start = 1
|
||
|
|
|
||
|
|
for y in range(y_start, y_limit, 2):
|
||
|
|
features.append( (types, x, y, w, h))
|
||
|
|
|
||
|
|
elif types == HAAR_FEATURE_TYPE_IV:
|
||
|
|
x_limit = win_Width - 2*w
|
||
|
|
y_limit = win_Height - 2*h
|
||
|
|
for x in range(1, x_limit):
|
||
|
|
for y in range(1, y_limit, 2):
|
||
|
|
features.append( (types, x, y, w, h))
|
||
|
|
return features
|
||
|
|
"""
|
||
|
|
|