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140 lines
3.5 KiB
140 lines
3.5 KiB
"""
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Programmer : EOF
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File : image.py
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Date : 2015.12.29
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E-mail : jasonleaster@163.com
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License : MIT License
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Description :
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This script file will initialize the image set
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and read all images in the directory which is given by
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user.
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"""
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import numpy
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import os
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import pylab
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from matplotlib import pyplot
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from matplotlib import image
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class Image:
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def __init__(self, fileName=None, label=None, Mat=None):
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if fileName is not None:
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self.imgName = fileName
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self.img = image.imread(fileName)
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if len(self.img.shape) == 3:
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self.img = self.img[:, :, 1]
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else:
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assert Mat is not None
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self.img = Mat
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self.label = label
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# self.stdImg = Image._normalization(self.img)
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# self.iimg = Image._integrateImg(self.stdImg)
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# self.vecImg = self.iimg.transpose().flatten()
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self.vecImg = Image._integrateImg(Image._normalization(self.img)).transpose().flatten()
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@staticmethod
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def _integrateImg(image):
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assert image.__class__ == numpy.ndarray
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row, col = image.shape
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# @iImg is integrated image of normalized image @self.stdImg
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iImg = numpy.zeros((row, col))
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"""
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for i in xrange(0, row):
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for j in xrange(0, col):
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if j == 0:
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iImg[i][j] = image[i][j]
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else:
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iImg[i][j] = iImg[i][j - 1] + image[i][j]
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for j in xrange(0, col):
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for i in xrange(1, row):
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iImg[i][j] += iImg[i - 1][j]
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"""
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iImg = image.cumsum(axis=1).cumsum(axis=0)
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return iImg
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@staticmethod
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def _normalization(image):
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assert image.__class__ == numpy.ndarray
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row, col = image.shape
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# stdImag standardized image
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stdImg = numpy.zeros((row, col))
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"""
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What image.sum() do is the same as the following code
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but more faster than this.
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for i in xrange(self.Row):
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for j in xrange(self.Col):
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sigma += image[i][j]
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"""
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# sigma = image.sum()
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meanVal = image.mean()
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stdValue = image.std()
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if stdValue == 0:
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stdValue = 1
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stdImg = (image - meanVal) / stdValue
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return stdImg
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@staticmethod
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def show(image=None):
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if image == None:
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return
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pyplot.matshow(image)
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pylab.show()
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class ImageSet:
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def __init__(self, imgDir=None, label=None, sampleNum=None):
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assert isinstance(imgDir, str)
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self.fileList = os.listdir(imgDir)
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self.fileList.sort()
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if sampleNum is None:
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self.sampleNum = len(self.fileList)
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else:
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self.sampleNum = sampleNum
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self.curFileIdx = self.sampleNum
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self.label = label
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self.images = [None for _ in range(self.sampleNum)]
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processed = -10.
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for i in range(self.sampleNum):
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self.images[i] = Image(os.path.join(imgDir, self.fileList[i]), label)
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if i % (self.sampleNum / 10) == 0:
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processed += 10.
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print("Loading ", processed, "%")
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print("Loading 100 %\n")
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def readNextImg(self):
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img = Image(os.path.join(self.imgDir, self.fileList[self.curFileIdx]), self.label)
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self.curFileIdx += 1
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return img
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