推土机距离的Python代码

Question

我正在寻找Python中的地球移动器的距离（或快速EMD）实现。关于在哪里找到它的任何线索，我在网上已经看够了。我想在我正在做的图像检索项目中使用它。谢谢。

编辑：我发现了使用纸浆库的一个非常好的解决方案。该页面还包含设置所需的说明。

Answer 1

OpenCv for
Python中有一个出色的实现。该函数的名称为CalcEMD2，用于比较两个图像直方图的简单代码如下所示：

#Import OpenCv library
from cv2 import *

### HISTOGRAM FUNCTION #########################################################
def calcHistogram(src):
    # Convert to HSV
    hsv = cv.CreateImage(cv.GetSize(src), 8, 3)
    cv.CvtColor(src, hsv, cv.CV_BGR2HSV)

    # Extract the H and S planes
    size = cv.GetSize(src)
    h_plane = cv.CreateMat(size[1], size[0], cv.CV_8UC1)
    s_plane = cv.CreateMat(size[1], size[0], cv.CV_8UC1)
    cv.Split(hsv, h_plane, s_plane, None, None)
    planes = [h_plane, s_plane]

    #Define numer of bins
    h_bins = 30
    s_bins = 32

    #Define histogram size
    hist_size = [h_bins, s_bins]

    # hue varies from 0 (~0 deg red) to 180 (~360 deg red again */
    h_ranges = [0, 180]

    # saturation varies from 0 (black-gray-white) to 255 (pure spectrum color)
    s_ranges = [0, 255]

    ranges = [h_ranges, s_ranges]

    #Create histogram
    hist = cv.CreateHist([h_bins, s_bins], cv.CV_HIST_ARRAY, ranges, 1)

    #Calc histogram
    cv.CalcHist([cv.GetImage(i) for i in planes], hist)

    cv.NormalizeHist(hist, 1.0)

    #Return histogram
    return hist

### EARTH MOVERS ############################################################
def calcEM(hist1,hist2,h_bins,s_bins):

    #Define number of rows
    numRows = h_bins*s_bins

    sig1 = cv.CreateMat(numRows, 3, cv.CV_32FC1)
    sig2 = cv.CreateMat(numRows, 3, cv.CV_32FC1)

    for h in range(h_bins):
        for s in range(s_bins): 
            bin_val = cv.QueryHistValue_2D(hist1, h, s)
            cv.Set2D(sig1, h*s_bins+s, 0, cv.Scalar(bin_val))
            cv.Set2D(sig1, h*s_bins+s, 1, cv.Scalar(h))
            cv.Set2D(sig1, h*s_bins+s, 2, cv.Scalar(s))

            bin_val = cv.QueryHistValue_2D(hist2, h, s)
            cv.Set2D(sig2, h*s_bins+s, 0, cv.Scalar(bin_val))
            cv.Set2D(sig2, h*s_bins+s, 1, cv.Scalar(h))
            cv.Set2D(sig2, h*s_bins+s, 2, cv.Scalar(s))

    #This is the important line were the OpenCV EM algorithm is called
    return cv.CalcEMD2(sig1,sig2,cv.CV_DIST_L2)

### MAIN ########################################################################
if __name__=="__main__":
    #Load image 1
    src1 = cv.LoadImage("image1.jpg")

    #Load image 1
    src2 = cv.LoadImage("image2.jpg")

    # Get histograms
    histSrc1= calcHistogram(src1)
    histSrc2= calcHistogram(src2)

    # Compare histograms using earth mover's
    histComp = calcEM(histSrc1,histSrc2,30,32)

    #Print solution
    print(histComp)

我使用Python 2.7和Python（x，y）测试了与之前的代码非常相似的代码。如果您想了解有关Earth
Mover的更多信息，并希望了解使用OpenCV和C ++的实现，则可以阅读Gary Bradski和Adrain
Kaebler的“学习OpenCV”一书的“第7章：直方图匹配”。