查找每种颜色中每列的平均BGR值

Question

我们正在编写一个看起来像96孔板的代码。我们有每口井的中心坐标。然后，我们创建了一个for循环，它允许我们获得每个井的BGR值。但是，我们需要以某种方式组织每一列，并对这些值进行平均。我相信我们从第一个循环中得到了一个错误。在这个例子中，函数似乎只经历了第一个循环，而不是第二个循环。当我运行它时，我得到了3个值(假设是bgr值)，然后继续推算平均值。它似乎也重复了一些平均值。任何建议，我可以改变，或错误的第一眼。我将提供下面的图像和图例。

指向图像的链接为：http://imgur.com/Eb87ZxW (图像已缩放，因此坐标可能不适用于上传的图像) http://imgur.com/P4tPPXX

import cv2, numpy as np, sys

#filename will be taken from the command line and process as the image variable
#filename= sys.argv([1])
img = cv2.imread('greenandblueplate.jpg')

#centroids
wells = [img[110,97], img[184,97], img[254,97], img[324,97], img[396,96], img[466,97], #columnH 12-7
         img[537,96], img[607,97], img[680,96], img[750,97], img[820,96], img[891,97], #columnH 6-1
         img[110,165],img[184,165],img[254,165],img[324,165],img[396,165],img[466,165], #columnG 12-7
         img[537,165],img[607,165],img[680,165],img[750,166],img[820,165],img[891,165], #columnG 6-1
         img[110,235],img[184,235],img[254,235],img[324,235],img[396,235],img[466,235], #columnF 12-7
         img[537,235],img[607,235],img[680,235],img[750,235],img[820,235],img[891,235], #columnF 6-1
         img[110,305],img[184,305],img[254,305],img[324,305],img[396,305],img[466,305], #columnE 12-7
         img[537,305],img[607,305],img[680,305],img[750,305],img[820,305],img[891,305], #columnE 6-1
         img[110,373],img[184,373],img[254,373],img[324,373],img[396,373],img[466,373], #columnD 12-7
         img[537,373],img[607,373],img[680,373],img[750,372],img[820,373],img[891,373], #columnD 6-1
         img[110,442],img[184,442],img[254,442],img[324,442],img[396,442],img[466,442], #columnC 12-7
         img[537,442],img[607,442],img[680,442],img[750,443],img[820,442],img[891,442], #columnC 6-1
         img[109,511],img[184,511],img[254,511],img[324,511],img[396,511],img[466,511], #columnB 12-7
         img[537,512],img[607,512],img[680,511],img[750,511],img[820,511],img[891,511], #columnB 6-1
         img[109,582],img[184,582],img[254,582],img[324,581],img[396,582],img[466,582], #columnA 12-7
         img[537,581],img[607,582],img[680,582],img[750,581],img[820,582],img[891,582]] #columnA 6-1

bAvgFilledWells = []
gAvgFilledWells = []
rAvgFilledWells = []

#filtering out the centroids that are not needed
#and getting the bgr values for the first color on the plate
for center in wells:
    if center[1] > 124:
        if center[0] < 360:
            b = img[center[0]-4: center[0]+5, center[1]-4: center[1]+5, 0]
            g = img[center[0]-4: center[0]+5, center[1]-4: center[1]+5, 1]
            r = img[center[0]-4: center[0]+5, center[1]-4: center[1]+5, 2]
            bAvg = np.mean(b)
            gAvg = np.mean(g)
            rAvg = np.mean(r)

            bAvgFilledWells.append(bAvg)
            gAvgFilledWells.append(gAvg)
            rAvgFilledWells.append(rAvg)
            print(center)
            print("For the first color, average value for blue is:", bAvg)
            print("For the first color, average value for green is:", gAvg)
            print("For the first color, average value for red is:", rAvg)


bAvgFilledWells2 = []
gAvgFilledWells2 = []
rAvgFilledWells2 = []

#filtering out the centroids that are not needed
#and getting the bgr values for the second color on the plate        
for center in wells:
    if center[1] > 124:
        if center[0] > 360 and center[0] < 642:
            b2 = img[center[0]-4: center[0]+5, center[1]-4: center[1]+5, 0]
            g2 = img[center[0]-4: center[0]+5, center[1]-4: center[1]+5, 1]
            r2 = img[center[0]-4: center[0]+5, center[1]-4: center[1]+5, 2]
            bAvg2 = np.mean(b2)
            gAvg2 = np.mean(g2)
            rAvg2 = np.mean(r2)

            print(center)
            print("For the second color, average value for blue is:", bAvg2)
            print("For the second color, average value for green is:", gAvg2)
            print("For the second color, average value for blue is:", rAvg2)
            bAvgFilledWells2.append(bAvg2)
            gAvgFilledWells2.append(gAvg2)
            rAvgFilledWells2.append(rAvg2)