模板匹配源码

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import cv2 import numpy as npfrom numpy import * import aircv as ac#在图像上下左右取额定大小的区域，并计算每个区域的sobel算子矩阵#定义模板此尺寸template_size = 60def getROISobel(src, index_x , index_y):    global template_size    xBegin = (src.shape[0]/4) * (2*index_x + 1) - (template_size/2)    yBegin = (src.shape[1]/4) * (2*index_y + 1) - (template_size/2)    xBegin = int(xBegin)    yBegin = int(yBegin)    print(src[xBegin : (xBegin + template_size), yBegin : (yBegin + template_size)].shape)    after_translation_x = cv2.Sobel(src[xBegin : xBegin+template_size, yBegin : yBegin + template_size] ,cv2.CV_16S, 1, 0)    after_translation_y = cv2.Sobel(src[xBegin : xBegin+template_size, yBegin : yBegin + template_size] ,cv2.CV_16S, 0, 1)    after_translation_x_abs = np.fabs(after_translation_x)    after_translation_y_abs = np.fabs(after_translation_y)    after_translation_magnitude = cv2.addWeighted(after_translation_x_abs,0.5,after_translation_x_abs,0.5,0)     return after_translation_magnitude#获取每一份sobel区域矩阵的sum值def sum(src):    sum = 0    for i in range(0, src.shape[0]):        for j in range(0, src.shape[1]):            sum += src[i][j]    return sum#返回所选模板的参数def get_position_index(region_1, region_2, region_3, region_4):    index = array([0,0])        if(sum(region_1) == max(sum(region_1), sum(region_2), sum(region_3), sum(region_4))):        index = array([0,0])        elif (sum(region_2) == max(sum(region_1), sum(region_2), sum(region_3), sum(region_4))):        index = array([0,1])     elif (sum(region_3) == max(sum(region_1), sum(region_2), sum(region_3), sum(region_4))):        index = array([1,0])     else:        index = array([1,1])     return index#找到图像与模板匹配的位置坐标def findposition(img, position_index):    imsrc = ac.imread('D:\\python_opencv\\source_image\\1122\\2\\1.jpg')    imtemplate = imsrc[int((imsrc.shape[0]/4) * (2*position_index[0] + 1) - (template_size/2)) : int((imsrc.shape[0]/4) * (2*position_index[0] + 1) + (template_size/2)), int((imsrc.shape[1]/4) * (2*position_index[1] + 1) - (template_size/2)) : int((imsrc.shape[1]/4) * (2*position_index[1] + 1) + (template_size/2))] #第一个参数代表y方向，第二个参数代表x方向    imsrc = img    # find the match position    #print("imsrc", imsrc)    pos = ac.find_template(imsrc, imtemplate,threshold=0.2)    #print("pos", pos)    center_pos = pos['result']    return center_pos#画图def draw_rectangle(img, pos_1, pos_4, color, line_width):    cv2.rectangle(img, pos_1, pos_4, color, line_width)    cv2.imshow('objDetect', imsrc)     cv2.waitKey(0)    cv2.destroyAllWindows()def translate(img, x, y):    H = np.float32([[1,0,x],[0,1,y]])    rows,cols = img.shape[:2]    res = cv2.warpAffine(img,H,(cols,rows)) #需要图像、变换矩阵、变换后的大小    return resdef add(a,b):        # 迭代输出行    result = np.zeros((640,480))    for i in range(len(a)):       # 迭代输出列        for j in range(len(a[0])):            result[i][j] = a[i][j] + b[i][j]    return resultdef typeconvert(a):    for i in range(len(a)):       # 迭代输出列        for j in range(len(a[0])):            a[i][j] = a[i][j] * (256)    return adef f(x):    return np.float(x)def g(x):    return np.int(x)if __name__ == "__main__":    img = cv2.imread("D:\\python_opencv\\source_image\\1123\\1\\1.jpg",0)    region_1 = getROISobel(img, 0, 0)    region_2 = getROISobel(img, 0, 1)    region_3 = getROISobel(img, 1, 0)    region_4 = getROISobel(img, 1, 1)    print(sum(region_1))    print(sum(region_2))    print(sum(region_3))    print(sum(region_4))    position_index = get_position_index(region_1, region_2, region_3, region_4)    print(position_index)    imsrc_1 = cv2.imread('D:\\python_opencv\\source_image\\1123\\1\\1.jpg')    imsrc_2 = cv2.imread('D:\\python_opencv\\source_image\\1123\\1\\2.jpg')    imsrc_3 = cv2.imread('D:\\python_opencv\\source_image\\1123\\1\\3.jpg')    imsrc_4 = cv2.imread('D:\\python_opencv\\source_image\\1123\\1\\4.jpg')    imsrc_5 = cv2.imread('D:\\python_opencv\\source_image\\1123\\1\\5.jpg')    imsrc_6 = cv2.imread('D:\\python_opencv\\source_image\\1123\\1\\6.jpg')    imsrc_7 = cv2.imread('D:\\python_opencv\\source_image\\1123\\1\\7.jpg')    imsrc_8 = cv2.imread('D:\\python_opencv\\source_image\\1123\\1\\8.jpg')    imsrc_9 = cv2.imread('D:\\python_opencv\\source_image\\1123\\1\\9.jpg')    imsrc_10 = cv2.imread('D:\\python_opencv\\source_image\\1123\\1\\10.jpg')    position_1 = findposition(imsrc_1, position_index)    position_2 = findposition(imsrc_2, position_index)    position_3 = findposition(imsrc_3, position_index)    position_4 = findposition(imsrc_4, position_index)    position_5 = findposition(imsrc_5, position_index)    position_6 = findposition(imsrc_6, position_index)    position_7 = findposition(imsrc_7, position_index)    position_8 = findposition(imsrc_8, position_index)    position_9 = findposition(imsrc_9, position_index)    position_10 = findposition(imsrc_10, position_index)    print("position_1[0]", position_1[0])    print("position_1[1]", position_1[1])    print("position_2[0]", position_2[0])    print("position_2[1]", position_2[1])    print("position_3[0]", position_3[0])    print("position_3[1]", position_3[1])    print("position_4[0]", position_4[0])    print("position_4[1]", position_4[1])    print(position_1[0] - position_2[0])    print(position_1[1] - position_2[1])    print(position_1[0] - position_3[0])    print(position_1[1] - position_3[1])    print(position_1[0] - position_4[0])    print(position_1[1] - position_4[1])    print(position_1[0] - position_5[0])    print(position_1[1] - position_5[1])    print(position_1[0] - position_6[0])    print(position_1[1] - position_6[1])    print(position_1[0] - position_7[0])    print(position_1[1] - position_7[1])    print(position_1[0] - position_8[0])    print(position_1[1] - position_8[1])    print(position_1[0] - position_9[0])    print(position_1[1] - position_9[1])    print(position_1[0] - position_10[0])    print(position_1[1] - position_10[1])    imsrc_1 = translate(imsrc_1, position_1[0] - position_1[0], position_1[1] - position_1[1])    imsrc_2 = translate(imsrc_2, position_1[0] - position_2[0], position_1[1] - position_2[1])    imsrc_3 = translate(imsrc_3, position_1[0] - position_3[0], position_1[1] - position_3[1])    imsrc_4 = translate(imsrc_4, position_1[0] - position_4[0], position_1[1] - position_4[1])    imsrc_5 = translate(imsrc_5, position_1[0] - position_5[0], position_1[1] - position_5[1])    imsrc_6 = translate(imsrc_6, position_1[0] - position_6[0], position_1[1] - position_6[1])    imsrc_7 = translate(imsrc_7, position_1[0] - position_7[0], position_1[1] - position_7[1])    imsrc_8 = translate(imsrc_8, position_1[0] - position_8[0], position_1[1] - position_8[1])    imsrc_9 = translate(imsrc_9, position_1[0] - position_9[0], position_1[1] - position_9[1])    imsrc_10 = translate(imsrc_10, position_1[0] - position_10[0], position_1[1] - position_10[1])    '''    imsrc_8 = cv2.imread('D:\\python_opencv\\source_image\\image_match\\8.jpg')    imsrc_9 = cv2.imread('D:\\python_opencv\\source_image\\image_match\\9.jpg')        imsrc_10 = cv2.imread('D:\\python_opencv\\source_image\\image_match\\10.jpg')    '''    #imsrc_sum = add(imsrc_1, imsrc_2, imsrc_3, imsrc_4, imsrc_5, imsrc_6, imsrc_7)    print(imsrc_1.shape)    f2 = np.vectorize(f)#让函数矩阵化，解决只能一对一强制性变换这一要求    imsrc_1 = f2(imsrc_1)    imsrc_2 = f2(imsrc_2)    #imsrc_sum = imsrc_1 + imsrc_2 + imsrc_3 + imsrc_4 + imsrc_5 + imsrc_6 + imsrc_7    #imsrc_average = imsrc_sum/7    imsrc_sum = imsrc_1 + imsrc_2 + imsrc_3 + imsrc_4 + imsrc_5 + imsrc_6 + imsrc_7 + imsrc_8 + imsrc_9 + imsrc_10    imsrc_average = imsrc_sum/10    #imsrc_sum = add(imsrc_1, imsrc_2)    g2 = np.vectorize(g)#让函数矩阵化，解决只能一对一强制性变换这一要求    #imsrc_average = g2(imsrc_average)    #imsrc_average = np.unit8(imsrc_average)    #print(g2(imsrc_average))    cv2.imshow('merge', typeconvert(g2(imsrc_average)))             cv2.waitKey(0)    cv2.destroyAllWindows()

second_max

import cv2 import numpy as npfrom numpy import * import aircv as ac#在图像上下左右取额定大小的区域，并计算每个区域的sobel算子矩阵#定义模板此尺寸template_size = 80def getROISobel(src, index_x , index_y):    global template_size    xBegin = (src.shape[0]/4) * (2*index_x + 1) - (template_size/2)    yBegin = (src.shape[1]/4) * (2*index_y + 1) - (template_size/2)    xBegin = int(xBegin)    yBegin = int(yBegin)    print(src[xBegin : (xBegin + template_size), yBegin : (yBegin + template_size)].shape)    after_translation_x = cv2.Sobel(src[xBegin : xBegin+template_size, yBegin : yBegin + template_size] ,cv2.CV_16S, 1, 0)    after_translation_y = cv2.Sobel(src[xBegin : xBegin+template_size, yBegin : yBegin + template_size] ,cv2.CV_16S, 0, 1)    after_translation_x_abs = np.fabs(after_translation_x)    after_translation_y_abs = np.fabs(after_translation_y)    after_translation_magnitude = cv2.addWeighted(after_translation_x_abs,0.5,after_translation_x_abs,0.5,0)     return after_translation_magnitude#获取每一份sobel区域矩阵的sum值def sum(src):    sum = 0    for i in range(0, src.shape[0]):        for j in range(0, src.shape[1]):            sum += src[i][j]    return sum#返回所选模板的参数def get_position_index(region_1, region_2, region_3, region_4):    index = array([0,0])        if(sum(region_1) == max(sum(region_1), sum(region_2), sum(region_3), sum(region_4))):        if(sum(region_2) == max(sum(region_2), sum(region_3), sum(region_4))):            index = array([0,1])        elif(sum(region_3) == max(sum(region_2), sum(region_3), sum(region_4))):            index = array([1,0])        else:            index = array([1,1])    elif (sum(region_2) == max(sum(region_1), sum(region_2), sum(region_3), sum(region_4))):        if(sum(region_1) == max(sum(region_1), sum(region_3), sum(region_4))):            index = array([0,0])        if(sum(region_3) == max(sum(region_1), sum(region_3), sum(region_4))):            index = array([1,0])        else:            index = array([1,1])     elif (sum(region_3) == max(sum(region_1), sum(region_2), sum(region_3), sum(region_4))):        if(sum(region_1) == max(sum(region_1), sum(region_2), sum(region_4))):            index = array([0,0])        if(sum(region_2) == max(sum(region_1), sum(region_2), sum(region_4))):            index = array([0,1])        else:            index = array([1,1])     else:        if(sum(region_1) == max(sum(region_1), sum(region_2), sum(region_3))):            index = array([0,0])        if(sum(region_2) == max(sum(region_1), sum(region_2), sum(region_3))):            index = array([0,1])        else:            index = array([1,0])     return index#找到图像与模板匹配的位置坐标def findposition(img, position_index):    imsrc = ac.imread('D:\\python_opencv\\source_image\\1123\\1\\1.jpg')    imtemplate = imsrc[int((imsrc.shape[0]/4) * (2*position_index[0] + 1) - (template_size/2)) : int((imsrc.shape[0]/4) * (2*position_index[0] + 1) + (template_size/2)), int((imsrc.shape[1]/4) * (2*position_index[1] + 1) - (template_size/2)) : int((imsrc.shape[1]/4) * (2*position_index[1] + 1) + (template_size/2))] #第一个参数代表y方向，第二个参数代表x方向    imsrc = img    # find the match position    #print("imsrc", imsrc)    pos = ac.find_template(imsrc, imtemplate,threshold=0.2)    #print("pos", pos)    center_pos = pos['result']    return center_pos#画图def draw_rectangle(img, pos_1, pos_4, color, line_width):    cv2.rectangle(img, pos_1, pos_4, color, line_width)    cv2.imshow('objDetect', imsrc)     cv2.waitKey(0)    cv2.destroyAllWindows()def translate(img, x, y):    H = np.float32([[1,0,x],[0,1,y]])    rows,cols = img.shape[:2]    res = cv2.warpAffine(img,H,(cols,rows)) #需要图像、变换矩阵、变换后的大小    return resdef add(a,b):        # 迭代输出行    result = np.zeros((640,480))    for i in range(len(a)):       # 迭代输出列        for j in range(len(a[0])):            result[i][j] = a[i][j] + b[i][j]    return resultdef typeconvert(a):    for i in range(len(a)):       # 迭代输出列        for j in range(len(a[0])):            a[i][j] = a[i][j] * (256)    return adef f(x):    return np.float(x)def g(x):    return np.int(x)if __name__ == "__main__":    img = cv2.imread("D:\\python_opencv\\source_image\\1122\\2\\1.jpg",0)    region_1 = getROISobel(img, 0, 0)    region_2 = getROISobel(img, 0, 1)    region_3 = getROISobel(img, 1, 0)    region_4 = getROISobel(img, 1, 1)    print(sum(region_1))    print(sum(region_2))    print(sum(region_3))    print(sum(region_4))    position_index = get_position_index(region_1, region_2, region_3, region_4)    print(position_index)    imsrc_1 = cv2.imread('D:\\python_opencv\\source_image\\1123\\1\\1.jpg')    imsrc_2 = cv2.imread('D:\\python_opencv\\source_image\\1123\\1\\2.jpg')    imsrc_3 = cv2.imread('D:\\python_opencv\\source_image\\1123\\1\\3.jpg')    imsrc_4 = cv2.imread('D:\\python_opencv\\source_image\\1123\\1\\4.jpg')    imsrc_5 = cv2.imread('D:\\python_opencv\\source_image\\1123\\1\\5.jpg')    imsrc_6 = cv2.imread('D:\\python_opencv\\source_image\\1123\\1\\6.jpg')    imsrc_7 = cv2.imread('D:\\python_opencv\\source_image\\1123\\1\\7.jpg')    imsrc_8 = cv2.imread('D:\\python_opencv\\source_image\\1123\\1\\8.jpg')    imsrc_9 = cv2.imread('D:\\python_opencv\\source_image\\1123\\1\\9.jpg')    imsrc_10 = cv2.imread('D:\\python_opencv\\source_image\\1123\\1\\10.jpg')    position_1 = findposition(imsrc_1, position_index)    position_2 = findposition(imsrc_2, position_index)    position_3 = findposition(imsrc_3, position_index)    position_4 = findposition(imsrc_4, position_index)    position_5 = findposition(imsrc_5, position_index)    position_6 = findposition(imsrc_6, position_index)    position_7 = findposition(imsrc_7, position_index)    position_8 = findposition(imsrc_8, position_index)    position_9 = findposition(imsrc_9, position_index)    position_10 = findposition(imsrc_10, position_index)    print("position_1[0]", position_1[0])    print("position_1[1]", position_1[1])    print("position_2[0]", position_2[0])    print("position_2[1]", position_2[1])    print(position_1[0] - position_2[0])    print(position_1[1] - position_2[1])    print(position_1[0] - position_3[0])    print(position_1[1] - position_3[1])    print(position_1[0] - position_4[0])    print(position_1[1] - position_4[1])    print(position_1[0] - position_5[0])    print(position_1[1] - position_5[1])    print(position_1[0] - position_6[0])    print(position_1[1] - position_6[1])    print(position_1[0] - position_7[0])    print(position_1[1] - position_7[1])    print(position_1[0] - position_8[0])    print(position_1[1] - position_8[1])    print(position_1[0] - position_9[0])    print(position_1[1] - position_9[1])    print(position_1[0] - position_10[0])    print(position_1[1] - position_10[1])    imsrc_1 = translate(imsrc_1, position_1[0] - position_1[0], position_1[1] - position_1[1])    imsrc_2 = translate(imsrc_2, position_1[0] - position_2[0], position_1[1] - position_2[1])    imsrc_3 = translate(imsrc_3, position_1[0] - position_3[0], position_1[1] - position_3[1])    imsrc_4 = translate(imsrc_4, position_1[0] - position_4[0], position_1[1] - position_4[1])    imsrc_5 = translate(imsrc_5, position_1[0] - position_5[0], position_1[1] - position_5[1])    imsrc_6 = translate(imsrc_6, position_1[0] - position_6[0], position_1[1] - position_6[1])    imsrc_7 = translate(imsrc_7, position_1[0] - position_7[0], position_1[1] - position_7[1])    imsrc_8 = translate(imsrc_8, position_1[0] - position_8[0], position_1[1] - position_8[1])    imsrc_9 = translate(imsrc_9, position_1[0] - position_9[0], position_1[1] - position_9[1])    imsrc_10 = translate(imsrc_10, position_1[0] - position_10[0], position_1[1] - position_10[1])    '''    imsrc_8 = cv2.imread('D:\\python_opencv\\source_image\\image_match\\8.jpg')    imsrc_9 = cv2.imread('D:\\python_opencv\\source_image\\image_match\\9.jpg')        imsrc_10 = cv2.imread('D:\\python_opencv\\source_image\\image_match\\10.jpg')    '''    #imsrc_sum = add(imsrc_1, imsrc_2, imsrc_3, imsrc_4, imsrc_5, imsrc_6, imsrc_7)    print(imsrc_1.shape)    f2 = np.vectorize(f)#让函数矩阵化，解决只能一对一强制性变换这一要求    imsrc_1 = f2(imsrc_1)    imsrc_2 = f2(imsrc_2)    #imsrc_sum = imsrc_1 + imsrc_2 + imsrc_3 + imsrc_4 + imsrc_5 + imsrc_6 + imsrc_7    #imsrc_average = imsrc_sum/7    imsrc_sum = imsrc_1 + imsrc_2 + imsrc_3 + imsrc_9    imsrc_average = imsrc_sum/4    #imsrc_sum = add(imsrc_1, imsrc_2)    g2 = np.vectorize(g)#让函数矩阵化，解决只能一对一强制性变换这一要求    #imsrc_average = g2(imsrc_average)    #imsrc_average = np.unit8(imsrc_average)    #print(g2(imsrc_average))    cv2.imshow('merge', typeconvert(g2(imsrc_average)))             cv2.waitKey(0)    cv2.destroyAllWindows()

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