提前约定：

pixmap是QPixmap类型的变量

image是QImage类型的变量

QPixmap=>QImage

image = pixmap.toImage()

QImage=>QPixmap

pixmap=QPixmap.fromImage(image)

Opencv=>Qimage

方法一：

def Opencv2QImage(opencv_img):
    width = opencv_img.shape[1] #获取图片宽度
    height = opencv_img.shape[0]  #获取图片高度
    pixmap = QPixmap(width, height) #根据已知的高度和宽度新建一个空的QPixmap,
    image = pixmap.toImage()  #将pximap转换为QImage类型的qimg
    #循环读取cv_image的每个像素的r,g,b值，构成qRgb对象，再设置为qimg内指定位置的像素
    for row in range(0, height):
        for col in range(0,width):
            b = opencv_img[row,col,0]
            g = opencv_img[row,col,1]
            r = opencv_img[row,col,2]
            pix = qRgb(r, g, b)
            image.setPixel(col, row, pix)
    return image #转换完成，返回

方法二

def OpencvToQImage(data):
    # 8-bits unsigned, NO. OF CHANNELS=1
    if data.dtype == np.uint8:
        channels = 1 if len(data.shape) == 2 else data.shape[2]
    if channels == 3: # CV_8UC3
        # Copy input Mat
        # Create QImage with same dimensions as input Mat
        img = QImage(data, data.shape[1], data.shape[0], data.strides[0], QImage.Format_RGB888)
        return img.rgbSwapped()
    elif channels == 1:
        # Copy input Mat
        # Create QImage with same dimensions as input Mat
        img = QImage(data, data.shape[1], data.shape[0], data.strides[0], QImage.Format_Indexed8)
        return img
    else:
        print("ERROR: numpy.ndarray could not be converted to QImage. Channels = %d" % data.shape[2])
        return QImage()

方法三(推荐):

def Opencv2QImage(cvimg):
    height, width, depth = cvimg.shape
    cvimg = cv2.cvtColor(cvimg, cv2.COLOR_BGR2RGB)
    cvimg = QImage(cvimg.data, width, height, width * depth, QImage.Format_RGB888)
    return cvimg

Qimage=>Opencv

def QImage2Opencv(qimg):
    
    tmp = qimg
    #使用numpy创建空的图象
    cv_image = numpy.zeros((tmp.height(), tmp.width(), 3), dtype=numpy.uint8)
  
    for row in range(0, tmp.height()):
        for col in range(0,tmp.width()):
            r = qRed(tmp.pixel(col, row))
            g = qGreen(tmp.pixel(col, row))
            b = qBlue(tmp.pixel(col, row))
            cv_image[row,col,0] = b
            cv_image[row,col,1] = g
            cv_image[row,col,2] = r
    
    return cv_image

QPixmap=>Opencv

def QPixmap2Opencv(pixmap):

    qimg = pixmap.toImage()
    temp_shape = (qimg.height(), qimg.bytesPerLine() * 8 // qimg.depth())
    temp_shape += (4,)
    ptr = qimg.bits()
    ptr.setsize(qimg.byteCount())
    result = np.array(ptr, dtype=np.uint8).reshape(temp_shape)
    result = result[..., :3]
    return result

Opencv=>QPixmap

可以现将Opencv转Qimage，然后把Qimage转Qpixmap