在PyQt中,如何将QImage转换为像素列表?

时间:2015-08-17 20:40:15

标签: pyqt pyqt4

我看到QImage.bits()函数和QImage.constBits(),但都返回voidptr,我不确定在python中你可以用它做什么。我熟悉C ++语法,但不熟悉python。

至于数据类型,我的意思是: 黑白像素等于[[0,0,0],[255,255,255]] QImage Format.RGB888

2 个答案:

答案 0 :(得分:1)

See the youtube video

我希望我了解您的需求,在这里我整理了一个应用程序。将QImage转换为Quadruplets的列表RGBA值,我希望它至少帮助你弄清楚如何做到这一点,你可以根据自己的需要实现它,你可以使用矩阵/矩阵操作库。像NumPy或任何其他矩阵操作lib。

但是,在这种情况下,我没有创造任何依赖,因为我认为保持简单更好,如果你需要更复杂的东西,你可以挖掘......

你需要一个图像,为了保持简单,我将提供3张图像,每张图像都有不同的尺寸和像素颜色Image 1 Image 2 Image 3

您还可以check my website to see the code

这是代码:

from PyQt4.QtCore import *
from PyQt4.QtGui import *
import sys


class main_window(QDialog):
    def __init__(self):
        QDialog.__init__(self)

        # Create a QTextBrowser
        qtb_rgba = QTextBrowser(self)
        # Create an empty list
        li_pixels = list()


        #!! QImage to list of pixels !! >>> RGB format
        image = QImage()
        load_image = image.load("test_img_3x3", ".jpg")
        # Make sure you got an image named "test_img_3x3" .jpg extension , it needs to sit on your HDD,
        # in the root from where you run the script
        # create it with the size of 3x3 , do it in Paint, or any other 2d image manipulation software

        # An assert error will occur if fails to open your image
        assert load_image == True

        # Find more data about our image
        # In our case is obvios that we create with our hand an image .jpg with a size of 3x3
        # Even so, the functions bellow will may help us sometimes

        # Obtain image size
        image_width = image.width()
        image_height = image.height()
        print("Your image size is:\nWidth: " + str(image_width) + " Height: " + str(image_height) + "\n" + str(image_width) + "x" + str(image_height))


        # Get QRGB values
        qrgb = image.pixel(0, 0)
        print("QRGB Values: " + str(qrgb))
        # Convert it to QColor
        qrgb_to_QCol = QColor(qrgb)
        # Once you got it converted in QColor you got a lot of freedom to choose from,
        # you can convert it to some of the most popular formats like:
        # CMYK, HSL, RGB, RGBA, magenta, or even individual chanels R , G , B  + a lot of other formats, even Floats...

        # Convert it to RGBA
        rgba = qrgb_to_QCol.getRgb()
        print("RGBA Values: " + str(rgba))

        # In order to achieve our goal: list of pixels for the entire image
        # we got many ways to achieve it, depending of your needs you may implelent it different
        # I will continue by producing a list of quadruplets values, 
        # from left to right - top to bottom 

        # The Quadruplets value for the list will be, which mean that 0 will hold value 0 on list , 1 hold 1 and so on...
        # y _ _
       #x|0 1 2
        #|3 4 5
        #|6 7 8

        # And the position will be:
        # y     _     _
       #x|0.0   1.0   2.0
        #|0.1   1.1   2.1
        #|0.2   1.2   2.2

        # So let`s do it

        # Generate a list of numbers for width
        li_num_width = []
        for i in range(image_width):
            li_num_width.append(i)

        # Generate a list of numbers for height
        li_num_height = []
        for i in range(image_height):
            li_num_height.append(i)

        # List for x num
        x = [li_num_width for i in range(len(li_num_height))]
        print("\nX list is:\n" + str(x))

        # List for y num
        for i in range(len(li_num_height)):
            y = [[i]*len(li_num_width) for i in range(len(li_num_height))]
        print("\nY list is:\n" + str(y))


        row_el_li = []
        row_el_li_y = []

        # Obtain list numbers for x
        for i in range(len(li_num_height)):
            row = x[i]
            for i in range(len(li_num_width)):
                row_el = row[i]
                #print(row_el)
                row_el_li.append(row_el)

        print("\nRow Elements list x: \n" + str(row_el_li))

        # Obtain list numbers for y
        for i in range(len(li_num_height)):
            row_y = y[i]
            for i in range(len(li_num_width)):
                row_el_y = row_y[i]
                #print(row_el_y)
                row_el_li_y.append(row_el_y)

        print("\nRow Elements list y: \n" + str(row_el_li_y))

        # Create a list, which eventualy will hold qrgb values, which is our goal
        qrgb_li = []
        # How many values will the list hold? or How many pixels in the image do we have?
        num_pixels = len(li_num_width) * len(li_num_height)
        print("\nNumber of Pixels:" + str(num_pixels))

        for i in range(num_pixels):
            ordered_qrgb = image.pixel(row_el_li[i], row_el_li_y[i])
            qrgb_li.append(ordered_qrgb)


        # One more step lets convert from QRGB list to RGBA list, which will lead us to the end of this tutorial
        rgba_li = []

        for i in range(len(qrgb_li)):
            qrgb_li_to_QCol = QColor(qrgb_li[i])
            rgba_set = qrgb_li_to_QCol.getRgb()
            rgba_li.append(rgba_set)

        print("\nList of Quadruplets RGBA Value: \n" + str(rgba_li))


        #!! QImage to list of pixels End !!

        qtb_rgba.setText(str(rgba_li))
        #.......
        self.setFixedSize(250, 300)
        self.setWindowTitle("QImage to list of pixels")

#.......3D Sasu Catalin
app = QApplication(sys.argv)
dialog = main_window()
dialog.show()
sys.exit(app.exec_())

我希望能帮助您,如果您需要有关此主题的更多详细信息,您可以不时访问my website ...

答案 1 :(得分:0)

对于仍然需要知道如何执行此操作的任何人,这是我当前正在使用的一些代码,无需保存和加载即可将像素数据从PyQt5传输到PyOpenCV。

由于PyOpenCV使用public static String[] no_repeats(String[] a) { return Arrays.stream(a) .distinct() .sorted() .toArray(String[]::new); } 代替了OpenCV numpy.array,因此应该可以回答这个问题。

Mat

我仍在快速试验原型,因此尚未对其进行优化,但这是这样做的方法:

  1. 验证没有解除引用悬空指针并从# Convert to 32-bit RGBA with solid opaque alpha # and get the pointer numpy will want. # # Cautions: # 1. I think I remember reading that PyQt5 only has # constBits() and PySide2 only has bits(), so you may # need to do something like `if hasattr(...)` for # portability. # # 2. Format_RGBX8888 is native-endian for your # platform and I suspect this code, as-is, # would break on a big-endian system. im_in = im_in.convertToFormat(QImage.Format_RGBX8888) ptr = im_in.constBits() ptr.setsize(im_in.byteCount()) # Convert the image into a numpy array in the # format PyOpenCV expects to operate on, explicitly # copying to avoid potential lifetime bugs when it # hasn't yet proven a performance issue for my uses. cv_im_in = np.array(ptr, copy=True).reshape( im_in.height(), im_in.width(), 4) cv_im_in = cv.cvtColor(cv_im_in, cv.COLOR_BGRA2RGB) 构造函数中删除copy=True的风险。
  2. 找到np.array可以产生的格式,相关的OpenCV模块可以直接使用该格式,并跳过QImage.convertToFormat步骤。 (我认为cv.cvtColor是这种格式,但目前我的项目中仍需要支持5.14之前的Qt版本。)