在PyQt中，如何将QImage转换为像素列表？

Question

我看到了QImage.bits()函数和QImage.constBits()，但它们都返回一个voidptr，我不确定在python中可以用它做什么。我熟悉C++语法，但不熟悉Python。

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

Answer 1

对于那些仍然需要知道如何做到这一点的人，我现在使用一些代码将像素数据从PyQt5获取到PyOpenCV，而无需保存和加载

由于PyOpenCV使用numpy.array代替OpenCV Mat，这应该可以回答这个问题

# 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)

我仍在快速试验原型，因此尚未对其进行优化，但下面介绍如何进行优化：

1. 验证不存在取消引用悬空指针的风险，并从np.array构造函数中删除copy=True
2. 找到QImage.convertToFormat可以生成的格式，相关OpenCV模块可以直接对其进行操作，并跳过cv.cvtColor步骤。（我认为Format_BGR888就是这种格式，但目前我的项目中仍然需要支持5.14之前的Qt版本。）

Answer 2

See the youtube video

我希望我能理解你的需求，在这里我组装了一个应用程序。这将把QImage转换成四元组RGBA值的列表，我希望它至少能帮助您了解如何实现它，您可以根据自己的需要实现它，您可以使用矩阵/矩阵操纵库。如NumPy或任何其他矩阵操作库

但是，在本例中，我没有创建任何依赖项，因为我认为保持简单更好，如果您需要更复杂的内容，您可以深入了解

你需要一张图片，为了简单起见，我将提供3张图片，每张图片的大小和像素颜色都不同。图片1:
图2:
图3:

你也可以check my website to see the code

代码如下：

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_())

我希望这能帮助你，如果你需要更多关于这个主题的细节，你可以不时访问my website