问题

I wish to utilize the easy plotting feature of Matplotlib to generate some bitmaps as templates or (rather large) convolution kernels.

我希望利用Matplotlib的简便绘图功能来生成一些位图作为模板或（相当大的）卷积核。

I followed this post to convert the plot into a Numpy array:

我按照此帖子的方法将绘图转换为Numpy数组：

def DrawKernel(x = 0.5, y = 0.5, radius = 0.49, dimension = 256):
    '''Make a solid circle and return a numpy array of it'''
    
    DPI = 100
    figure, axes = plt.subplots(figsize=(dimension/DPI, dimension/DPI), dpi=DPI)
    canvas = FigureCanvas(figure)

    Drawing_colored_circle = plt.Circle(( x, y ), radius, color='k')
    
    axes.set_aspect( 1 )
    axes.axis("off")
    axes.add_artist( Drawing_colored_circle )

    canvas.draw()  

    # Convert figure into a numpy array
    img = np.frombuffer(canvas.tostring_rgb(), dtype='uint8')
    img = img.reshape(dimension, dimension, 3)

    return img

But this seems to show the plot every time it's called (screenshot in Google Colab) :

但似乎每次调用此函数都会显示绘图（在Google Colab中截图）：

Since this function will be invoked frequently later, I don't want to see every plot generated with it. Is there a way to let it be generated but not displayed?

由于此函数将在以后频繁调用，我不想看到每次生成的绘图。是否有一种方法可以生成它但不显示？

def DrawKernel(x = 0.5, y = 0.5, radius = 0.49, dimension = 256):
    '''Make a solid circle and return a numpy array of it'''

    DPI = 100
    figure, axes = plt.subplots(figsize=(dimension/DPI, dimension/DPI), dpi=DPI)
    canvas = FigureCanvas(figure)

    Drawing_colored_circle = plt.Circle(( x, y ), radius, color='k')
    
    axes.set_aspect( 1 )
    axes.axis("off")
    axes.add_artist( Drawing_colored_circle )

    canvas.draw()  

    # Convert figure into an numpy array
    img = np.frombuffer(canvas.tostring_rgb(), dtype='uint8')
    img = img.reshape(dimension, dimension, 3)

    return img

答案1

得分: 1

Here is the translated code portion:

只需在`plt.subplots`中添加`visible=False`：

from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
from matplotlib.figure import Figure
from matplotlib import pyplot as plt
def DrawKernel(x = 0.5, y = 0.5, radius = 0.49, dimension = 256):
    '''创建一个实心圆并返回其numpy数组'''
    
    DPI = 100
    figure, axes = plt.subplots(figsize=(dimension/DPI, dimension/DPI), dpi=DPI, visible=False)
    canvas = FigureCanvas(figure)

    
    Drawing_colored_circle = plt.Circle(( x, y ), radius, color='k')
    
    axes.set_aspect( 1 )
    axes.axis("off")
    axes.add_artist( Drawing_colored_circle )
    
    canvas.draw()  
    
    # 将图形转换为numpy数组
    img = np.frombuffer(canvas.tostring_rgb(), dtype='uint8')
    img = img.reshape(dimension, dimension, 3)
    
    return img
DrawKernel();

Please note that I have translated the code part only, as per your request.

from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
from matplotlib.figure import Figure
from matplotlib import pyplot as plt
def DrawKernel(x = 0.5, y = 0.5, radius = 0.49, dimension = 256):
    '''Make a solid circle and return a numpy array of it'''

    DPI = 100
    figure, axes = plt.subplots(figsize=(dimension/DPI, dimension/DPI), dpi=DPI, visible=False)
    canvas = FigureCanvas(figure)


    Drawing_colored_circle = plt.Circle(( x, y ), radius, color='k')
    
    axes.set_aspect( 1 )
    axes.axis("off")
    axes.add_artist( Drawing_colored_circle )

    canvas.draw()  

    # Convert figure into an numpy array
    img = np.frombuffer(canvas.tostring_rgb(), dtype='uint8')
    img = img.reshape(dimension, dimension, 3)

    return img
DrawKernel();