如何将像素/numpy-array 转换为矢量点？

Question

我想将灰度图片的像素值转换为矢量点，以便像素的灰度值确定相应点的半径。 但是我完全卡住了，这个项目必须在周日完成，我现在真的很绝望

背景： 对于我的大学课程“python 简介”，我想用 python 构建一个“rasterbator”（https://rasterbator.net/）的无耻副本（但以更原始的方式） .

我想如何解决这个问题？： 我用 PIL 加载图像，使其成为灰度图像并将其转换为 numpy 数组。然后我将数组分割成许多小正方形数组（每个预期点一个段），计算每个数组的平均值并将其重新组合到一个数组中，该数组现在比原始数组小得多。到那时，我能够做到（但我花了很长时间）。 现在我想用点“替换”像素并创建几个 PDF，这样您就可以打印、粘合在一起并制作一张大海报。

这种方法可行吗？还是我找错树了？

我是一个该死的 python 初学者。 python的问题是对我来说，有太多我不知道的模块。可能答案真的很简单，但我根本不知道在哪里看。如果有人能告诉我，我是否走在正确的道路上或指向正确的方向，我将不胜感激。

提前致谢

这里是我目前管理的代码（虽然不多）

from PIL import Image as img
import numpy as np

greyscale = np.asarray(img.open("test.jpg").convert("L")) #load picture into array and make it greyscale

end_width = 1500 # chosen width of final picture in mm (will be with kwargs later on)
dot_size = 13 #chosen dot-size of final pictutre in mm (will be with kwargs later on)
estimate_dot_count_x = int(np.ceil(end_width/dot_size)) # estimates the "horizontal resolution"

pixel_in_segment = int(np.ceil(greyscale.shape[1]/estimate_dot_count_x)) #calculates the edge length of a segment
W=pixel_in_segment #just for shorter formular later on 

estimate_dot_count_y = int(np.ceil(greyscale.shape[0]/pixel_in_segment)) # estimates the "vertical resolution"
final_dot_count_x=int(np.ceil(greyscale.shape[1]/W)) #final horizontal resolution for shape of new array
final_dot_count_y=int(np.ceil(greyscale.shape[0]/W)) #final vertical resolution for shape of new array
#slice array into multiple pieces
tiles = [greyscale[x:x+W,y:y+W] for x in range(0,greyscale.shape[0],W) for y in range(0,greyscale.shape[1],W)]
#calculate mean values of each segment an safe it to list
average_list = []
for pixel in tiles:
    result=int(np.mean(pixel))
    average_list.append(result)
#convert list back into an array
downscale=np.asarray(average_list, dtype=int).reshape(final_dot_count_y,final_dot_count_x)

编辑： 不知何故，我设法将数组绘制到矢量点：

#inverse and normalize gray value so That I can multiply with max dot size
for ix,iy in np.ndindex(downscale.shape):
    downscale[ix,iy]= float(1-downscale[ix,iy]*(1/255))

reportlab 是我一直在寻找的关键...

from reportlab.lib.units import mm
from reportlab.pdfgen import canvas
#making dots
def printing(c):
    c.translate(spacing*0.5,imh-(spacing*0.5))
    for ix,iy in np.ndindex(downscale.shape):
       c.circle(iy*(spacing), ix*(-spacing), downscale[ix, iy]*max_dot_size, stroke=1, fill=1)
c = canvas.Canvas("hello.pdf", pagesize=(imwidth, imhight))
printing(c)
c.showPage()
c.save()

这就提出了一个问题： 如何告诉reportlab，我想以通用打印机格式（'letter' 或'A4'）将这个大画布（尺寸为 2m x1.5m）打印到多页？

Answer 1

仅供参考，我可以重建“Rasterbator” 代码可能有点混乱，并且缺少错误处理，但我工作得非常好，而且我没时间了。所以这就是我上传的。 一些变量是德语，对不起。我倾向于混合语言。必须改变它。

需要模块reportlab

from PIL import Image as img
import numpy as np
from reportlab.lib.units import mm
from reportlab.pdfgen import canvas
from reportlab.lib.pagesizes import A4
from math import sqrt


#load image to array and make it greyscale
input_file = input("Please enter the image file you want do convert: ")
greyscale = np.asarray(img.open(input_file).convert("L"))

print("\n"+"Image resolution is " + str(greyscale.shape[1]) + "x" + str(greyscale.shape[0]))
#defining width of poster
print("\n"+"please enter the target width of your poster")
print("remember, the dimensions of an A4 sheet is: 210mm x 297mm ")
end_width= int(input("target poster width in mm: "))
#defining grid size of poster
print('\n'+'The distance between 2 Points in the grid. Choose the grid size wisely in relation to the size of your poster '+'\n'+'recommended size is 7-12mm')
print('please notice, that the maximum dot size is higher than the grid size (factor 1.4) to allow pure black coverage')
grid_size = int(input("Please enter the target grid size in mm: "))
#select orientation
print("your sheets can be arranged in portrait or landscape orientation")
print_format = input("Please enter p for portrait or l for landscape :")

if print_format=="l":
    height, width = A4 #Landscape
elif print_format=="p":
    width, height = A4 #Portrait
else:
    print("-invalid input-  continuing with default (portrait)")
    width, height = A4 #Portrait



# calculates the "x-resolution" as a base for further calculations
estimate_dot_count_x = int(np.ceil(end_width/grid_size)) 

#calculates the size of a segment in array
pixel_in_segment = int(np.ceil(greyscale.shape[1]/estimate_dot_count_x))
W=pixel_in_segment #obsolete, just for shorter formulars later on

#final horizontal resolution for shape of new array
final_dot_count_x=int(np.ceil(greyscale.shape[1]/W))
#final vertical resolution for shape of new array
final_dot_count_y=int(np.ceil(greyscale.shape[0]/W))
#slice array into multiple pieces
tiles = [greyscale[x:x+W,y:y+W] for x in range(0,greyscale.shape[0],W) for y in range(0,greyscale.shape[1],W)]

#calculate mean values of each segment an safe it to list
average_list = []
for pixel in tiles:
    result=int(np.mean(pixel))
    average_list.append(result)

#convert list back into an array 
downscale=np.asarray(average_list, dtype=float).reshape(final_dot_count_y,final_dot_count_x)

print('\n'+'downscaling picture...')

#prepare data to work in point scale
spacing=grid_size*mm
#calculating final poster size
imw=downscale.shape[1]*spacing
imh=downscale.shape[0]*spacing
#scaling dots to allow complete coverage with black for very dark areas
max_dot_size=spacing*sqrt(2)/2

#inverse and normalize pixel value
for ix,iy in np.ndindex(downscale.shape):
    downscale[ix,iy]= float(1-downscale[ix,iy]*(1/255))


print('\n'+'printing image to pdf...')
#calculate numer of A4 sheets required for printing
pages_w = int(np.ceil(imw/width))
pages_h = int(np.ceil(imh/height))
#stuff for showing progress while printing
seitenzahl=0
gesamtseitenzahl = pages_w*pages_h


def printing(c):
    #auxillary variables for iterating over poster
    left=width*x
    top=height*y
    #iterate instructions
    c.translate(-left+spacing*0.5,imh-top+(spacing*0.5))
    #drawing the circles
    for ix,iy in np.ndindex(downscale.shape):
        c.circle(iy*(spacing), ix*(-spacing), downscale[ix, iy]*max_dot_size, stroke=1, fill=1)

#setting canvas properties
c = canvas.Canvas(str(input_file)+".pdf", pagesize=(width, height))
#make pages
for x in range(pages_w):
    for y in range(pages_h):
        #progress documentation
        seitenzahl = seitenzahl+1
        #call printing function
        printing(c)
        #progress documentation
        print("printing page " + str(seitenzahl)+ " of " + str(gesamtseitenzahl))
        c.showPage()

#save to disk        
print('\n'+'save to disk...')
c.save()
print('...PDF successfully saved as ' + str(input_file)+".pdf")

Answer 2

而不是“将图像切成小方块并计算每个方块的平均值”...如果您想要 80 个点通过 60 个点向下，只需像这样使用resize()：

im_resized = im.resize((80, 60))