废话少说，直接上图：

理论：

对图片灰度值以及字符的灰度值都做histogram，并进行主要部分的对应，可以改善对比度和显示效果

经过我在网上拼拼凑凑，以及自己稍微改改得到的代码如下:

PIL库：

只需要安装pillow库就行了。以下是终端安装代码：

pip install pillow

• 1

完整源码：

from PIL import Image, ImageDraw, ImageFont
import operator, bisect
def getChar(val):
    index = bisect.bisect_left(scores, val)
    if index > 0 and sorted_weights[index][1] + sorted_weights[index -
                                                               1][1] > 2 * val:
        index -= 1
    return sorted_weights[index][0]

def transform(image_file):
    image_file = image_file.convert("L")
    codePic = ""
    for h in range(image_file.size[1]):
        for w in range(image_file.size[0]):
            gray = image_file.getpixel((w, h))
            codePic += getChar(maximum * (1 - gray / 255))
        codePic += "
"
    return codePic


PictureName = input("请输入您要转换的照片名称：")
readinFilePath = f"{PictureName}"
outputTextFile = f"{PictureName}_ascii.txt"
outputImageFile = f"{PictureName}_ascii.jpg"
fnt = ImageFont.truetype("Courier New.ttf", 10)
chrx, chry = fnt.getsize(chr(32))
normalization = chrx * chry * 255
weights = {}

for i in range(32, 127):
    chrImage = fnt.getmask(chr(i))
    sizex, sizey = chrImage.size
    ctr = sum(
        chrImage.getpixel((x, y)) for y in range(sizey) for x in range(sizex))
    weights[chr(i)] = ctr / normalization
weights[chr(32)] = 0.01
weights.pop("_", None)
weights.pop("-", None)
sorted_weights = sorted(weights.items(), key=operator.itemgetter(1))
scores = [y for (x, y) in sorted_weights]
maximum = scores[-1]
base = Image.open(open(readinFilePath, "rb"))
resolution = 0.3
sizes = [resolution * i for i in (0.665, 0.3122