pip install Image argparse pillow

from PIL import Image
import argparse

#命令行输入参数处理
parser = argparse.ArgumentParser()
parser.add_argument('file')                                 #输入文件
parser.add_argument('-o', '--output')                       #输出文件
parser.add_argument('--width', type = int, default = 80)    #输出字符画宽
parser.add_argument('--height', type = int, default = 80)   #输出字符画高
args = parser.parse_args()                                  # 获取参数

IMG = args.file
WIDTH = args.width
HEIGHT = args.height
OUTPUT = args.output

# 我们定义的不重复的字符列表，灰度值小（暗）的用列表开头的符号，灰度值大（亮）的用列表末尾的符号
ascii_char = list("$@B%8&WM#*oahkbdpqwmZO0QLCJUYXzcvunxrjft/\|()1{}[]?-_+~<>i!lI;:,\"^`'. ")

# 将256灰度映射到70个字符上
def get_char(r,g,b,alpha = 256):
    if alpha == 0:
        return ' '
    length = len(ascii_char)
    gray = int(0.2126 * r + 0.7152 * g + 0.0722 * b)

    unit = (256.0 + 1)/length
    return ascii_char[int(gray/unit)]

if __name__ == '__main__':

    im = Image.open(IMG)
    im = im.resize((WIDTH,HEIGHT), Image.NEAREST)

    txt = ""

    #将图片看成由像素点组成的二维数组，i代表每一行，j代表每一列
    for i in range(HEIGHT):
        for j in range(WIDTH):
            #getpixel()函数的参数是由每个像素点在图片中的相对位置（w，h）组成的元组
            #返回值是一个代表图片像素值的(r,g,b,alpha)元组
            txt += get_char(*im.getpixel((j,i)))
        txt += '\n'

    print(txt)
    #字符画输出到文件
    if OUTPUT:
        with open(OUTPUT,'w') as f:
            f.write(txt)
    else:
        with open("output.txt",'w') as f:
            f.write(txt)

python .\a.py .\time.jpg -o teaGod.txt --width 80 --height 40

 

 

 

 

转成视频图

import cv2
import os
show_heigth = 30              
show_width = 80

ascii_char = list("$@B%8&WM#*oahkbdpqwmZO0QLCJUYXzcvunxrjft/\|()1{}[]?-_+~<>i!lI;:,\"^`'. ")
#生成一个ascii字符列表
char_len = len(ascii_char)

vc = cv2.VideoCapture("v.mkv")          #加载一个视频

if vc.isOpened():                       #判断是否正常打开
    rval , frame = vc.read()
else:
    rval = False
    
frame_count = 0
outputList = []                         #初始化输出列表
while rval:   #循环读取视频帧  
    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)  #使用opencv转化成灰度图
    gray = cv2.resize(gray,(show_width,show_heigth))#resize灰度图
    text = ""
    for pixel_line in gray:
        for pixel in pixel_line:                    #字符串拼接
            text += ascii_char[int(pixel / 256 * char_len )]
        text += "\n"                                
    outputList.append(text)
    frame_count = frame_count + 1                           
    if frame_count % 100 == 0:
        print("已处理" + str(frame_count) + "帧")
    rval, frame = vc.read()  
print("处理完毕")

for frame in outputList:            
    os.system("cls")                    #清屏
    print(frame)
    print()
    print()