Opencv realizes grayscale, inversion, edge detection and export of multiple sets of moving pictures

1. Original image

Two, python program

import cv2
import imageio
import numpy as np
from PIL import Image
import matplotlib.pyplot as plt
import matplotlib.animation as amt

gif=imageio.mimread('under one person.gif')# 仅支持英文路径

plt.ion()
fig,ax=plt.subplots(3,2)

def graph(img):
    f1=ax[0,0].imshow(img)
    ax[0,0].set_title('Original Image'),ax[0,0].set_xticks([]),ax[0,0].set_yticks([])

    img2=cv2.cvtColor(img,cv2.COLOR_RGB2BGR)
    f2=ax[0,1].imshow(img2)
    ax[0,1].set_title('RGB_to_BGR Image'),ax[0,1].set_xticks([]),ax[0,1].set_yticks([])

    img3=cv2.cvtColor(img2,cv2.COLOR_BGR2GRAY)
    f3=ax[1,0].imshow(img3)
    ax[1,0].set_title('BGR_to_Gray Image'),ax[1,0].set_xticks([]),ax[1,0].set_yticks([])

    matrix=np.asarray(img2)
    matrix=255-matrix
    img4=Image.fromarray(matrix)
    f4=ax[1,1].imshow(img4)
    ax[1,1].set_title('Reversed BGR Image'),ax[1,1].set_xticks([]),ax[1,1].set_yticks([])

    edges=cv2.Canny(img2,50,200)
    f5=ax[2,0].imshow(edges,cmap='gray')
    ax[2,0].set_title('Edge Image'),ax[2,0].set_xticks([]),ax[2,0].set_yticks([])

    matrix2=np.asarray(edges)
    matrix2=255-matrix2
    edges2=Image.fromarray(matrix2)
    f6=ax[2,1].imshow(edges2,cmap='gray')
    ax[2,1].set_title('Reversed Edge Image'),ax[2,1].set_xticks([]),ax[2,1].set_yticks([])

    plt.pause(0.01)
    return f1,f2,f3,f4,f5,f6

artists=[]
for img in gif:
    g=graph(img)
    artists.append(g)

plt.ioff()
plt.show()
amt.ArtistAnimation(fig=fig,artists=artists).save('动图.gif',writer='pillow',fps=60,dpi=100)# fps：每秒帧数，dpi：每英寸像素点

3. Effect display