基于paddlehub2.4.0: 让动态视频生成漫画书！【一键运行】

# 安装 paddlehub!pip install paddlehub
!hub install stylepro_artistic

%%capture
!unzip  /home/aistudio/data/data93870/index.zip -d /home/aistudio/work/style

#定义函数计算单通道的直方图的相似值，越小差异越大def calculate_delta(image1=False, image2=False):
    if type(image1)!=type(image2) :
        degree = [1e-10]    else:        # 灰度直方图算法
        # 计算单通道的直方图的相似值
        hist1 = cv2.calcHist([image1], [0], None, [256], [0.0, 255.0])
        hist2 = cv2.calcHist([image2], [0], None, [256], [0.0, 255.0])        # 计算直方图的重合度
        degree = 0
        for i in range(len(hist1)):            if hist1[i] != hist2[i]:
                degree = degree + \
                    (1 - abs(hist1[i] - hist2[i]) / max(hist1[i], hist2[i]))            else:
                degree = degree + 1
        degree = degree / len(hist1)        while type(degree)==type([]):
            degree=degree[0]
        degree=[degree]    return degree

plt.subplot(1, 4, 1) 
img1 = load_comic_photo('/home/aistudio/work/style/06/0012.png')
plt.imshow(  cv2.cvtColor( img1 ,cv2.COLOR_BGR2RGB) )
plt.axis('off')
plt.subplot(1, 4, 2)  
img2 = load_comic_photo('/home/aistudio/work/style/05/0013.png')
plt.imshow(  cv2.cvtColor( img2 ,cv2.COLOR_BGR2RGB) )
plt.axis('off')
plt.subplot(1, 4, 3)  
img3 = load_comic_photo('/home/aistudio/work/style/05/0014.png')
plt.imshow(  cv2.cvtColor( img3 ,cv2.COLOR_BGR2RGB) )
plt.axis('off')
plt.subplot(1, 4, 4)  
img4 = load_comic_photo('/home/aistudio/work/style/05/0015.png')
plt.imshow(  cv2.cvtColor( img4 ,cv2.COLOR_BGR2RGB) )
plt.axis('off')
plt.tight_layout()  # 自动调整子图参数  plt.show()

import paddlehub as hub#图片转为漫画stylepro_artistic = hub.Module(name="stylepro_artistic") #加载预训练模型def get_cartoon_img(src_img_data):
    result = stylepro_artistic.style_transfer(
        images=[{            'content': src_img_data ,            'styles': [load_comic_photo('/home/aistudio/work/style/05/0013.png')
                ,load_comic_photo('/home/aistudio/work/style/07/0015.png')
            ]
        }]
        )
    t = result[0]['data']
    t = cv2.cvtColor( t,cv2.COLOR_RGB2GRAY) # 先要转换为灰度图片
    t = cv2.medianBlur(t,3)    return t

## 将视频转换为图片,抽取关键帧import osimport cv2#显示图片def showimg(img, isgray=False):
  plt.axis("off")  if isgray == True:
    plt.imshow(img, cmap='gray')  else: 
    plt.imshow(img)
  plt.show()def get_video_key_frame(video_src,frame_path='',show_key_frame=False,show_comic_key_frame=False):
    if frame_path and not os.path.exists(frame_path):
        os.mkdir(frame_path)    if frame_path and not os.path.exists(frame_path+'results/'):
        frame_path_ = frame_path+'results/'
        os.mkdir(frame_path_)
    vc = cv2.VideoCapture(video_src)
    i_imp =-1000 #上一次保存的帧号
    (frame_last,delta_last) =(False,0)#上一帧图、上一帧的差异指数
    if vc.isOpened():
        rval, frame = vc.read()    else:
        rval = False

    i = 0 #当前帧号
    while rval:
        rval, frame = vc.read()        if  rval:
            delta = calculate_delta(frame_last, frame )[0] # 计算差异程度
            pct = abs(delta - delta_last)/(delta+0.000001) #差异程度的变化量
            if pct>0.2 and i-i_imp>10: #差异程度变化很大，且间隔半秒以上
                if show_key_frame:                    None
                if frame_path:
                    cv2.imwrite(frame_path+'img_{}.jpg'.format(i), frame)                if show_comic_key_frame:
                    frame_cartoon = get_cartoon_img(frame)                    if frame_path:
                        cv2.imwrite(frame_path+'results/'+'img_{}.jpg'.format(i), frame_cartoon)
                i_imp = i
            (frame_last,delta_last) = ( frame , delta )
            i += 1

video = 'work/shipin.mp4'frame_path = 'work/mov/picture/'# 抽取关键帧get_video_key_frame(video,frame_path,show_key_frame=True,show_comic_key_frame=False)# 关键帧转为漫画get_video_key_frame(video,frame_path,show_key_frame=False,show_comic_key_frame=True)

!mv /home/aistudio/work/mov/picture/results /home/aistudio/work/movdef sort_images(img_folder):  
    """按文件名中的数字排序图片"""  
    # 使用glob匹配所有jpg图片  
    img_paths = [os.path.join(img_folder, img) for img in os.listdir(img_folder) if img.endswith('.jpg')]  
    # 按文件名中的数字排序  
    img_paths.sort(key=lambda x: int(os.path.splitext(os.path.basename(x))[0].split('_')[1]))  
    return img_paths  


img_list_1 = sort_images("/home/aistudio/work/mov/picture")
img_list_2 = sort_images("/home/aistudio/work/mov/results")print("img_list_1:",img_list_1)print("img_list_2:",img_list_2)

import cv2  
import matplotlib.pyplot as plt  

for i in range(len(img_list_1)):    # 读取图片  
    image1 = cv2.imread(img_list_1[i])  # 替换为你的图片路径  
    image2 = cv2.imread(img_list_2[i])  # 替换为你的图片路径  
    
    image1_rgb = cv2.cvtColor(image1, cv2.COLOR_BGR2RGB)  
    image2_rgb = cv2.cvtColor(image2, cv2.COLOR_BGR2RGB)  
    
    # 使用matplotlib显示图片  
    fig, axes = plt.subplots(1, 2, figsize=(10, 5))  # 创建一个1行2列的图形  

    axes[0].imshow(image1_rgb)  # 显示第一张图片  
    axes[0].axis('off')  # 关闭坐标轴  
    
    axes[1].imshow(image2_rgb)  # 显示第二张图片  
    axes[1].axis('off')  # 关闭坐标轴  
    plt.show()