数字文创：冰冰老婆带你去旅游---基于paddlehub的人像分割与视频合成

!pip install -U paddlehub -i https://pypi.tuna.tsinghua.edu.cn/simple

import numpy as npimport matplotlib.image as mpimgimport matplotlib.pyplot as pltimport osfrom PIL import Imageimport paddlehub as hubimport cv2from moviepy.editor import VideoFileClipimport shutil

os.environ["CUDA_VISIBLE_DEVICES"]="0"#GPU模式

#背景视频转jpgdef video_to_pic():
    if os.path.exists('./background_pic'):
        shutil.rmtree('./background_pic')#删除文件夹以及文件       
    os.mkdir('./background_pic')#创建文件夹
    index = 0
    cap = cv2.VideoCapture('./background.mp4')
    ret,frame = cap.read()    while ret:
        cv2.imwrite('./background_pic/%d.jpg'%index, frame)
        index += 1
        ret,frame = cap.read()
    cap.release()    print('Video cut finish, all %d frame' % index)
video_to_pic()

#人像视频转jpgdef video_to_pic():
    if os.path.exists('./video_pic'):
        shutil.rmtree('./video_pic')#删除文件夹以及文件       
    os.mkdir('./video_pic')#创建文件夹
    index = 0
    cap = cv2.VideoCapture('./xxm.mp4')
    ret,frame = cap.read()    while ret:
        cv2.imwrite('./video_pic/%d.jpg'%index, frame)
        index += 1
        ret,frame = cap.read()
    cap.release()    print('Video cut finish, all %d frame' % index)
video_to_pic()

#图片平移def tl(img_path):
    '''x轴平移输出两张jpg图片,dest1,dest2'''
    img = cv2.imread(img_path)
    rows,cols, channel = img.shape# 平移矩阵M：[[1,0,x],[0,1,y]]
    M1 = np.float32([[1,0,400],[0,1,0]])    #M2 = np.float32([[1,0,-400],[0,1,0]])
    dest1 = cv2.warpAffine(img,M1,(cols,rows), borderValue=(255, 255, 255))#仿射平移
    #dest2 = cv2.warpAffine(img,M2,(cols,rows), borderValue=(255, 255, 255))
    
    cv2.imwrite('./dest1'+'/'+file,dest1)#保存图片
   # cv2.imwrite('./dest2'+'/'+file,dest2)
    # print('保存平移图片成功')

#保存平移后的图片（背景）#filename_list = os.listdir('background_pic')#if os.path.exists('dest2'):#    shutil.rmtree('dest2')#os.mkdir('dest2')#for file in filename_list:#    tl('./background_pic'+'/'+file)#print("文件已创建")

#保存平移后的图片(人像)filename_list = os.listdir('video_pic')if os.path.exists('dest1'):
    shutil.rmtree('dest1')
os.mkdir('dest1')for file in filename_list:
    tl('./video_pic'+'/'+file)print("文件已创建")

#扣出平移后图片中的人像def seg_pic(path,savepath):
    i = 0
    module= hub.Module(name="deeplabv3p_xception65_humanseg")
    pic_path = path    if os.path.exists(savepath):
        shutil.rmtree(savepath)
    os.mkdir(savepath)
    
    filename_list = os.listdir(pic_path)
    filename_list.sort(key=lambda x: int(x[:-4]))#图片排序
    
    for fname in filename_list:
        result = module.segmentation(images=[cv2.imread(pic_path+'/'+fname)], visualization=True, output_dir=savepath,use_gpu=True)        #print('已处理处理',pic_path,'图片：', i)
        i+=1
    
    filename_list = os.listdir(savepath)
    filename_list.sort()
    i=0
    for file in filename_list:
        os.rename(savepath+'/'+file,savepath+'/'+str(i)+'.jpg')#（修改前目录名，修改后名）
        i+=1
    print('抠图完成')#左边原图路径，右边抠图输出路径seg_pic('dest1','res_dest1')#seg_pic('dest2','res_dest2')

#将扣出的人像与原图合并def blend_images(fore_path, base_path ,savepath):
    """
    将抠出的人物图像换背景
    fore_image: 前景图片，抠出的人物图片
    base_image: 背景图片
    """
    filename_list = os.listdir(fore_path)    for fname in filename_list:
        fore_image = fore_path + '/' + fname 
        base_image = base_path + '/' + fname    # 读入图片
        base_image = Image.open(base_image).convert('RGB')
        fore_image = Image.open(fore_image).resize(base_image.size)    # 图片加权合成
        scope_map = np.array(fore_image)[:,:,-1] / 255
        scope_map = scope_map[:,:,np.newaxis]
        scope_map = np.repeat(scope_map, repeats=3, axis=2)
        res_image = np.multiply(scope_map, np.array(fore_image)[:,:,:3]) + np.multiply((1-scope_map), np.array(base_image))    
    #保存图片
        res_image = Image.fromarray(np.uint8(res_image))
        res_image.save(savepath + '/' + fname)

savepath = 'result_picture'if os.path.exists(savepath):
    shutil.rmtree(savepath)
os.mkdir(savepath) 
blend_images('res_dest1', 'background_pic', savepath)#删除多余文件以免混淆shutil.rmtree('dest1')#shutil.rmtree('dest2')shutil.rmtree('res_dest1')#shutil.rmtree('res_dest2')print("图片成功合成")

#图片变视频加配乐def merge_to_mp4():
    fourcc = cv2.VideoWriter_fourcc(*'mp4v')
    video= cv2.VideoCapture('./background.mp4')
    fps = video.get(cv2.CAP_PROP_FPS)
    img = Image.open('./result_picture/1.jpg')#需要整合成视频的图片路径
    out = cv2.VideoWriter('result.mp4', fourcc, fps, (img.size[0], img.size[1]))
    files = os.listdir('./result_picture')
    files.sort(key=lambda x: int(x[:-4]))    for i in files:
        img = cv2.imread('./result_picture/'+i)
        out.write(img)#保存帧
    out.release()    print('ok!')def add_audio():
    video_origin = VideoFileClip('xxm.mp4')
    audio=video_origin.audio
    video_result = VideoFileClip('./result.mp4')
    video_result = video_result.set_audio(audio)
    video_result.write_videofile('成品.mp4')    
    print('ok!')

merge_to_mp4()
add_audio()