Ejemplo n.º 1
0
def cleanmosaic_video_byframe(opt,netG,netM):
    path = opt.media_path
    fps,imagepaths = video_init(opt,path)
    positions = []
    # get position
    for i,imagepath in enumerate(imagepaths,1):
        img_origin = impro.imread(os.path.join('./tmp/video2image',imagepath))
        x,y,size = runmodel.get_mosaic_position(img_origin,netM,opt)[:3]
        positions.append([x,y,size])
        print('\r','Find mosaic location:'+str(i)+'/'+str(len(imagepaths)),util.get_bar(100*i/len(imagepaths),num=40),end='')

    print('\nOptimize mosaic locations...')
    positions =np.array(positions)
    for i in range(3):positions[:,i] = filt.medfilt(positions[:,i],opt.medfilt_num)

    # clean mosaic
    for i,imagepath in enumerate(imagepaths,0):
        x,y,size = positions[i][0],positions[i][1],positions[i][2]
        img_origin = impro.imread(os.path.join('./tmp/video2image',imagepath))
        img_result = img_origin.copy()
        if size != 0:
            img_mosaic = img_origin[y-size:y+size,x-size:x+size]
            img_fake = runmodel.run_pix2pix(img_mosaic,netG,opt)
            img_result = impro.replace_mosaic(img_origin,img_fake,x,y,size,opt.no_feather)
        cv2.imwrite(os.path.join('./tmp/replace_mosaic',imagepath),img_result)
        print('\r','Clean Mosaic:'+str(i+1)+'/'+str(len(imagepaths)),util.get_bar(100*i/len(imagepaths),num=40),end='')
    print()
    ffmpeg.image2video( fps,
                './tmp/replace_mosaic/output_%05d.'+opt.tempimage_type,
                './tmp/voice_tmp.mp3',
                 os.path.join(opt.result_dir,os.path.splitext(os.path.basename(path))[0]+'_clean.mp4'))  
Ejemplo n.º 2
0
def get_mosaic_positions(opt, netM, imagepaths, savemask=True):
    # get mosaic position
    positions = []
    t1 = time.time()
    if not opt.no_preview:
        cv2.namedWindow('mosaic mask', cv2.WINDOW_NORMAL)
    print('Step:2/4 -- Find mosaic location')
    for i, imagepath in enumerate(imagepaths, 1):
        img_origin = impro.imread(
            os.path.join(opt.temp_dir + '/video2image', imagepath))
        x, y, size, mask = runmodel.get_mosaic_position(img_origin, netM, opt)
        positions.append([x, y, size])
        if savemask:
            cv2.imwrite(os.path.join(opt.temp_dir + '/mosaic_mask', imagepath),
                        mask)

        #preview result and print
        if not opt.no_preview:
            cv2.imshow('mosaic mask', mask)
            cv2.waitKey(1) & 0xFF
        t2 = time.time()
        print('\r',
              str(i) + '/' + str(len(imagepaths)),
              util.get_bar(100 * i / len(imagepaths), num=35),
              util.counttime(t1, t2, i, len(imagepaths)),
              end='')

    if not opt.no_preview:
        cv2.destroyAllWindows()
    print('\nOptimize mosaic locations...')
    positions = np.array(positions)
    for i in range(3):
        positions[:, i] = filt.medfilt(positions[:, i], opt.medfilt_num)

    return positions
Ejemplo n.º 3
0
def cleanmosaic_img_server(opt,img_origin,netG,netM):
    x,y,size,mask = runmodel.get_mosaic_position(img_origin,netM,opt)
    img_result = img_origin.copy()
    if size > 100 :
        img_mosaic = img_origin[y-size:y+size,x-size:x+size]
        if opt.traditional:
            img_fake = runmodel.traditional_cleaner(img_mosaic,opt)
        else:
            img_fake = runmodel.run_pix2pix(img_mosaic,netG,opt)
        img_result = impro.replace_mosaic(img_origin,img_fake,mask,x,y,size,opt.no_feather)
    return img_result
Ejemplo n.º 4
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def cleanmosaic_video_fusion(opt,netG,netM):
    path = opt.media_path
    N = 25
    INPUT_SIZE = 128
    fps,imagepaths = video_init(opt,path)
    positions = []
    # get position
    for i,imagepath in enumerate(imagepaths,1):
        img_origin = impro.imread(os.path.join('./tmp/video2image',imagepath))
        # x,y,size = runmodel.get_mosaic_position(img_origin,net_mosaic_pos,opt)[:3]
        x,y,size,mask = runmodel.get_mosaic_position(img_origin,netM,opt)
        cv2.imwrite(os.path.join('./tmp/mosaic_mask',imagepath), mask)
        positions.append([x,y,size])
        print('\r','Find mosaic location:'+str(i)+'/'+str(len(imagepaths)),util.get_bar(100*i/len(imagepaths),num=40),end='')
    print('\nOptimize mosaic locations...')
    positions =np.array(positions)
    for i in range(3):positions[:,i] = filt.medfilt(positions[:,i],opt.medfilt_num)

    # clean mosaic
    for i,imagepath in enumerate(imagepaths,0):
        x,y,size = positions[i][0],positions[i][1],positions[i][2]
        img_origin = impro.imread(os.path.join('./tmp/video2image',imagepath))
        mask = cv2.imread(os.path.join('./tmp/mosaic_mask',imagepath),0)
        
        if size==0:
            cv2.imwrite(os.path.join('./tmp/replace_mosaic',imagepath),img_origin)
        else:
            mosaic_input = np.zeros((INPUT_SIZE,INPUT_SIZE,3*N+1), dtype='uint8')
            for j in range(0,N):
                img = impro.imread(os.path.join('./tmp/video2image',imagepaths[np.clip(i+j-12,0,len(imagepaths)-1)]))
                img = img[y-size:y+size,x-size:x+size]
                img = impro.resize(img,INPUT_SIZE)
                mosaic_input[:,:,j*3:(j+1)*3] = img
            mask = impro.resize(mask,np.min(img_origin.shape[:2]))
            mask = mask[y-size:y+size,x-size:x+size]
            mask = impro.resize(mask, INPUT_SIZE)
            mosaic_input[:,:,-1] = mask
            mosaic_input = data.im2tensor(mosaic_input,bgr2rgb=False,use_gpu=opt.use_gpu,use_transform = False,is0_1 = False)
            unmosaic_pred = netG(mosaic_input)
            
            #unmosaic_pred = (unmosaic_pred.cpu().detach().numpy()*255)[0]
            #img_fake = unmosaic_pred.transpose((1, 2, 0))
            img_fake = data.tensor2im(unmosaic_pred,rgb2bgr = False ,is0_1 = False)
            img_result = impro.replace_mosaic(img_origin,img_fake,x,y,size,opt.no_feather)
            cv2.imwrite(os.path.join('./tmp/replace_mosaic',imagepath),img_result)
        print('\r','Clean Mosaic:'+str(i+1)+'/'+str(len(imagepaths)),util.get_bar(100*i/len(imagepaths),num=40),end='')
    print()
    ffmpeg.image2video( fps,
                './tmp/replace_mosaic/output_%05d.'+opt.tempimage_type,
                './tmp/voice_tmp.mp3',
                 os.path.join(opt.result_dir,os.path.splitext(os.path.basename(path))[0]+'_clean.mp4'))        
Ejemplo n.º 5
0
def get_mosaic_positions(opt,netM,imagepaths,savemask=True):
    # get mosaic position
    positions = []
    for i,imagepath in enumerate(imagepaths,1):
        img_origin = impro.imread(os.path.join('./tmp/video2image',imagepath))
        x,y,size,mask = runmodel.get_mosaic_position(img_origin,netM,opt)
        if savemask:
            cv2.imwrite(os.path.join('./tmp/mosaic_mask',imagepath), mask)
        positions.append([x,y,size])
        print('\r','Find mosaic location:'+str(i)+'/'+str(len(imagepaths)),util.get_bar(100*i/len(imagepaths),num=35),end='')
    print('\nOptimize mosaic locations...')
    positions =np.array(positions)
    for i in range(3):positions[:,i] = filt.medfilt(positions[:,i],opt.medfilt_num)
    return positions
Ejemplo n.º 6
0
def cleanmosaic_img(opt,netG,netM):

    path = opt.media_path
    print('Clean Mosaic:',path)
    img_origin = impro.imread(path)
    x,y,size,mask = runmodel.get_mosaic_position(img_origin,netM,opt)
    #cv2.imwrite('./mask/'+os.path.basename(path), mask)
    img_result = img_origin.copy()
    if size != 0 :
        img_mosaic = img_origin[y-size:y+size,x-size:x+size]
        img_fake = runmodel.run_pix2pix(img_mosaic,netG,opt)
        img_result = impro.replace_mosaic(img_origin,img_fake,x,y,size,opt.no_feather)
    else:
        print('Do not find mosaic')
    impro.imwrite(os.path.join(opt.result_dir,os.path.splitext(os.path.basename(path))[0]+'_clean.jpg'),img_result)
Ejemplo n.º 7
0
def cleanmosaic_video_byframe(opt):
    netG = loadmodel.pix2pix(opt)
    net_mosaic_pos = loadmodel.unet_clean(opt)
    path = opt.media_path
    util.clean_tempfiles()
    fps = ffmpeg.get_video_infos(path)[0]
    ffmpeg.video2voice(path, './tmp/voice_tmp.mp3')
    ffmpeg.video2image(path,
                       './tmp/video2image/output_%05d.' + opt.tempimage_type)
    positions = []
    imagepaths = os.listdir('./tmp/video2image')
    imagepaths.sort()

    # get position
    for imagepath in imagepaths:
        img_origin = impro.imread(os.path.join('./tmp/video2image', imagepath))
        x, y, size = runmodel.get_mosaic_position(img_origin, net_mosaic_pos,
                                                  opt)[:3]
        positions.append([x, y, size])
        print('Find mosaic location:', imagepath)
    print('Optimize mosaic locations...')
    positions = np.array(positions)
    for i in range(3):
        positions[:, i] = filt.medfilt(positions[:, i], opt.medfilt_num)

    # clean mosaic
    for i, imagepath in enumerate(imagepaths, 0):
        x, y, size = positions[i][0], positions[i][1], positions[i][2]
        img_origin = impro.imread(os.path.join('./tmp/video2image', imagepath))
        img_result = img_origin.copy()
        if size != 0:
            img_mosaic = img_origin[y - size:y + size, x - size:x + size]
            img_fake = runmodel.run_pix2pix(img_mosaic, netG, opt)
            img_result = impro.replace_mosaic(img_origin, img_fake, x, y, size,
                                              opt.no_feather)
        cv2.imwrite(os.path.join('./tmp/replace_mosaic', imagepath),
                    img_result)
        print('Clean Mosaic:', imagepath)
    ffmpeg.image2video(
        fps, './tmp/replace_mosaic/output_%05d.' + opt.tempimage_type,
        './tmp/voice_tmp.mp3',
        os.path.join(
            opt.result_dir,
            os.path.splitext(os.path.basename(path))[0] + '_clean.mp4'))
    ffmpeg.video2image(path,
                       './tmp/video2image/output_%05d.' + opt.tempimage_type)
    imagepaths = os.listdir('./tmp/video2image')
    imagepaths.sort()

    # get position
    positions = []
    img_ori_example = impro.imread(
        os.path.join('./tmp/video2image', imagepaths[0]))
    mask_avg = np.zeros((impro.resize(img_ori_example, 128)).shape[:2])
    for imagepath in imagepaths:
        imagepath = os.path.join('./tmp/video2image', imagepath)
        print('Find ROI location:', imagepath)
        img = impro.imread(imagepath)
        x, y, size, mask = runmodel.get_mosaic_position(img,
                                                        net,
                                                        opt,
                                                        threshold=64)
        cv2.imwrite(
            os.path.join('./tmp/ROI_mask', os.path.basename(imagepath)), mask)
        positions.append([x, y, size])
        mask_avg = mask_avg + mask
    print('Optimize ROI locations...')
    mask_index = filt.position_medfilt(np.array(positions), 13)

    mask = np.clip(mask_avg / len(imagepaths), 0, 255).astype('uint8')
    mask = impro.mask_threshold(mask, 20, 32)
    x, y, size, area = impro.boundingSquare(mask, Ex_mul=1.5)
    rat = min(img_ori_example.shape[:2]) / 128.0
    x, y, size = int(rat * x), int(rat * y), int(rat * size)
    cv2.imwrite(os.path.join('./tmp/ROI_mask_check', 'test_show.png'), mask)
    if size != 0:
Ejemplo n.º 9
0
def cleanmosaic_video_fusion(opt):
    net = loadmodel.pix2pix(opt)
    net_mosaic_pos = loadmodel.unet_clean(opt)
    path = opt.media_path
    N = 25

    util.clean_tempfiles()
    fps = ffmpeg.get_video_infos(path)[0]
    ffmpeg.video2voice(path, './tmp/voice_tmp.mp3')
    ffmpeg.video2image(path,
                       './tmp/video2image/output_%05d.' + opt.tempimage_type)
    positions = []
    imagepaths = os.listdir('./tmp/video2image')
    imagepaths.sort()

    # get position
    for imagepath in imagepaths:
        img_origin = impro.imread(os.path.join('./tmp/video2image', imagepath))
        # x,y,size = runmodel.get_mosaic_position(img_origin,net_mosaic_pos,opt)[:3]
        x, y, size, mask = runmodel.get_mosaic_position(
            img_origin, net_mosaic_pos, opt)
        cv2.imwrite(os.path.join('./tmp/mosaic_mask', imagepath), mask)
        positions.append([x, y, size])
        print('Find mosaic location:', imagepath)
    print('Optimize mosaic locations...')
    positions = np.array(positions)
    for i in range(3):
        positions[:, i] = filt.medfilt(positions[:, i], opt.medfilt_num)

    # clean mosaic
    print('Clean mosaic...')
    for i, imagepath in enumerate(imagepaths, 0):
        print('Clean mosaic:', imagepath)
        x, y, size = positions[i][0], positions[i][1], positions[i][2]
        img_origin = impro.imread(os.path.join('./tmp/video2image', imagepath))
        mask = cv2.imread(os.path.join('./tmp/mosaic_mask', imagepath), 0)

        if size == 0:
            cv2.imwrite(os.path.join('./tmp/replace_mosaic', imagepath),
                        img_origin)
        else:
            mosaic_input = np.zeros((256, 256, 3 * N + 1), dtype='uint8')
            for j in range(0, N):
                img = impro.imread(
                    os.path.join(
                        './tmp/video2image',
                        imagepaths[np.clip(i + j - 12, 0,
                                           len(imagepaths) - 1)]))
                img = img[y - size:y + size, x - size:x + size]
                img = impro.resize(img, 256)
                mosaic_input[:, :, j * 3:(j + 1) * 3] = img
            mask = impro.resize(mask, np.min(img_origin.shape[:2]))
            mask = mask[y - size:y + size, x - size:x + size]
            mask = impro.resize(mask, 256)
            mosaic_input[:, :, -1] = mask
            mosaic_input = data.im2tensor(mosaic_input,
                                          bgr2rgb=False,
                                          use_gpu=opt.use_gpu,
                                          use_transform=False)
            unmosaic_pred = net(mosaic_input)

            unmosaic_pred = (unmosaic_pred.cpu().detach().numpy() * 255)[0]
            img_fake = unmosaic_pred.transpose((1, 2, 0))
            img_result = impro.replace_mosaic(img_origin, img_fake, x, y, size,
                                              opt.no_feather)
            cv2.imwrite(os.path.join('./tmp/replace_mosaic', imagepath),
                        img_result)

    ffmpeg.image2video(
        fps, './tmp/replace_mosaic/output_%05d.' + opt.tempimage_type,
        './tmp/voice_tmp.mp3',
        os.path.join(
            opt.result_dir,
            os.path.splitext(os.path.basename(path))[0] + '_clean.mp4'))
Ejemplo n.º 10
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def main():
    if opt.mode == 'add':

        net = loadmodel.unet(opt)
        path = opt.media_path
        if util.is_img(path):
            print('Add Mosaic:', path)
            img = impro.imread(path)
            mask = runmodel.get_ROI_position(img, net, opt)[0]
            img = mosaic.addmosaic(img, mask, opt)
            cv2.imwrite(os.path.join(opt.result_dir, os.path.basename(path)),
                        img)
        elif util.is_video(path):
            util.clean_tempfiles()
            fps = ffmpeg.get_video_infos(path)[0]
            ffmpeg.video2voice(path, './tmp/voice_tmp.mp3')
            ffmpeg.video2image(
                path, './tmp/video2image/output_%05d.' + opt.tempimage_type)
            imagepaths = os.listdir('./tmp/video2image')
            imagepaths.sort()

            # get position
            positions = []
            for imagepath in imagepaths:
                imagepath = os.path.join('./tmp/video2image', imagepath)
                print('Find ROI location:', imagepath)
                img = impro.imread(imagepath)
                mask, x, y, area = runmodel.get_ROI_position(img, net, opt)
                positions.append([x, y, area])
                cv2.imwrite(
                    os.path.join('./tmp/ROI_mask',
                                 os.path.basename(imagepath)), mask)
            print('Optimize ROI locations...')
            mask_index = filt.position_medfilt(np.array(positions), 7)

            # add mosaic
            print('Add mosaic to images...')
            for i in range(len(imagepaths)):
                mask_path = os.path.join('./tmp/ROI_mask',
                                         imagepaths[mask_index[i]])
                mask = impro.imread(mask_path)
                img = impro.imread(
                    os.path.join('./tmp/video2image', imagepaths[i]))
                img = mosaic.addmosaic(img, mask, opt)
                cv2.imwrite(
                    os.path.join('./tmp/addmosaic_image',
                                 os.path.basename(imagepaths[i])), img)

            ffmpeg.image2video(
                fps, './tmp/addmosaic_image/output_%05d.' + opt.tempimage_type,
                './tmp/voice_tmp.mp3',
                os.path.join(
                    opt.result_dir,
                    os.path.splitext(os.path.basename(path))[0] + '_add.mp4'))

    elif opt.mode == 'clean':
        netG = loadmodel.pix2pix(opt)
        net_mosaic_pos = loadmodel.unet_clean(opt)
        path = opt.media_path
        if util.is_img(path):
            print('Clean Mosaic:', path)
            img_origin = impro.imread(path)
            x, y, size = runmodel.get_mosaic_position(img_origin,
                                                      net_mosaic_pos, opt)
            img_result = img_origin.copy()
            if size != 0:
                img_mosaic = img_origin[y - size:y + size, x - size:x + size]
                img_fake = runmodel.run_pix2pix(img_mosaic, netG, opt)
                img_result = impro.replace_mosaic(img_origin, img_fake, x, y,
                                                  size, opt.no_feather)
            cv2.imwrite(os.path.join(opt.result_dir, os.path.basename(path)),
                        img_result)

        elif util.is_video(path):
            util.clean_tempfiles()
            fps = ffmpeg.get_video_infos(path)[0]
            ffmpeg.video2voice(path, './tmp/voice_tmp.mp3')
            ffmpeg.video2image(
                path, './tmp/video2image/output_%05d.' + opt.tempimage_type)
            positions = []
            imagepaths = os.listdir('./tmp/video2image')
            imagepaths.sort()

            # get position
            for imagepath in imagepaths:
                imagepath = os.path.join('./tmp/video2image', imagepath)
                img_origin = impro.imread(imagepath)
                x, y, size = runmodel.get_mosaic_position(
                    img_origin, net_mosaic_pos, opt)
                positions.append([x, y, size])
                print('Find mosaic location:', imagepath)
            print('Optimize mosaic locations...')
            positions = np.array(positions)
            for i in range(3):
                positions[:, i] = filt.medfilt(positions[:, i],
                                               opt.medfilt_num)

            # clean mosaic
            for i, imagepath in enumerate(imagepaths, 0):
                imagepath = os.path.join('./tmp/video2image', imagepath)
                x, y, size = positions[i][0], positions[i][1], positions[i][2]
                img_origin = impro.imread(imagepath)
                img_result = img_origin.copy()
                if size != 0:
                    img_mosaic = img_origin[y - size:y + size,
                                            x - size:x + size]
                    img_fake = runmodel.run_pix2pix(img_mosaic, netG, opt)
                    img_result = impro.replace_mosaic(img_origin, img_fake, x,
                                                      y, size, opt.no_feather)
                cv2.imwrite(
                    os.path.join('./tmp/replace_mosaic',
                                 os.path.basename(imagepath)), img_result)
                print('Clean Mosaic:', imagepath)
            ffmpeg.image2video(
                fps, './tmp/replace_mosaic/output_%05d.' + opt.tempimage_type,
                './tmp/voice_tmp.mp3',
                os.path.join(
                    opt.result_dir,
                    os.path.splitext(os.path.basename(path))[0] +
                    '_clean.mp4'))
    util.clean_tempfiles(tmp_init=False)
Ejemplo n.º 11
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def get_mosaic_positions(opt, netM, imagepaths, savemask=True):
    # resume
    continue_flag = False
    if os.path.isfile(os.path.join(opt.temp_dir, 'step.json')):
        step = util.loadjson(os.path.join(opt.temp_dir, 'step.json'))
        resume_frame = int(step['frame'])
        if int(step['step']) > 2:
            pre_positions = np.load(
                os.path.join(opt.temp_dir, 'mosaic_positions.npy'))
            return pre_positions
        if int(step['step']) >= 2 and resume_frame > 0:
            pre_positions = np.load(
                os.path.join(opt.temp_dir, 'mosaic_positions.npy'))
            continue_flag = True
            imagepaths = imagepaths[resume_frame:]

    positions = []
    t1 = time.time()
    if not opt.no_preview:
        cv2.namedWindow('mosaic mask', cv2.WINDOW_NORMAL)
    print('Step:2/4 -- Find mosaic location')

    img_read_pool = Queue(4)

    def loader(imagepaths):
        for imagepath in imagepaths:
            img_origin = impro.imread(
                os.path.join(opt.temp_dir + '/video2image', imagepath))
            img_read_pool.put(img_origin)

    t = Thread(target=loader, args=(imagepaths, ))
    t.setDaemon(True)
    t.start()

    for i, imagepath in enumerate(imagepaths, 1):
        img_origin = img_read_pool.get()
        x, y, size, mask = runmodel.get_mosaic_position(img_origin, netM, opt)
        positions.append([x, y, size])
        if savemask:
            t = Thread(target=cv2.imwrite,
                       args=(
                           os.path.join(opt.temp_dir + '/mosaic_mask',
                                        imagepath),
                           mask,
                       ))
            t.start()
        if i % 1000 == 0:
            save_positions = np.array(positions)
            if continue_flag:
                save_positions = np.concatenate(
                    (pre_positions, save_positions), axis=0)
            np.save(os.path.join(opt.temp_dir, 'mosaic_positions.npy'),
                    save_positions)
            step = {'step': 2, 'frame': i + resume_frame}
            util.savejson(os.path.join(opt.temp_dir, 'step.json'), step)

        #preview result and print
        if not opt.no_preview:
            cv2.imshow('mosaic mask', mask)
            cv2.waitKey(1) & 0xFF
        t2 = time.time()
        print('\r',
              str(i) + '/' + str(len(imagepaths)),
              util.get_bar(100 * i / len(imagepaths), num=35),
              util.counttime(t1, t2, i, len(imagepaths)),
              end='')

    if not opt.no_preview:
        cv2.destroyAllWindows()
    print('\nOptimize mosaic locations...')
    positions = np.array(positions)
    if continue_flag:
        positions = np.concatenate((pre_positions, positions), axis=0)
    for i in range(3):
        positions[:, i] = filt.medfilt(positions[:, i], opt.medfilt_num)
    step = {'step': 3, 'frame': 0}
    util.savejson(os.path.join(opt.temp_dir, 'step.json'), step)
    np.save(os.path.join(opt.temp_dir, 'mosaic_positions.npy'), positions)

    return positions
Ejemplo n.º 12
0
        ffmpeg.image2video(
            fps, './tmp/addmosaic_image/output_%05d.' + opt.tempimage_type,
            './tmp/voice_tmp.mp3',
            os.path.join(
                opt.result_dir,
                os.path.splitext(os.path.basename(path))[0] + '_add.mp4'))

elif opt.mode == 'clean':
    netG = loadmodel.pix2pix(opt)
    net_mosaic_pos = loadmodel.unet_clean(opt)
    path = opt.media_path
    if util.is_img(path):
        print('Clean Mosaic:', path)
        img_origin = impro.imread(path)
        x, y, size = runmodel.get_mosaic_position(img_origin, net_mosaic_pos,
                                                  opt)
        img_result = img_origin.copy()
        if size != 0:
            img_mosaic = img_origin[y - size:y + size, x - size:x + size]
            img_fake = runmodel.run_pix2pix(img_mosaic,
                                            netG,
                                            use_gpu=opt.use_gpu)
            img_result = impro.replace_mosaic(img_origin, img_fake, x, y, size,
                                              opt.no_feather)
        cv2.imwrite(os.path.join(opt.result_dir, os.path.basename(path)),
                    img_result)

    elif util.is_video(path):
        util.clean_tempfiles()
        fps = ffmpeg.get_video_infos(path)[0]
        ffmpeg.video2voice(path, './tmp/voice_tmp.mp3')