Esempio n. 1
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def main():

    if os.path.isdir(opt.media_path):
        files = util.Traversal(opt.media_path)
    else:
        files = [opt.media_path]
    if opt.mode == 'add':
        netS = loadmodel.bisenet(opt, 'roi')
        for file in files:
            opt.media_path = file
            if util.is_img(file):
                core.addmosaic_img(opt, netS)
            elif util.is_video(file):
                core.addmosaic_video(opt, netS)
                util.clean_tempfiles(opt, tmp_init=False)
            else:
                print('This type of file is not supported')
            util.clean_tempfiles(opt, tmp_init=False)

    elif opt.mode == 'clean':
        netM = loadmodel.bisenet(opt, 'mosaic')
        if opt.traditional:
            netG = None
        elif opt.netG == 'video':
            netG = loadmodel.video(opt)
        else:
            netG = loadmodel.pix2pix(opt)

        for file in files:
            opt.media_path = file
            if util.is_img(file):
                core.cleanmosaic_img(opt, netG, netM)
            elif util.is_video(file):
                if opt.netG == 'video' and not opt.traditional:
                    core.cleanmosaic_video_fusion(opt, netG, netM)
                else:
                    core.cleanmosaic_video_byframe(opt, netG, netM)
                util.clean_tempfiles(opt, tmp_init=False)
            else:
                print('This type of file is not supported')

    elif opt.mode == 'style':
        netG = loadmodel.style(opt)
        for file in files:
            opt.media_path = file
            if util.is_img(file):
                core.styletransfer_img(opt, netG)
            elif util.is_video(file):
                core.styletransfer_video(opt, netG)
                util.clean_tempfiles(opt, tmp_init=False)
            else:
                print('This type of file is not supported')

    util.clean_tempfiles(opt, tmp_init=False)
Esempio n. 2
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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'))
Esempio n. 3
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def cleanmosaic_img(opt):
    netG = loadmodel.pix2pix(opt)
    net_mosaic_pos = loadmodel.unet_clean(opt)
    path = opt.media_path
    print('Clean Mosaic:', path)
    img_origin = impro.imread(path)
    x, y, size = runmodel.get_mosaic_position(img_origin, net_mosaic_pos,
                                              opt)[:3]
    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')
    cv2.imwrite(
        os.path.join(
            opt.result_dir,
            os.path.splitext(os.path.basename(path))[0] + '_clean.jpg'),
        img_result)
Esempio n. 4
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        mask = np.zeros(img_origin.shape, dtype='uint8')
        mask = cv2.rectangle(mask, (x - size + entad, y - size + entad),
                             (x + size - entad, y + size - entad),
                             (255, 255, 255), -1)
        mask = (cv2.blur(mask, (eclosion_num, eclosion_num)))
        mask = mask / 255.0

        img_tmp = np.zeros(img_origin.shape)
        img_tmp[y - size:y + size, x - size:x + size] = img_fake
        img_result = img_origin.copy()
        img_result = (img_origin * (1 - mask) + img_tmp * mask).astype('uint8')
    return img_result


netG = loadmodel.pix2pix(os.path.join(opt.model_dir, opt.model_name),
                         opt.model_type_netG,
                         use_gpu=opt.use_gpu)
net_mosaic_pos = loadmodel.unet(os.path.join(opt.model_dir,
                                             opt.mosaic_position_model_name),
                                use_gpu=opt.use_gpu)

filepaths = util.Traversal(opt.input_dir)

for path in filepaths:
    if util.is_img(path):
        print('Clean Mosaic:', path)
        img_origin = cv2.imread(path)
        x, y, size = get_mosaic_position(img_origin)
        img_result = img_origin.copy()
        if size != 0:
            img_mosaic = img_origin[y - size:y + size, x - size:x + size]
Esempio n. 5
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try:
    from cores import Options, core
    from util import util
    from util import image_processing as impro
    from models import loadmodel
except Exception as e:
    print(e)
    input('Please press any key to exit.\n')
    sys.exit(0)

# python server.py --gpu_id 0 --model_path ./pretrained_models/mosaic/clean_face_HD.pth
opt = Options()
opt.parser.add_argument('--port', type=int, default=4000, help='')
opt = opt.getparse(True)
netM = loadmodel.bisenet(opt, 'mosaic')
netG = loadmodel.pix2pix(opt)

from flask import Flask, request
import base64
import shutil

app = Flask(__name__)


@app.route("/handle", methods=["POST"])
def handle():
    result = {}
    # to opencv img
    try:
        imgRec = request.form['img']
        imgByte = base64.b64decode(imgRec)
Esempio n. 6
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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'))
Esempio n. 7
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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)