def addmosaic_video(opt,netS):
path = opt.media_path
fps,imagepaths = video_init(opt,path)
# get position
positions = []
for i,imagepath in enumerate(imagepaths,1):
img = impro.imread(os.path.join('./tmp/video2image',imagepath))
mask,x,y,area = runmodel.get_ROI_position(img,netS,opt)
positions.append([x,y,area])
cv2.imwrite(os.path.join('./tmp/ROI_mask',imagepath),mask)
print('\r','Find ROI location:'+str(i)+'/'+str(len(imagepaths)),util.get_bar(100*i/len(imagepaths),num=40),end='')
print('\nOptimize ROI locations...')
mask_index = filt.position_medfilt(np.array(positions), 7)
# add mosaic
for i in range(len(imagepaths)):
mask = impro.imread(os.path.join('./tmp/ROI_mask',imagepaths[mask_index[i]]),'gray')
img = impro.imread(os.path.join('./tmp/video2image',imagepaths[i]))
if impro.mask_area(mask)>100:
img = mosaic.addmosaic(img, mask, opt)
cv2.imwrite(os.path.join('./tmp/addmosaic_image',imagepaths[i]),img)
print('\r','Add Mosaic:'+str(i+1)+'/'+str(len(imagepaths)),util.get_bar(100*i/len(imagepaths),num=40),end='')
print()
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'))
def addmosaic_img(opt,netS):
path = opt.media_path
print('Add Mosaic:',path)
img = impro.imread(path)
mask = runmodel.get_ROI_position(img,netS,opt)[0]
img = mosaic.addmosaic(img,mask,opt)
impro.imwrite(os.path.join(opt.result_dir,os.path.splitext(os.path.basename(path))[0]+'_add.jpg'),img)
def addmosaic_video(opt):
net = loadmodel.unet(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)
imagepaths = os.listdir('./tmp/video2image')
imagepaths.sort()
# get position
positions = []
for imagepath in imagepaths:
print('Find ROI location:', imagepath)
img = impro.imread(os.path.join('./tmp/video2image', 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', 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 = impro.imread(
os.path.join('./tmp/ROI_mask', imagepaths[mask_index[i]]))
img = impro.imread(os.path.join('./tmp/video2image', imagepaths[i]))
img = mosaic.addmosaic(img, mask, opt)
cv2.imwrite(os.path.join('./tmp/addmosaic_image', 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'))
for cut_point in range(1, int(
(endtime - opt.time) / opt.interval)):
util.clean_tempfiles(opt)
ffmpeg.video2image(
videopath,
opt.temp_dir + '/video2image/%05d.' + opt.tempimage_type,
fps=1,
start_time=util.second2stamp(cut_point * opt.interval),
last_time=util.second2stamp(opt.time))
imagepaths = util.Traversal(opt.temp_dir + '/video2image')
imagepaths = sorted(imagepaths)
cnt = 0
for i in range(opt.time):
img = impro.imread(imagepaths[i])
mask = runmodel.get_ROI_position(img,
net,
opt,
keepsize=True)[0]
if not opt.all_mosaic_area:
mask = impro.find_mostlikely_ROI(mask)
x, y, size, area = impro.boundingSquare(mask, Ex_mul=1)
if area > opt.minmaskarea and size > opt.minsize and impro.Q_lapulase(
img) > opt.quality:
cnt += 1
if cnt == opt.time:
# print(second)
timestamps.append(
util.second2stamp(cut_point * opt.interval))
util.writelog(os.path.join(opt.savedir, 'opt.txt'),
videopath + '\n' + str(timestamps))
#print(timestamps)
def get_roi_positions(opt, netS, 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:
mask_index = np.load(os.path.join(opt.temp_dir, 'mask_index.npy'))
return mask_index
if int(step['step']) >= 2 and resume_frame > 0:
pre_positions = np.load(
os.path.join(opt.temp_dir, 'roi_positions.npy'))
continue_flag = True
imagepaths = imagepaths[resume_frame:]
positions = []
t1 = time.time()
if not opt.no_preview:
cv2.namedWindow('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.daemon = True
t.start()
for i, imagepath in enumerate(imagepaths, 1):
img_origin = img_read_pool.get()
mask, x, y, size, area = runmodel.get_ROI_position(
img_origin, netS, opt)
positions.append([x, y, area])
if savemask:
t = Thread(target=cv2.imwrite,
args=(
os.path.join(opt.temp_dir + '/ROI_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, 'roi_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('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 ROI locations...')
if continue_flag:
positions = np.concatenate((pre_positions, positions), axis=0)
mask_index = filt.position_medfilt(np.array(positions), 7)
step = {'step': 3, 'frame': 0}
util.savejson(os.path.join(opt.temp_dir, 'step.json'), step)
np.save(os.path.join(opt.temp_dir, 'roi_positions.npy'), positions)
np.save(os.path.join(opt.temp_dir, 'mask_index.npy'), np.array(mask_index))
return mask_index
def addmosaic_video(opt, netS):
path = opt.media_path
fps, imagepaths = video_init(opt, path)[:2]
length = len(imagepaths)
# get position
positions = []
t1 = time.time()
if not opt.no_preview:
cv2.namedWindow('preview', cv2.WINDOW_NORMAL)
print('Step:2/4 -- Find ROI location')
for i, imagepath in enumerate(imagepaths, 1):
img = impro.imread(
os.path.join(opt.temp_dir + '/video2image', imagepath))
mask, x, y, size, area = runmodel.get_ROI_position(img, netS, opt)
positions.append([x, y, area])
cv2.imwrite(os.path.join(opt.temp_dir + '/ROI_mask', imagepath), mask)
#preview result and print
if not opt.no_preview:
cv2.imshow('preview', mask)
cv2.waitKey(1) & 0xFF
t2 = time.time()
print('\r',
str(i) + '/' + str(length),
util.get_bar(100 * i / length, num=35),
util.counttime(t1, t2, i, length),
end='')
print('\nOptimize ROI locations...')
mask_index = filt.position_medfilt(np.array(positions), 7)
# add mosaic
print('Step:3/4 -- Add Mosaic:')
t1 = time.time()
for i, imagepath in enumerate(imagepaths, 1):
mask = impro.imread(
os.path.join(opt.temp_dir + '/ROI_mask',
imagepaths[mask_index[i - 1]]), 'gray')
img = impro.imread(
os.path.join(opt.temp_dir + '/video2image', imagepath))
if impro.mask_area(mask) > 100:
try: #Avoid unknown errors
img = mosaic.addmosaic(img, mask, opt)
except Exception as e:
print('Warning:', e)
cv2.imwrite(os.path.join(opt.temp_dir + '/addmosaic_image', imagepath),
img)
os.remove(os.path.join(opt.temp_dir + '/video2image', imagepath))
#preview result and print
if not opt.no_preview:
cv2.imshow('preview', img)
cv2.waitKey(1) & 0xFF
t2 = time.time()
print('\r',
str(i) + '/' + str(length),
util.get_bar(100 * i / length, num=35),
util.counttime(t1, t2, i, length),
end='')
print()
if not opt.no_preview:
cv2.destroyAllWindows()
print('Step:4/4 -- Convert images to video')
ffmpeg.image2video(
fps,
opt.temp_dir + '/addmosaic_image/output_%06d.' + opt.tempimage_type,
opt.temp_dir + '/voice_tmp.mp3',
os.path.join(opt.result_dir,
os.path.splitext(os.path.basename(path))[0] + '_add.mp4'))
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)
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('Optimized 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]))