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 styletransfer_img(opt, netG):
print('Style Transfer_img:', opt.media_path)
img = impro.imread(opt.media_path)
img = runmodel.run_styletransfer(opt, netG, img)
suffix = os.path.basename(opt.model_path).replace('.pth', '').replace(
'style_', '')
impro.imwrite(
os.path.join(
opt.result_dir,
os.path.splitext(os.path.basename(opt.media_path))[0] + '_' +
suffix + '.jpg'), img)
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)
fill_flags = -1 * np.ones(int(src_indexs[-1] / 100 * FPS) + 12,
dtype=np.int64)
for i in range(len(src_indexs)):
match_index = match_indexs[i]
adv_frame = dst_adv_frames[match_indexs[i]]
start_frame = int(np.round(src_indexs[i] / 100 * FPS) - adv_frame)
last_frame = int(dst_last_frames[match_index])
for j in range(last_frame):
fill_flags[start_frame + j] = match_index
img = cv2.imread(
os.path.join('./tmp/video_imgs', '%02d' % match_index,
'%05d' % (j + 1) + '.png'))
impro.imwrite(
os.path.join('./tmp/output_imgs',
'%05d' % (start_frame + j) + '.jpg'), img)
if i != (len(src_indexs) - 1) and start_frame + last_frame <= int(
np.round(src_indexs[i + 1] / 100 * FPS) - adv_frame):
for j in range(
int(np.round(src_indexs[i + 1] / 100 * FPS) - adv_frame) -
start_frame - last_frame + 1):
frame = start_frame + last_frame + j
fill_flags[frame] = match_index
img = cv2.imread(
os.path.join('./tmp/video_imgs', '%02d' % match_index,
'%05d' % (last_frame) + '.png'))
impro.imwrite(
os.path.join('./tmp/output_imgs',
'%05d' % (frame) + '.jpg'), img)
for i, imagepath in enumerate(imagepaths):
x, y, size = positions[i][0], positions[i][1], positions[i][2]
tmp_cnt = i
while size < opt.minsize // 2:
tmp_cnt = tmp_cnt - 1
x, y, size = positions[tmp_cnt][0], positions[tmp_cnt][
1], positions[tmp_cnt][2]
img = impro.resize(imgs[i][y - size:y + size,
x - size:x + size],
opt.outsize,
interpolation=cv2.INTER_CUBIC)
mask = impro.resize(masks[i][y - size:y + size,
x - size:x + size],
opt.outsize,
interpolation=cv2.INTER_CUBIC)
impro.imwrite(
os.path.join(origindir, '%05d' % (i + 1) + '.jpg'), img)
impro.imwrite(os.path.join(maskdir, '%05d' % (i + 1) + '.png'),
mask)
# x_tmp,y_tmp,size_tmp
# for imagepath in imagepaths:
# img = impro.imread(imagepath)
# mask,x,y,halfsize,area = runmodel.get_ROI_position(img,net,opt,keepsize=True)
# if halfsize>opt.minsize//4:
# if not opt.all_mosaic_area:
# mask_avg = impro.find_mostlikely_ROI(mask_avg)
# x,y,size,area = impro.boundingSquare(mask_avg,Ex_mul=ex_mul)
# img = impro.resize(imgs[i][y-size:y+size,x-size:x+size],opt.outsize,interpolation=cv2.INTER_CUBIC)
# mask = impro.resize(masks[i][y-size:y+size,x-size:x+size],opt.outsize,interpolation=cv2.INTER_CUBIC)
# impro.imwrite(os.path.join(origindir,'%05d'%(i+1)+'.jpg'), img)
# impro.imwrite(os.path.join(maskdir,'%05d'%(i+1)+'.png'), mask)