# Image Inpainting with Learnable Bidirectional Attention Maps. The PaddlePaddle implementation of Image Inpainting with Learnable Bidirectional Attention Maps in ICCV 2019, by Chaohao Xie, Shaohui Liu, Chao Li, Ming-Ming Cheng, Wangmeng Zuo, Xiao Liu, Shilei Wen, Errui Ding.\ <https://arxiv.org/abs/1909.00968> ## 1. Requirements. PaddlePaddle version == 1.6.\ Python version == 3.6.\ NCCL for multiple GPUs. ## 2. Usage. Download the pretrained models by <https://pan.baidu.com/s/1Xpgj6pcBTYYYxsAlJrFXgg>, password: apfo.\ Run the test script. ``` sh test.sh ``` ``` mkdir -p results/paris FLAGS_fraction_of_gpu_memory_to_use=0.1 \ CUDA_VISIBLE_DEVICES=0 \ FLAGS_eager_delete_tensor_gb=0.0 \ FLAGS_fast_eager_deletion_mode=1 \ python -u test.py \ --pretrained_model 'pretrained_models/LBAM_ParisStreetView' \ # path to the pretrained model --imgfn 'imgs/paris/pic.png' \ # input picture. --maskfn 'imgs/paris/mask.png' \ # mask. --resultfn 'results/paris' # folder for the result. ``` Input picture:\  Input mask:\  Inpainting result:\ 
