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(sparnet) C:\Users\user\sparnet>python test_enhance_single_unalign.py --gpus 1 --model sparnethd --name SPARNetHD_V4_Attn2D --res_depth 10 --att_name spar --Gnorm "in" --pretrain_model_path pretrain_models/SPARNetHD_V4_Attn2D_net_H-epoch10.pth --test_img_path ./test_images/test_hzgg.jpg --results_dir test_hzgg_results ----------------- Options --------------- Dnorm: none Gnorm: in [default: bn] att_name: spar batch_size: 32 bottleneck_size: 4 checkpoints_dir: ./check_points data_device: cuda:0 [default: None] dataroot: None dataset_name: celeba debug: False device: cuda:0 [default: None] epoch: latest eval: False gpu_ids: [0] [default: None] gpus: 1 init_gain: 0.02 init_type: normal input_nc: 3 isTrain: False [default: None] load_iter: 0 [default: 0] load_size: None max_dataset_size: inf model: sparnethd [default: test] n_layers_D: 4 name: SPARNetHD_V4_Attn2D [default: experiment_name] ndf: 64 ngf: 64 ntest: inf num_D: 3 num_test: 50 num_threads: 8 output_nc: 3 phase: test preprocess: none pretrain_model_path: pretrain_models/SPARNetHD_V4_Attn2D_net_H-epoch10.pth [default: ] res_depth: 10 results_dir: test_hzgg_results [default: ./results/] save_as_dir: seed: 123 serial_batches: False suffix: test_img_path: ./test_images/test_hzgg.jpg [default: ] test_upscale: 1 verbose: False ----------------- End ------------------- ======> Loading images, crop and align faces. ======> Saving aligned LQ faces to test_hzgg_results\LQ_faces initialize network SPARNet with normal model [SPARNetHDModel] was created Loading pretrained model pretrain_models/SPARNetHD_V4_Attn2D_net_H-epoch10.pth 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [08:16<00:00, 496.16s/it] ======> Save the enhanced faces. ======> Paste the enhanced faces back to the original image. 100%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 1/1 [00:00<00:00, 8.58it/s] ======> Save final result to test_hzgg_results\hq_final.jpg
(sparnet) C:\Users\user\sparnet>
(sparnet) C:\Users\user\sparnet>conda list
packages in environment at C:\Users\user\miniconda3\envs\sparnet:
Name Version Build Channel
absl-py 1.4.0 pypi_0 pypi astor 0.8.1 pypi_0 pypi blas 1.0 mkl ca-certificates 2023.5.7 h56e8100_0 conda-forge certifi 2023.5.7 pyhd8ed1ab_0 conda-forge cmake 3.26.3 pypi_0 pypi colorama 0.4.6 pypi_0 pypi cudatoolkit 10.1.243 h74a9793_0 cycler 0.11.0 pypi_0 pypi dlib 19.24.0 py37h53cf009_0 conda-forge fonttools 4.38.0 pypi_0 pypi freetype 2.12.1 ha860e81_0 future 0.18.3 pypi_0 pypi gast 0.2.2 pypi_0 pypi giflib 5.2.1 h8cc25b3_3 google-pasta 0.2.0 pypi_0 pypi grpcio 1.54.2 pypi_0 pypi h5py 3.8.0 pypi_0 pypi imageio 2.9.0 pypi_0 pypi imgaug 0.4.0 pypi_0 pypi importlib-metadata 6.6.0 pypi_0 pypi intel-openmp 2021.4.0 haa95532_3556 jpeg 9e h2bbff1b_1 keras-applications 1.0.8 pypi_0 pypi keras-preprocessing 1.1.2 pypi_0 pypi kiwisolver 1.4.4 pypi_0 pypi lerc 3.0 hd77b12b_0 libdeflate 1.17 h2bbff1b_0 libpng 1.6.39 h8cc25b3_0 libtiff 4.5.0 h6c2663c_2 libwebp 1.2.4 hbc33d0d_1 libwebp-base 1.2.4 h2bbff1b_1 lz4-c 1.9.4 h2bbff1b_0 markdown 3.4.3 pypi_0 pypi markupsafe 2.1.2 pypi_0 pypi matplotlib 3.5.3 pypi_0 pypi mkl 2021.4.0 haa95532_640 mkl-service 2.4.0 py37h2bbff1b_0 mkl_fft 1.3.1 py37h277e83a_0 mkl_random 1.2.2 py37hf11a4ad_0 networkx 2.6.3 pypi_0 pypi ninja 1.10.2 haa95532_5 ninja-base 1.10.2 h6d14046_5 numpy 1.21.5 py37h7a0a035_3 numpy-base 1.21.5 py37hca35cd5_3 opencv-python 4.7.0.72 pypi_0 pypi openssl 1.1.1t h2bbff1b_0 opt-einsum 3.3.0 pypi_0 pypi packaging 23.1 pypi_0 pypi pillow 7.2.0 pypi_0 pypi pip 22.3.1 py37haa95532_0 protobuf 4.23.0 pypi_0 pypi pyparsing 3.0.9 pypi_0 pypi python 3.7.16 h6244533_0 python-dateutil 2.8.2 pypi_0 pypi python_abi 3.7 2_cp37m conda-forge pytorch 1.5.1 py3.7_cuda101_cudnn7_0 pytorch pytorch-fid 0.3.0 pypi_0 pypi pywavelets 1.3.0 pypi_0 pypi scikit-image 0.17.2 pypi_0 pypi scipy 1.4.1 pypi_0 pypi setuptools 65.6.3 py37haa95532_0 shapely 2.0.1 pypi_0 pypi six 1.16.0 pyhd3eb1b0_1 sqlite 3.41.2 h2bbff1b_0 tensorboard 1.15.0 pypi_0 pypi tensorboardx 2.1 pypi_0 pypi tensorflow 1.15.0 pypi_0 pypi tensorflow-estimator 1.15.1 pypi_0 pypi termcolor 2.3.0 pypi_0 pypi tifffile 2021.11.2 pypi_0 pypi tk 8.6.12 h2bbff1b_0 torchvision 0.6.1 py37_cu101 pytorch tqdm 4.65.0 pypi_0 pypi typing-extensions 4.5.0 pypi_0 pypi vc 14.2 h21ff451_1 vs2015_runtime 14.27.29016 h5e58377_2 werkzeug 2.2.3 pypi_0 pypi wheel 0.38.4 py37haa95532_0 wincertstore 0.2 py37haa95532_2 wrapt 1.15.0 pypi_0 pypi xz 5.4.2 h8cc25b3_0 zipp 3.15.0 pypi_0 pypi zlib 1.2.13 h8cc25b3_0 zstd 1.5.5 hd43e919_0
(sparnet) C:\Users\user\sparnet>
python test_enhance_single_unalign.py --gpus 1 --model sparnethd --name SPARNetHD_V4_Attn3D --res_depth 10 --att_name spar3d --Gnorm "in" --pretrain_model_path ./pretrain_models/SPARNetHD_V4_Attn3D_net_H-epoch10.pth --test_img_path ./test_images/test_hzgg.jpg --results_dir test_hzgg_results