dataset_paths = { 'cars_train': '', 'cars_test': '', 'celeba_train': '', 'celeba_test': '', 'celeba_test_w_inv': '', 'celeba_test_w_latents': '', 'ffhq': '', 'ffhq_w_inv': '', 'ffhq_w_latents': '', 'afhq_wild_train': '', 'afhq_wild_test': '', } model_paths = { # models for backbones and losses 'ir_se50': 'pretrained_models/model_ir_se50.pth', 'resnet34': 'pretrained_models/resnet34-333f7ec4.pth', 'moco': 'pretrained_models/moco_v2_800ep_pretrain.pt', # stylegan2 generators 'stylegan_ffhq': 'pretrained_models/stylegan2-ffhq-config-f.pt', 'stylegan_cars': 'pretrained_models/stylegan2-car-config-f.pt', 'stylegan_ada_wild': 'pretrained_models/afhqwild.pt', # model for face alignment 'shape_predictor': 'pretrained_models/shape_predictor_68_face_landmarks.dat', # models for ID similarity computation 'curricular_face': 'pretrained_models/CurricularFace_Backbone.pth', 'mtcnn_pnet': 'pretrained_models/mtcnn/pnet.npy', 'mtcnn_rnet': 'pretrained_models/mtcnn/rnet.npy', 'mtcnn_onet': 'pretrained_models/mtcnn/onet.npy', # WEncoders for training on various domains 'faces_w_encoder': 'pretrained_models/faces_w_encoder.pt', 'cars_w_encoder': 'pretrained_models/cars_w_encoder.pt', 'afhq_wild_w_encoder': 'pretrained_models/afhq_wild_w_encoder.pt', # models for domain adaptation 'restyle_e4e_ffhq': 'pretrained_models/restyle_e4e_ffhq_encode.pt', 'stylegan_pixar': 'pretrained_models/pixar.pt', 'stylegan_toonify': 'pretrained_models/ffhq_cartoon_blended.pt', 'stylegan_sketch': 'pretrained_models/sketch.pt', 'stylegan_disney': 'pretrained_models/disney_princess.pt' } edit_paths = { 'age': 'editing/interfacegan_directions/age.pt', 'smile': 'editing/interfacegan_directions/smile.pt', 'pose': 'editing/interfacegan_directions/pose.pt', 'cars': 'editing/ganspace_directions/cars_pca.pt', 'styleclip': { 'delta_i_c': 'editing/styleclip/global_directions/ffhq/fs3.npy', 's_statistics': 'editing/styleclip/global_directions/ffhq/S_mean_std', 'templates': 'editing/styleclip/global_directions/templates.txt' } }