我个人很喜欢作者在stylegan2-ada-pytorch仓库README中的一句话“This repository is a faithful reimplementation of StyleGAN2-ADA in PyTorch, focusing on correctness, performance, and compatibility.”。而这句话,也是我要对你们说的,miemieGAN里的stylegan2-ada、stylegan3跟随官方原版仓库,咩酱对齐了单机单卡、...
StyleGan2 ADA是一种基于人工智能的图像生成模型,它使用PyTorch框架进行开发和训练。该模型可以生成高分辨率、逼真的图像,具有广泛的应用场景,如艺术创作、游戏开发、虚拟现实等。 在使用...
docker build --tag sg2ada:latest../docker_run.sh python3 generate.py --outdir=out --trunc=1 --seeds=85,265,297,849 \ --network=https://nvlabs-fi-cdn.nvidia.com/stylegan2-ada-pytorch/pretrained/metfaces.pkl Note: The Docker image requires NVIDIA driver releaser455.23or later. ...
stylegan2-ada-training-curves.png train-help.txt metrics torch_utils training .gitignore Dockerfile LICENSE.txt README.md calc_metrics.py dataset_tool.py docker_run.sh generate.py legacy.py mc_logger.py projector.py style_mixing.py train.py Breadcrumbs stylegan2-ada-pytorch /docs / train-hel...
docker build --tag sg2ada:latest . ./docker_run.sh python3 generate.py --outdir=out --trunc=1 --seeds=85,265,297,849 \ --network=https://nvlabs-fi-cdn.nvidia.com/stylegan2-ada-pytorch/pretrained/metfaces.pkl Note: The Docker image requires NVIDIA driver releaser455.23or later. ...
StyleGAN2-ADA — Official PyTorch implementation Release notes Data repository Requirements Getting started Projecting images to latent space Using networks from Python Preparing datasets Training new networks Expected training time Quality metrics License ...
StyleGAN2-ADA - Official PyTorch implementation. Contribute to qqq-tech/stylegan2-ada-pytorch development by creating an account on GitHub.
StyleGAN2-ADA - Official PyTorch implementation. Contribute to qqq-tech/stylegan2-ada-pytorch development by creating an account on GitHub.
--network=https://nvlabs-fi-cdn.nvidia.com/stylegan2-ada-pytorch/pretrained/ffhq.pkl Available metrics: \b ADA paper: fid50k_full Frechet inception distance against the full dataset. kid50k_full Kernel inception distance against the full dataset. pr50k3_full Precision and recall againt ...
--network=https://nvlabs-fi-cdn.nvidia.com/stylegan2-ada-pytorch/pretrained/metfaces.pkl \b # Generate uncurated MetFaces images with truncation (Fig.12 upper left) python generate.py --outdir=out --trunc=0.7 --seeds=600-605\\ --network=https://nvlabs-fi-cdn.nvidia.com/stylegan2-ada-...