stylegan2-pytorch | Image Quality of StyleGAN ( StyleGAN | Machine Learning library

by rosinality Python Version: Current License: MIT

X-Ray Key Features Code Snippets(3)Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | stylegan2-pytorch Summary

stylegan2-pytorch is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Generative adversarial networks applications. stylegan2-pytorch has no bugs, it has no vulnerabilities, it has a Permissive License and it has medium support. However stylegan2-pytorch build file is not available. You can download it from GitHub.

Implementation of Analyzing and Improving the Image Quality of StyleGAN (StyleGAN 2) in PyTorch

Support

Quality

Security

License

Reuse

Support

stylegan2-pytorch has a medium active ecosystem.

It has 2425 star(s) with 612 fork(s). There are 37 watchers for this library.

It had no major release in the last 6 months.

There are 191 open issues and 124 have been closed. On average issues are closed in 6 days. There are 14 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of stylegan2-pytorch is current.

Quality

stylegan2-pytorch has 0 bugs and 0 code smells.

Security

stylegan2-pytorch has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

stylegan2-pytorch code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

stylegan2-pytorch is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

stylegan2-pytorch releases are not available. You will need to build from source code and install.

stylegan2-pytorch has no build file. You will be need to create the build yourself to build the component from source.

stylegan2-pytorch saves you 1482 person hours of effort in developing the same functionality from scratch.

It has 3861 lines of code, 240 functions and 25 files.

It has medium code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed stylegan2-pytorch and discovered the below as its top functions. This is intended to give you an instant insight into stylegan2-pytorch implemented functionality, and help decide if they suit your requirements.

Train the model .
Gradient of convolutional gradient .
Initialize inception v3 .
Initialize the model .
Fill the state_dict .
Sample an affine .
Generate random affine .
Convenience function to create a 2d wavefunction .
Compute the score of a JND dataset .
Score a FASC dataset .

Get all kandi verified functions for this library.

stylegan2-pytorch Key Features

No Key Features are available at this moment for stylegan2-pytorch.

stylegan2-pytorch Examples and Code Snippets

Citations

Jupyter Notebook

Lines of Code : 112

License : No License

Copy

@inproceedings{choi2020starganv2,
  title={StarGAN v2: Diverse Image Synthesis for Multiple Domains},
  author={Yunjey Choi and Youngjung Uh and Jaejun Yoo and Jung-Woo Ha},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Patte

Simple Pytorch StyleGAN2-Distillation Implementation,Usage

Python

Lines of Code : 8

License : No License

Copy

python misc_imdb_preprocessing.py

python all_in_one.py --attribute [gender/age] --phase train --db_root [imdb_dataset_path] 

python all_in_one.py --attribute [gender/age] --phase test --db_root [imdb_dataset_path]

python generate_distillation.py -

Self-Diagnosing GAN,StyleGAN2

Python

Lines of Code : 4

License : Permissive (Apache-2.0)

Copy

python prepare_data.py --out ./dataset/ffhq/lmdb_256.mdb --size 256 --path ./dataset/ffhq

python -m torch.distributed.launch --nproc_per_node=4 --master_port=15694 train_ffhq.py --root ./dataset/ffhq/lmdb_256.mdb --batch 4 --dataset ffhq --exp_name

Community Discussions

Trending Discussions on stylegan2-pytorch

How to make conda use its own gcc version?

WARNING: Legacy build of wheel for 'pysqlite3' created no files. - How do I build a non-legacy build of wheels?

Pytorch says that CUDA is not available

QUESTION

How to make conda use its own gcc version?

Asked 2021-Dec-12 at 16:12

I am trying to run the training of stylegan2-pytorch on a remote system. The remote system has gcc (9.3.0) installed on it. I'm using conda env that has the following installed (cudatoolkit=10.2, torch=1.5.0+, and ninja=1.8.2, gcc_linux-64=7.5.0). I encounter the following error:

...

ANSWER

Answered 2021-Dec-12 at 16:12

Just to share, not sure it will help you. However it shows that in standard conditions it is possible to use the conda gcc as described in the documentation instead of the system gcc.

Source https://stackoverflow.com/questions/70316504

QUESTION

WARNING: Legacy build of wheel for 'pysqlite3' created no files. - How do I build a non-legacy build of wheels?

Asked 2021-Sep-18 at 21:19

I try to install a package (https://github.com/lucidrains/stylegan2-pytorch) on my AWS EC2 instance. I have installed Python 3.7 and is trying to install the package through that by running:

...

ANSWER

Answered 2021-Sep-18 at 21:19

By using the --verbose-flag I saw:

Source https://stackoverflow.com/questions/69237931

QUESTION

Pytorch says that CUDA is not available

Asked 2020-Oct-31 at 21:26

I'm trying to run Pytorch on a laptop that I have. It's an older model but it does have an Nvidia graphics card. I realize it is probably not going to be sufficient for real machine learning but I am trying to do it so I can learn the process of getting CUDA installed.

I have followed the steps on the installation guide for Ubuntu 18.04 (my specific distribution is Xubuntu).

My graphics card is a GeForce 845M, verified by lspci | grep nvidia:

...

ANSWER

Answered 2020-Oct-31 at 21:26

PyTorch doesn't use the system's CUDA library. When you install PyTorch using the precompiled binaries using either pip or conda it is shipped with a copy of the specified version of the CUDA library which is installed locally. In fact, you don't even need to install CUDA on your system to use PyTorch with CUDA support.

There are two scenarios which could have caused your issue.

You installed the CPU only version of PyTorch. In this case PyTorch wasn't compiled with CUDA support so it didn't support CUDA.
You installed the CUDA 10.2 version of PyTorch. In this case the problem is that your graphics card currently uses the 418.87 drivers, which only support up to CUDA 10.1. The two potential fixes in this case would be to either install updated drivers (version >= 440.33 according to Table 2) or to install a version of PyTorch compiled against CUDA 10.1.

To determine the appropriate command to use when installing PyTorch you can use the handy widget in the "Quick start locally" section at pytorch.org. Just select the appropriate operating system, package manager, and CUDA version then run the recommended command.

In your case one solution was to use

Source https://stackoverflow.com/questions/62359175

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install stylegan2-pytorch

You can download it from GitHub.
You can use stylegan2-pytorch like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

Find more information at: