FastPhotoStyle | Style transfer , deep learning , feature transform | Machine Learning library

by NVIDIA Python Version: f33e07f License: Non-SPDX

X-Ray Key Features Code Snippets Community Discussions(2)Vulnerabilities Install Support

kandi X-RAY | FastPhotoStyle Summary

FastPhotoStyle is a Python library typically used in Institutions, Learning, Education, Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Tensorflow applications. FastPhotoStyle has no bugs, it has no vulnerabilities and it has medium support. However FastPhotoStyle build file is not available and it has a Non-SPDX License. You can download it from GitHub.

Given a content photo and a style photo, the code can transfer the style of the style photo to the content photo. The details of the algorithm behind the code is documented in our arxiv paper. Please cite the paper if this code repository is used in your publications. A Closed-form Solution to Photorealistic Image Stylization Yijun Li (UC Merced), Ming-Yu Liu (NVIDIA), Xueting Li (UC Merced), Ming-Hsuan Yang (NVIDIA, UC Merced), Jan Kautz (NVIDIA) European Conference on Computer Vision (ECCV), 2018.

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Quality

Security

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Support

FastPhotoStyle has a medium active ecosystem.

It has 11009 star(s) with 1208 fork(s). There are 276 watchers for this library.

It had no major release in the last 12 months.

There are 47 open issues and 39 have been closed. On average issues are closed in 63 days. There are 8 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of FastPhotoStyle is f33e07f

Quality

FastPhotoStyle has 0 bugs and 42 code smells.

Security

FastPhotoStyle has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

FastPhotoStyle code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

FastPhotoStyle has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

FastPhotoStyle releases are available to install and integrate.

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

FastPhotoStyle saves you 425 person hours of effort in developing the same functionality from scratch.

It has 1008 lines of code, 27 functions and 9 files.

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

Top functions reviewed by kandi - BETA

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

Styles the image
Forward multiple x
Computes the label information
Transform image
Process the image
Returns a rolling block
Performs padding of an array
Compute the laplacian matrix
Download a file from Google Drive
Save response content to destination
Get confirm token from response cookies
Segment the given image
Loads the state of a photo
Assign weights to pth

Get all kandi verified functions for this library.

FastPhotoStyle Key Features

No Key Features are available at this moment for FastPhotoStyle.

FastPhotoStyle Examples and Code Snippets

No Code Snippets are available at this moment for FastPhotoStyle.

Community Discussions

Trending Discussions on FastPhotoStyle

No module named 'cupy' on Google Colab

best_local_affine_kernel.cu [WinError 126] The specified module could not be found on Windows 10

QUESTION

No module named 'cupy' on Google Colab

Asked 2019-Jun-13 at 14:00

I'm working on the FastPhotoStyle project: https://github.com/NVIDIA/FastPhotoStyle

and I follow the steps of its tutorial: https://github.com/NVIDIA/FastPhotoStyle/blob/master/TUTORIAL.md

I'm running Example 1 on Google Colab where default environment is

CUDA 10.0
Python 3.6
Chainer 5.4.0
CuPy 5.4.0

This is how I tried on Colab Notebook:

https://colab.research.google.com/drive/1oBgdJgXCLlUQhpwPoG1Uom3OKTzHR4BF

After running

...

ANSWER

Answered 2019-Jun-13 at 14:00

have you tried running the demo with python full path?

Source https://stackoverflow.com/questions/56563973

QUESTION

best_local_affine_kernel.cu [WinError 126] The specified module could not be found on Windows 10

Asked 2018-Dec-29 at 18:17

I am running FastPhotoStyle code on Windows 10 and using Python 3.7, CUDA 10.0 and cuda 9.1. Although I made the change that was suggested to upgrade the version of Python from string to Byte, I am still getting the same error. Can you please suggest a fix for this issue.

...

ANSWER

Answered 2018-Dec-29 at 17:19

Please check the documentation here --> https://github.com/NVIDIA/FastPhotoStyle/blob/master/TUTORIAL.md

The above link specifies setup on Ubuntu but there are prerequites for Python modules as well that you should have installed on your machine.

Source https://stackoverflow.com/questions/53971661

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

Vulnerabilities

No vulnerabilities reported

Install FastPhotoStyle

You can download it from GitHub.
You can use FastPhotoStyle 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 .

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