pastiche | PyTorch implementation of Neural Style Transfer | Computer Vision library

by dstein64 Python Version: 1.4.0 License: MIT

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

kandi X-RAY | pastiche Summary

pastiche is a Python library typically used in Artificial Intelligence, Computer Vision, Deep Learning, Pytorch applications. pastiche has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install pastiche' or download it from GitHub, PyPI.

A PyTorch-based Python implementation of Neural Style Transfer [1]. .

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Quality

Security

License

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Support

pastiche has a low active ecosystem.

It has 18 star(s) with 4 fork(s). There are 2 watchers for this library.

It had no major release in the last 12 months.

There are 0 open issues and 3 have been closed. On average issues are closed in 9 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of pastiche is 1.4.0

Quality

pastiche has no bugs reported.

Security

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

License

pastiche 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

pastiche releases are available to install and integrate.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

Top functions reviewed by kandi - BETA

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

Parse arguments
Return a tuple of the names of available GPUs
Transfers source and target color
Compute the covariance matrix
Compute the square root of the input matrix
Save a quantized binary bin
Return a representation of the device s mapping
Draws the loss
Calculate loss
Perform a forward computation
Calculate the gram of the input tensor
Set device strategy
Save image to PIL image
Creates a VGG19 from a Keras HDF5 file

Get all kandi verified functions for this library.

pastiche Key Features

No Key Features are available at this moment for pastiche.

pastiche Examples and Code Snippets

No Code Snippets are available at this moment for pastiche.

Community Discussions

Trending Discussions on pastiche

How do I decode curl url encoded string in a C++ server

Auto Authorization using localStorage and Websocket

Magenta multistyle pastiche generator only generates solid black images?

QUESTION

How do I decode curl url encoded string in a C++ server

Asked 2019-Jul-07 at 08:50

I am using the c++ pastiche rest api library to make a rest api in ubuntu linux. I have got the server to work without problems. I can use php curl to post data to my server. The server receives the data and can return the data. The problem is this. When I post to the server with curl post it sends it to the server in a url encoded string like this name=percy&age=34&eye_color=blue. I need to know how to in C++ put each one into a string. Also one of the fields may also have binary data as well as ordinary strings. I have already written the code to interpret the binary data, but I don't know how to convert the string from curl post at the moment. Please ignore the fact my port is different in my php. The reason is that I am running ubuntu in virtualbox.

I need to extract strings and binary data from the post I am sending. This is what I don't know how to do. I am not sure if I may need another library to do this, or not

Here is my php code:-

...

ANSWER

Answered 2019-Jul-07 at 08:50

I have solved this question now, but I had to change the way I sent the data. Instead of sending the data as formdata I sent it json encoded like this.

Source https://stackoverflow.com/questions/56818691

QUESTION

Auto Authorization using localStorage and Websocket

Asked 2018-Mar-22 at 13:58

I have a project I'm working on which is a single-page dynamic web app which uses Javascript and a Websocket to retrieve data from a Golang server. I've implemented the auto-authorization method described in this article. I was referred to that article from this one which at the end mentions to check out the first article I linked (just in case you were wondering what that first article was "improving" upon).

This is how my setup works:

Client loads app, and before anything dynamic loads, client connects to Websocket
Client sends login, device token, and session token through Websocket (of course if they were logged in before) from localStorage
Golang Websocket server checks if database has matching login, device token, session token, client's browser/version, etc (I get a few other pieces of data to match a device with the user's HTTP request for extra security)
If there's a match, Golang generates a new session token, updates the database match with it, and sends it back to the client
Client gets session token and updates it in their localStorage to use the next time they load the site

Now, don't get me wrong. Everything is working great... but there's one problem:

If a user logs in, then reloads the page a bunch of times as fast as they can, sometimes the websocket and server don't have enough time to get the user's next session token back to them. This of course causes their tokens to expire and be removed from the database and notifies the user that their credentials have either been expired or stolen (which really doesn't look good from a business standpoint).

I have some thoughts on solutions, but none seem promising in scalability and for the long run.

All thoughts and solutions on the matter are appreciated!

...

ANSWER

Answered 2018-Mar-22 at 13:58

After login you should send two tokens to the browser, a short-lived session token (say, one hour) and a long-lived remember-me token (say, 30 days). The session token's TTL is reset to one hour every time the browser shows activity, but its value does not change.

If and only if the session cookie has expired (or is otherwise invalid), the remember-me cookie is traded for a new, authenticated, session. This does not happen when reloading the page, only after the browser has been inactive for more than an hour.

Prolonging the session happens purely on the server side. Only when trading the remember-me token is it critical that the browser receives and stores the new session token.

You should not delete the remember-me token from the database immediately after first use. If I start my browser it restores previously open tabs, which may include multiple for your site. Consequently, your server will receive multiple requests (or websocket connections) almost simultaneously and those requests race for the new session-token.

At my workplace we allow remember-me tokens to be used for up to two minutes after first use, and at most N times, whichever happens first. That fixes races and allows for retries in case of connectivity issues.

Source https://stackoverflow.com/questions/49418541

QUESTION

Magenta multistyle pastiche generator only generates solid black images?

Asked 2017-Oct-05 at 14:21

I've been playing around with the Magenta Multistyle Pastiche Generator, but so far it will only generate solid black images. Someone on a GitHub forum had the same problem, and apparently Magenta is only compatible on CPU with TensorFlow 1.0.1? However, I installed 1.0.1 and I'm still having the same problem. Here's what I'm running in the terminal (after "source activate magenta", of course)

$ image_stylization_transform \

...

ANSWER

Answered 2017-Oct-05 at 14:21

I changed environment by docker instead of pip install magenta, solved this problem. https://github.com/tensorflow/magenta-demos/pull/18#issuecomment-334453199

Hoping that the information will be of some help to you.

Source https://stackoverflow.com/questions/44683174

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

Vulnerabilities

No vulnerabilities reported

Install pastiche

Python 3.6 or greater.
Python 3.6 or greater

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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