Text-to-Image-Synthesis | Pytorch implementation of Generative Adversarial | Machine Learning library

by aelnouby Python Version: Current License: GPL-3.0

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | Text-to-Image-Synthesis Summary

Text-to-Image-Synthesis is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Generative adversarial networks applications. Text-to-Image-Synthesis has no bugs, it has no vulnerabilities, it has a Strong Copyleft License and it has low support. However Text-to-Image-Synthesis build file is not available. You can download it from GitHub.

This is a pytorch implementation of Generative Adversarial Text-to-Image Synthesis paper, we train a conditional generative adversarial network, conditioned on text descriptions, to generate images that correspond to the description. The network architecture is shown below (Image from [1]). This architecture is based on DCGAN.

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Text-to-Image-Synthesis has a low active ecosystem.

It has 304 star(s) with 77 fork(s). There are 14 watchers for this library.

It had no major release in the last 6 months.

There are 11 open issues and 21 have been closed. On average issues are closed in 14 days. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of Text-to-Image-Synthesis is current.

Quality

Text-to-Image-Synthesis has 0 bugs and 21 code smells.

Security

Text-to-Image-Synthesis has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

Text-to-Image-Synthesis code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

Text-to-Image-Synthesis is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

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Text-to-Image-Synthesis releases are not available. You will need to build from source code and install.

Text-to-Image-Synthesis has no build file. You will be need to create the build yourself to build the component from source.

Text-to-Image-Synthesis saves you 418 person hours of effort in developing the same functionality from scratch.

It has 991 lines of code, 52 functions and 13 files.

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

Top functions reviewed by kandi - BETA

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

Train the model
Train the WAN
Train the loss function
Train the vanilla WAN
Train a v2gan
Plot a line
Plots the discriminator coefficient for a given epoch
Logs an iteration
Saves checkpoint to directory
Log iteration of iteration
Plot the discriminator
Smooth a tensor

Get all kandi verified functions for this library.

Text-to-Image-Synthesis Key Features

No Key Features are available at this moment for Text-to-Image-Synthesis.

Text-to-Image-Synthesis Examples and Code Snippets

No Code Snippets are available at this moment for Text-to-Image-Synthesis.

Community Discussions

Trending Discussions on Text-to-Image-Synthesis

Text to Image generation using torch model/path file

QUESTION

Text to Image generation using torch model/path file

Asked 2021-Jun-06 at 06:40

I trained a text to image generation model based on https://github.com/aelnouby/Text-to-Image-Synthesis. Now I have 2 path files (one for generator , another for discriminator) . How to generate images using this path files?

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ANSWER

Answered 2021-Jun-06 at 06:40

You need to pass your generator path file here. self.generator.load_state_dict(torch.load(pre_trained_gen)) Refer line 28 of trainer.py

Source https://stackoverflow.com/questions/67772795

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

Vulnerabilities

No vulnerabilities reported

Install Text-to-Image-Synthesis

You can download it from GitHub.
You can use Text-to-Image-Synthesis 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.

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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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