deep-daze | Simple command line tool for text to image generation | Machine Learning library

 by   lucidrains Python Version: 0.11.1 License: MIT

kandi X-RAY | deep-daze Summary

kandi X-RAY | deep-daze Summary

deep-daze is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow applications. deep-daze has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has medium support. You can install using 'pip install deep-daze' or download it from GitHub, PyPI.

Simple command line tool for text to image generation using OpenAI's CLIP and Siren. Credit goes to Ryan Murdock for the discovery of this technique (and for coming up with the great name)!. This will require that you have an Nvidia GPU or AMD GPU.
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              deep-daze has a medium active ecosystem.
              It has 4394 star(s) with 335 fork(s). There are 77 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 94 open issues and 73 have been closed. On average issues are closed in 13 days. There are 2 open pull requests and 0 closed requests.
              It has a neutral sentiment in the developer community.
              The latest version of deep-daze is 0.11.1

            kandi-Quality Quality

              deep-daze has 0 bugs and 0 code smells.

            kandi-Security Security

              deep-daze has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              deep-daze code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              deep-daze is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              deep-daze 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.
              It has 1154 lines of code, 69 functions and 6 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed deep-daze and discovered the below as its top functions. This is intended to give you an instant insight into deep-daze implemented functionality, and help decide if they suit your requirements.
            • Train the model .
            • Load a model .
            • Generate a BeautifulSoup token .
            • Builds a model from a dictionary .
            • Download a file .
            • update the words_per_epoch .
            • Tokenize texts .
            • Initializes model parameters .
            • Open a folder .
            • Convert weights from nn .
            Get all kandi verified functions for this library.

            deep-daze Key Features

            No Key Features are available at this moment for deep-daze.

            deep-daze Examples and Code Snippets

            copy iconCopy
            python text_to_painting.py --prompt "a painting of an evergreen tree" --num_iter 2500 --use_blob --subdir vit_rn50_useblob
              

            Community Discussions

            QUESTION

            Running deep-daze on nvidia jetson - "Could not find a version that satisfies the requirement torchvision>=0.8.2"
            Asked 2021-Mar-24 at 02:36

            I have an nvidia Jetson Nano (the 4gb version). I am attempting to run this project on it: https://github.com/lucidrains/deep-daze

            I am attempting to run the command pip install deep-daze. However, I do not have pip so I am running pip3 install deep-daze. When I run that I get

            ...

            ANSWER

            Answered 2021-Mar-24 at 02:36

            Thanks to the comment from Elbek I got this working! I was able to follow the guide here: https://forums.developer.nvidia.com/t/pytorch-for-jetson-version-1-8-0-now-available/72048

            Unfortunately after I got everything installed I ran into an issue with not having enough memory, but, it all got installed.

            Source https://stackoverflow.com/questions/66740533

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

            Vulnerabilities

            No vulnerabilities reported

            Install deep-daze

            Presuming Python is installed:.
            Open command prompt and navigate to the directory of your current version of Python

            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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            Install
          • PyPI

            pip install deep-daze

          • CLONE
          • HTTPS

            https://github.com/lucidrains/deep-daze.git

          • CLI

            gh repo clone lucidrains/deep-daze

          • sshUrl

            git@github.com:lucidrains/deep-daze.git

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