ai-art-generator VS TensorFlow2.0_Notebooks

Compare ai-art-generator vs TensorFlow2.0_Notebooks and see what are their differences.

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ai-art-generator TensorFlow2.0_Notebooks
3 1
627 37
- -
0.0 0.0
about 1 year ago about 3 years ago
Python Jupyter Notebook
GNU General Public License v3.0 or later MIT License
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

ai-art-generator

Posts with mentions or reviews of ai-art-generator. We have used some of these posts to build our list of alternatives and similar projects.
  • Cheap setup to run SD?
    1 project | /r/StableDiffusion | 5 Sep 2022
    I have a github project that will help you set up large batches of prompts too.
  • Local AI art generation tool updated for Stable Diffusion
    1 project | /r/bigsleep | 22 Aug 2022
    Hey all, just a note that I've updated my AI-art generator to work with Stable Diffusion (both txt2img and imgtoimg)! If you have a decent GPU (8GB VRAM+, though more is better), you should be able to use Stable Diffusion on your local computer.
  • Tesla M40 24GB GPU: very poor machine-learning performance?
    1 project | /r/MLQuestions | 1 Jan 2022
    I'm a software engineer, but a complete machine-learning noob (not exactly a linux guru, either). I'm trying to use the GPU for VQGAN+CLIP image generation. Running on an RTX 3060, I get almost 4 iterations per second, so a 512x512 image takes about 2 minutes to create with default settings. Running on the Tesla M40, I get about 0.4 iterations per second (~22 minutes per 512x512 image at the same settings). A full order of magnitude slower! I'd read that older Tesla GPUs are some of the top value picks when it comes to ML applications, but obviously with this level of performance that isn't the case at all. I figure I must be going wrong somewhere.

TensorFlow2.0_Notebooks

Posts with mentions or reviews of TensorFlow2.0_Notebooks. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-04-17.

What are some alternatives?

When comparing ai-art-generator and TensorFlow2.0_Notebooks you can also consider the following projects:

vqgan-clip-generator - Implements VQGAN+CLIP for image and video generation, and style transfers, based on text and image prompts. Emphasis on ease-of-use, documentation, and smooth video creation.

mmcv - OpenMMLab Computer Vision Foundation

Animender - An AI that recommends anime based on personal history.

Time-Series-Forecasting-Using-LSTM - Time-Series Forecasting on Stock Prices using LSTM

tensorflow-deep-learning - All course materials for the Zero to Mastery Deep Learning with TensorFlow course.

cryptocurrency-price-prediction - Cryptocurrency Price Prediction Using LSTM neural network

Deep-Learning-With-TensorFlow - All the resources and hands-on exercises for you to get started with Deep Learning in TensorFlow

strv-ml-mask2face - Virtually remove a face mask to see what a person looks like underneath

ReVersion - ReVersion: Diffusion-Based Relation Inversion from Images

TensorFlow-Tutorials - TensorFlow Tutorials with YouTube Videos

TTS - πŸΈπŸ’¬ - a deep learning toolkit for Text-to-Speech, battle-tested in research and production

Deep-Learning-In-Production - Build, train, deploy, scale and maintain deep learning models. Understand ML infrastructure and MLOps using hands-on examples.