framework-reproducibility VS RealESRScaler

Compare framework-reproducibility vs RealESRScaler and see what are their differences.

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framework-reproducibility RealESRScaler
5 2
418 53
1.2% -
5.8 10.0
7 months ago about 1 year ago
Python Python
Apache License 2.0 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.

framework-reproducibility

Posts with mentions or reviews of framework-reproducibility. We have used some of these posts to build our list of alternatives and similar projects.

RealESRScaler

Posts with mentions or reviews of RealESRScaler. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2023-02-22.

What are some alternatives?

When comparing framework-reproducibility and RealESRScaler you can also consider the following projects:

einops - Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)

QualityScaler - QualityScaler - image/video deeplearning upscaling for any GPU

Real-Time-Voice-Cloning - Clone a voice in 5 seconds to generate arbitrary speech in real-time

RealScaler - RealScaler - image/video AI upscaler app (Real-ESRGAN)

horovod - Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

NiceScaler - Images & Video DeepLearning Upscaler

FluidFrames.RIFE - FluidFrames.RIFE | video AI frame-generation app

Tsuki - Manga uncensoring scripts using DeepCreamPy & HentAI combined with custom scripts

onnx-web - web UI for GPU-accelerated ONNX pipelines like Stable Diffusion, even on Windows and AMD