the-gan-zoo VS dnn_from_scratch

Compare the-gan-zoo vs dnn_from_scratch and see what are their differences.

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the-gan-zoo dnn_from_scratch
2 1
14,007 29
- -
0.0 0.0
7 months ago almost 3 years ago
Python Python
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.

the-gan-zoo

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

dnn_from_scratch

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

What are some alternatives?

When comparing the-gan-zoo and dnn_from_scratch you can also consider the following projects:

anycost-gan - [CVPR 2021] Anycost GANs for Interactive Image Synthesis and Editing

deepxde - A library for scientific machine learning and physics-informed learning

Conditional-Generative-Adversarial-Network - Train a GAN to transform images from one domain to another domain

HyperGAN - Composable GAN framework with api and user interface

Anime-Generation - 🎨 Anime generation with GANs.

ALAE - [CVPR2020] Adversarial Latent Autoencoders

stylegan2-pytorch - Simplest working implementation of Stylegan2, state of the art generative adversarial network, in Pytorch. Enabling everyone to experience disentanglement

guesslang - Detect the programming language of a source code

pytorch-CycleGAN-and-pix2pix - Image-to-Image Translation in PyTorch

open-lpr - Open Source and Free License Plate Recognition Software

Mask-RCNN-TF2 - Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow 2.0