Like a cowsay but without cows!

Last update: Feb 20, 2022

Related tags

Deep Learning foxsay

Overview

Foxsay

This is a simple program that generates pictures of a cute fox with a message.

It is like a cowsay but without cows! Fox girls are better!

Usage

$ ./foxsay.py "Hello, Github!"
# Or.
$ python3 ./foxsay.py "Hello, Github!"
# Or call it without text to get a fox's wisdom.
$ ./foxsay.py

# ╭────────────────╮
# │                │
# │ Hello, Github! │
# │                │
# ╰─v──────────────╯
#
#      |\_|\             ,_.=-,_
#   ._.@ @  ,._.-=-.,_.=`   {.-`
#     '-.,_      (   .-,_ _.`
#          'm`m^"-m.G    `

How to add a new wisdom

Just add it into the WISDOM (in ./foxsay.py file) and create a new Pull Request!

WISDOM = [
    # ...
    "Add your own one! :)",
]

License

MIT

With ❤️ by Anastasia Kim (@gingermuffin)

Owner

Anastasia Kim

GitHub Repository

Learning to Reconstruct 3D Non-Cuboid Room Layout from a Single RGB Image

NonCuboidRoom Paper Learning to Reconstruct 3D Non-Cuboid Room Layout from a Single RGB Image Cheng Yang*, Jia Zheng*, Xili Dai, Rui Tang, Yi Ma, Xiao

67 Dec 15, 2022

Key information extraction from invoice document with Graph Convolution Network

Key Information Extraction from Scanned Invoices Key information extraction from invoice document with Graph Convolution Network Related blog post fro

39 Dec 16, 2022

Data and analysis code for an MS on SK VOC genomes phenotyping/neutralisation assays

Description Summary of phylogenomic methods and analyses used in "Immunogenicity of convalescent and vaccinated sera against clinical isolates of ance

1 Jan 06, 2022

hipCaffe: the HIP port of Caffe

Caffe Caffe is a deep learning framework made with expression, speed, and modularity in mind. It is developed by the Berkeley Vision and Learning Cent

126 Dec 05, 2022

Self-Supervised Learning of Event-based Optical Flow with Spiking Neural Networks

Self-Supervised Learning of Event-based Optical Flow with Spiking Neural Networks Work accepted at NeurIPS'21 [paper, video]. If you use this code in

43 Dec 07, 2022

Prompt Tuning with Rules

PTR Code and datasets for our paper "PTR: Prompt Tuning with Rules for Text Classification" If you use the code, please cite the following paper: @art

118 Dec 30, 2022

Code for the paper: Hierarchical Reinforcement Learning With Timed Subgoals, published at NeurIPS 2021

Hierarchical reinforcement learning with Timed Subgoals (HiTS) This repository contains code for reproducing experiments from our paper "Hierarchical

21 Dec 03, 2022

All supplementary material used by me while TA-ing CS3244: Machine Learning

CS3244-Tutorial-Material All supplementary material used by me while TA-ing CS3244: Machine Learning at NUS School of Computing. What is this? I teach

18 Sep 23, 2022

To propose and implement a multi-class classification approach to disaster assessment from the given data set of post-earthquake satellite imagery.

2 Jan 05, 2022

This is the pytorch re-implementation of the IterNorm

IterNorm-pytorch Pytorch reimplementation of the IterNorm methods, which is described in the following paper: Iterative Normalization: Beyond Standard

32 Dec 27, 2022

This project demonstrates the use of neural networks and computer vision to create a classifier that interprets the Brazilian Sign Language.

LIBRAS-Image-Classifier This project demonstrates the use of neural networks and computer vision to create a classifier that interprets the Brazilian

26 Oct 14, 2022

Like a cowsay but without cows!

Related tags

Overview

Foxsay

Usage

How to add a new wisdom

License

Owner

Anastasia Kim

Learning to Reconstruct 3D Non-Cuboid Room Layout from a Single RGB Image

Key information extraction from invoice document with Graph Convolution Network

Data and analysis code for an MS on SK VOC genomes phenotyping/neutralisation assays

hipCaffe: the HIP port of Caffe

Self-Supervised Learning of Event-based Optical Flow with Spiking Neural Networks

Prompt Tuning with Rules

Code for the paper: Hierarchical Reinforcement Learning With Timed Subgoals, published at NeurIPS 2021

All supplementary material used by me while TA-ing CS3244: Machine Learning

To propose and implement a multi-class classification approach to disaster assessment from the given data set of post-earthquake satellite imagery.

This is the pytorch re-implementation of the IterNorm

This project demonstrates the use of neural networks and computer vision to create a classifier that interprets the Brazilian Sign Language.

A Physics-based Noise Formation Model for Extreme Low-light Raw Denoising (CVPR 2020 Oral & TPAMI 2021)

PyTorch implementations of the paper: "Learning Independent Instance Maps for Crowd Localization"

AlgoVision - A Framework for Differentiable Algorithms and Algorithmic Supervision

Deep Reinforcement Learning for mobile robot navigation in ROS Gazebo simulator

Code of paper: "DropAttack: A Masked Weight Adversarial Training Method to Improve Generalization of Neural Networks"

The description of FMFCC-A (audio track of FMFCC) dataset and Challenge resluts.

RINDNet: Edge Detection for Discontinuity in Reflectance, Illumination, Normal and Depth, in ICCV 2021 (oral)

Tensorflow implementation of our method: "Triangle Graph Interest Network for Click-through Rate Prediction".

Implementation of gaze tracking and demo