Image to Amogus Converter

Converts given image (.png, .jpg, etc) to an amogus gif!

Usage

Place image in the /target/ folder (or anywhere realistically, assuming you can get its path). Next, type the following into the console:

$ python amogus.py path [-size]

Where path is a required string relating to the path of the target image and -size is an optional parameter relating to the size of the outputted .gif (see -h for details).

$ python amogus.py -h
usage: image_to_amogus [-h] [-size SIZE] path

positional arguments:
  path        Path to target image, where the /target/ folder is the current
              directory.

optional arguments:
  -h, --help  show this help message and exit
  -size SIZE  Integer representing the size length of square images, and the
              length of the shortest side in rectangular images (16 by
              default).

Example

Here's an example of the program run on the Girl with a Pearl Earring.

Examples:

$ python amogus.py example.jpg
example_amogus.gif saved in ../output/ folder. So sussy! ඞ

$ python amogus.py example.jpg -size=8
example_amogus.gif saved in ../output/ folder. So sussy! ඞ

$ python amogus.py example.jpg -size=32
example_amogus.gif saved in ../output/ folder. So sussy! ඞ

$ python amogus.py example.jpg -size=64
example_amogus.gif saved in ../output/ folder. So sussy! ඞ

Converts given image (png, jpg, etc) to amogus gif.

Related tags

Overview

Image to Amogus Converter

Usage

Example

Owner

Hank Magan

A simple, unofficial implementation of MAE using pytorch-lightning

Deep learning with TensorFlow and earth observation data.

Its a Plant Leaf Disease Detection System based on Machine Learning.

Official implementation for the paper "Attentive Prototypes for Source-free Unsupervised Domain Adaptive 3D Object Detection"

Vision transformers (ViTs) have found only limited practical use in processing images

Object Depth via Motion and Detection Dataset

Tensorflow implementation of "BEGAN: Boundary Equilibrium Generative Adversarial Networks"

pytorch implementation of fast-neural-style

This is the accompanying toolbox for the paper "A Survey on GANs for Anomaly Detection"

A PyTorch implementation of "Graph Classification Using Structural Attention" (KDD 2018).

All materials of Cassandra Event, Udyam'22

Lacmus is a cross-platform application that helps to find people who are lost in the forest using computer vision and neural networks.

This is an official implementation for "Self-Supervised Learning with Swin Transformers".

Convolutional Neural Network for 3D meshes in PyTorch

This repository contains pre-trained models and some evaluation code for our paper Towards Unsupervised Dense Information Retrieval with Contrastive Learning

FTIR-Deep Learning - FTIR Deep Learning With Python

The source code of "SIDE: Center-based Stereo 3D Detector with Structure-aware Instance Depth Estimation", accepted to WACV 2022.

Code for our NeurIPS 2021 paper 'Exploiting the Intrinsic Neighborhood Structure for Source-free Domain Adaptation'

This is the official Pytorch implementation of the paper "Diverse Motion Stylization for Multiple Style Domains via Spatial-Temporal Graph-Based Generative Model"

MMDetection3D is an open source object detection toolbox based on PyTorch