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https://github.com/zumbov2/colorizer
An R wrapper for the DeOldify image colorization API on DeepAI.
https://github.com/zumbov2/colorizer
colorization deoldify image rstats-package
Last synced: 2 months ago
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An R wrapper for the DeOldify image colorization API on DeepAI.
- Host: GitHub
- URL: https://github.com/zumbov2/colorizer
- Owner: zumbov2
- License: other
- Created: 2020-10-22T11:01:31.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2020-11-09T22:29:04.000Z (about 4 years ago)
- Last Synced: 2024-12-04T08:37:08.940Z (2 months ago)
- Topics: colorization, deoldify, image, rstats-package
- Language: R
- Homepage: https://deepai.org/machine-learning-model/colorizer
- Size: 18.4 MB
- Stars: 20
- Watchers: 3
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
- jimsghstars - zumbov2/colorizer - An R wrapper for the DeOldify image colorization API on DeepAI. (R)
README
[](https://cran.r-project.org/package=colorizer)
[](https://travis-ci.org/zumbov2/colorizer)
[](http://cran.rstudio.com/web/packages/colorizer/index.html)
# colorizer
This R package is an interface to the awesome [DeOldify image colorization API](https://github.com/jantic/DeOldify) on [DeepAI](https://deepai.org/machine-learning-model/colorizer), providing the possibility to **colorize and restore old images**. More about the NoGAN learning method used to train DeOldify can be found [here](https://www.fast.ai/2019/05/03/decrappify/).
The default api-key can be used to make a **few requests**. After [registration on DeepAI](https://deepai.org/), around **5000 requests** are currently (Oct 2020) possible within the **free service**.
## Installation
Version 0.1.0 is on CRAN and can be installed as follows:
```r
install.packages("colorizer")
```
Install from GitHub for a regularly updated version (latest: 0.1.0):
```r
install.packages("devtools")
devtools::install_github("zumbov2/colorizer")
```
# Functions
The package provides **three functions/verbs**: `colorize()` to perform API requests, `juxtapose()` to create different comparisons of original and colorized images, and `clsave()` to save colorized images and comparisons.
## Examples
### Breadfruit, approx. 1870
```r
# API call
colorizer::colorize(
img = "https://upload.wikimedia.org/wikipedia/commons/9/9e/Breadfruit.jpg",
key = my_key
) %>%
# Saving colorized image
colorizer::clsave(destfile = "colorized.png") %>%
# Comparing colorized image to original
colorizer::juxtapose(type = "side-by-side") %>%
# Saving comparsion
colorizer::clsave(destfile = "comparison.png")
```
### Children, 1920s
```r
colorizer::colorize(
img = "https://cdn.pixabay.com/photo/2013/02/13/22/38/children-81487_1280.jpg",
key = my_key,
) %>%
juxtapose("side-by-side") %>%
clsave("children1920.jpg")
```
### My Grandpa, 1936
```r
colorizer::colorize(
img = "diskus1936.jpg",
key = my_key
) %>%
colorizer::juxtapose("side-by-side") %>%
colorizer::clsave("HansZumbach.jpg")
```
### John Wayne and Gail Russell, 1940s
```r
colorizer::colorize(
img = "https://cdn.pixabay.com/photo/2014/07/16/03/49/john-wayne-394468_1280.jpg",
key = my_key
) %>%
colorizer::juxtapose("side-by-side") %>%
colorizer::clsave("Wayne-Russel.jpg")
```
## Types of juxtaposition
The comparisons are made using the [magick package](https://github.com/ropensci/magick) – for platform-specific dependencies please see the section [Installation](https://github.com/ropensci/magick#Installation). The following **juxtaposition types** are currently available:
### `type = "side-by-side"`
### `type = "stacked"`
### `type = "c-focus"`
### `type = "h-focus"`
### `type = "v-focus"`
### `type = "h-split"`
### `type = "v-split"`
### `type = "d-split"`
### `type = "u-animate"`
### `type = "s-animate"`
