https://github.com/time4tea/oidnjni
Java JNI Wrappers (Kotlin) for the Intel Open Image Denoise Library
https://github.com/time4tea/oidnjni
Last synced: about 1 year ago
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Java JNI Wrappers (Kotlin) for the Intel Open Image Denoise Library
- Host: GitHub
- URL: https://github.com/time4tea/oidnjni
- Owner: time4tea
- License: mit
- Created: 2020-01-04T18:17:09.000Z (over 6 years ago)
- Default Branch: master
- Last Pushed: 2021-04-16T17:39:55.000Z (about 5 years ago)
- Last Synced: 2025-03-30T23:51:13.519Z (about 1 year ago)
- Language: Kotlin
- Size: 5.21 MB
- Stars: 18
- Watchers: 3
- Forks: 4
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE
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README
### Kotlin / Java JNI Interface to Intel Open Image Denoise Library (OIDN)
## What is this?
Its a Kotlin library and JNI interface to the [Intel Open Image Denoise Library](https://www.openimagedenoise.org)
## Before
## After
## Installing
To install, add these dependencies to your **Gradle** file:
```groovy
dependencies {
compile group: "net.time4tea", name: "oidnjni", version: "0.1.13"
}
```
## How to use
```kotlin
val oidn = Oidn()
val color = Oidn.allocateBuffer(image.width, image.height)
// put some data in the image...
val output = Oidn.allocateBuffer(image.width, image.height)
oidn.newDevice(Oidn.DeviceType.DEVICE_TYPE_DEFAULT).use { device ->
device.raytraceFilter().use { filter ->
filter.setFilterImage(
color, output, image.width, image.height
)
filter.commit()
filter.execute()
device.error()
}
}
```
You can look at the `OidnTest` class for an example usage of the library.
The OIDN library requires a specific raster format, which the Java standard library supports, but does
not give an easy way to create. Use `OidnImages.newBufferedImage()` to create a new buffered image.
Similarly, none of the ImageIO libraries support the raster format. You'll need to create a `BufferedImage`
in a standard format for these functions to work.
```kotlin
fun save(image: BufferedImage, file: File) {
val dest = BufferedImage(image.width, image.height, BufferedImage.TYPE_INT_RGB)
try {
image.copyTo(dest)
ImageIO.write(dest, "PNG", file)
} finally {
dest.flush()
}
}
```
## Performance
The code is almost certainly far from optimal, no effort has gone into making it performant. However, running the filter
will dominate the performance of the code - the JNI wrapper is very thin.
Processing the above image takes 0.35s on my laptop.
## TODO
- [ ] Mac / Windows - I have no hardware - contributors wanted!
- [ ] HDR Images - I have no use-case - contributors wanted!
## Projects that use the OidnJNI library
Please let me know if your project uses or wants to use this small library
- [Raytrace in a weekend Kotlin](https://github.com/time4tea/raytrace-in-a-weekend-kotlin)
## Contributors
[@leMaik](https://github.com/leMaik)
Contributors are welcome! Either for new use-cases, or new features.