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@ -2,12 +2,12 @@
OpenRewind is an open-source alternative to [rewind.ai](https://rewind.ai), forked from [OpenRecall](https://github.com/openrecall/openrecall). OpenRewind is an open-source alternative to [rewind.ai](https://rewind.ai), forked from [OpenRecall](https://github.com/openrecall/openrecall).
We want to create an open source app that provides similar core functionality We wanted to create an open source app that provides similar core functionality
to rewind.ai, and that app is **OpenRewind**. to rewind.ai, and that app is **OpenRewind**.
## Alpha Release: 0.8.0 ## Alpha Release: 0.8.0
Latest works: There is an Alpha version available! We currently only support Apple Silicon Macs. Latest results: There is an Alpha version available! We currently only support Apple Silicon Macs.
(Of course, thanks to building on Electron, there will definitely be support for multiple platforms in the beta/stable release) (Of course, thanks to building on Electron, there will definitely be support for multiple platforms in the beta/stable release)
### ✨ Features ### ✨ Features
@ -20,7 +20,7 @@ Latest works: There is an Alpha version available! We currently only support App
## To-dos ## To-dos
### OCR optimized for the specific platform ## OCR optimized for the specific platform
We will use the OCR API provided by the OS for macOS and Windows. We will use the OCR API provided by the OS for macOS and Windows.
@ -29,9 +29,9 @@ Reference projects:
> We [forked](https://github.com/alikia2x/ocrit) this project to suit our needs > We [forked](https://github.com/alikia2x/ocrit) this project to suit our needs
- [Windows.Media.Ocr.Cli](https://github.com/zh-h/Windows.Media.Ocr.Cli) - [Windows.Media.Ocr.Cli](https://github.com/zh-h/Windows.Media.Ocr.Cli)
### Big-little architecture optimizations for Apple Silicon ## Big-little architecture optimizations for Apple Silicon
We wrote a small Swift program that allows a given program to run at a selected QoS class. On ARM Mac, this means we can put some work (such as video encoding) to Efficient cores, reducing peak CPU usage and power consumption. We wrote a small Swift program that allows a given program to run at a selected QoS energy class. On ARM Macs, this means we can offload some work (such as video encoding) to energy-efficient cores, reducing peak CPU usage and power consumption.
> See: [Prioritize Work with Quality of Service Classes](https://developer.apple.com/library/archive/documentation/Performance/Conceptual/EnergyGuide-iOS/PrioritizeWorkWithQoS.html) > See: [Prioritize Work with Quality of Service Classes](https://developer.apple.com/library/archive/documentation/Performance/Conceptual/EnergyGuide-iOS/PrioritizeWorkWithQoS.html)