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# Flowframes - Windows GUI for Video Interpolation
Flowframes Windows GUI for video interpolation - Supports RIFE, RIFE-NCNN, DAIN-NCNN networks.
Flowframes Windows GUI for video interpolation - Supports RIFE Pytorch and NCNN implementations.
Flowframes is **open-source donationware**. Builds are released for free on itch after an early-access period on Patreon. This repo's code is complete and does not "paywall" experienced users who want to compile the program themselves.
However, **I do not provide support for self-built versions** as I can't guarantee that the code of this repo is stable at any given moment.
However, **I do not provide support for self-built versions** as I can't guarantee that the code of this repo is stable at any given moment. Refer to the releases if you want to get the most stable sourcce code.
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* Download on [itch](https://nmkd.itch.io/flowframes) or, for the most recent beta versions, on [Patreon](https://www.patreon.com/n00mkrad). This repo does not provide builds.
* Run Flowframes.exe
* Pre-1.18: Select the components you want to install (certain packages are required, cannot be unticked)
Starting with 1.18, the installer has been removed, and Flowframes is instead distributed as an all-in-one archive. Download the "Full" file if you are using a Maxwell/Pascal/Turing GPU and want to use embedded Pytorch. Use "NoPython" if you run an AMD GPU or want to use your system Python/Pytorch installation.
Starting with 1.18, the installer has been removed, and Flowframes is instead distributed as an all-in-one archive. Download the "Full" file if you are using a Maxwell/Pascal/Turing GPU and want to use embedded Pytorch, or "Full-RTX3000" if you have an Ampere GPU. Use "NoPython"/"Slim" if you run an AMD GPU or want to use your system Python/Pytorch installation.
## Using A Pytorch Implementation
Some of the AI networks run on Tencent's NCNN framework, which allows them to run on any modern (Vulkan-capable) GPU.
Flowframes comes with RIFE-NCNN which runs on Tencent's NCNN framework, which allows it to run on any modern (Vulkan-capable) GPU.
However, others (like RIFE) run best via their original Pytorch implementation.
However, the official RIFE implementation run best via its original Pytorch implementation.
The requirements to run these are the following:
* A **modern Nvidia GPU** (750 Ti, 900/1000/1600/2000/3000 Series).
* A **Python** installation including Pytorch (1.5 or later) as well as the packages `opencv-python` and `imageio`.
* You can install a portable version of all those requirements from the Flowframes Installer. This does not support RTX 3000 cards yet.
* The python runtime with pytorch is included in the Flowframes "Full" and "Full-RTX3000" downloads.
[More Details On Python Dependencies](PythonDependencies.md)
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## Running A Pytorch Implementation on Nvidia Ampere GPUs
Ampere support is currently (Dec 2020) limited. The embedded Python runtime is not compatible with RTX 3000 cards. To enable compatiblity, [install Pytorch 1.7.1](https://pytorch.org/get-started/locally/) or newer on Python 3.8.x.
The python runtime included in the "Full-RTX3000" package includes support for Ampere GPUs. If you want to use your own installation, [use Pytorch 1.7.1](https://pytorch.org/get-started/locally/) or newer on Python 3.8.x.
Important: Ampere GPUs perform worse than they should on cuDNN 8.04 and older. If your cuDNN version is not >=8.05, you can manually update it by downloading it from Nvidia and replacing the DLLs in the torch folder. If you don't want to do that, you can wait until 8.05 is included in Pytorch.
Important: Ampere GPUs perform worse than they should on cuDNN 8.04 and older. If your cuDNN version is not >=8.05, you can manually update it by downloading it from Nvidia and replacing the DLLs in the torch folder. The embedded runtime already includes those files.