Mirrors/flowframes
1
0
Fork 0
mirror of https://github.com/n00mkrad/flowframes.git synced 2025-12-23 19:59:31 +01:00
Code Issues Packages Projects Releases Wiki Activity

Basic support for RIFE-NCNN-VS

Browse Source
This commit is contained in:
n00mkrad
2022-05-31 22:17:22 +02:00
parent 241e92043d
commit 9ea9ec0875
25 changed files with 317 additions and 121 deletions
Download Patch File Download Diff File Expand all files Collapse all files

28
Code/Data/Implementations.cs
View File

@@ -4,28 +4,32 @@ namespace Flowframes.Data
{
class Implementations
{
public static AI rifeCuda = new AI(AI.Backend.Pytorch, "RIFE_CUDA", "RIFE",
"CUDA/Pytorch Implementation of RIFE (Nvidia Only!)", "rife-cuda", AI.FactorSupport.AnyInteger, new int[] { 2, 3, 4, 5, 6, 7, 8, 9, 10 });
public static AI rifeCuda = new AI(AI.AiBackend.Pytorch, "RIFE_CUDA", "RIFE",
"CUDA/Pytorch Implementation of RIFE (Nvidia Only!)", "rife-cuda", AI.InterpFactorSupport.AnyInteger, new int[] { 2, 3, 4, 5, 6, 7, 8, 9, 10 });
public static AI rifeNcnn = new AI(AI.Backend.Ncnn, "RIFE_NCNN", "RIFE (NCNN)",
"Vulkan/NCNN Implementation of RIFE", "rife-ncnn", AI.FactorSupport.AnyFloat, new int[] { 2, 3, 4, 5, 6, 7, 8, 9, 10 });
public static AI rifeNcnn = new AI(AI.AiBackend.Ncnn, "RIFE_NCNN", "RIFE (NCNN)",
"Vulkan/NCNN Implementation of RIFE", "rife-ncnn", AI.InterpFactorSupport.AnyFloat, new int[] { 2, 3, 4, 5, 6, 7, 8, 9, 10 });
public static AI flavrCuda = new AI(AI.Backend.Pytorch, "FLAVR_CUDA", "FLAVR",
"Experimental Pytorch Implementation of FLAVR (Nvidia Only!)", "flavr-cuda", AI.FactorSupport.Fixed, new int[] { 2, 4, 8 });
public static AI rifeNcnnVs = new AI(AI.AiBackend.Ncnn, "RIFE_NCNN_VS", "RIFE (NCNN/VS)",
"Vulkan/NCNN Implementation of RIFE in VS", "rife-ncnn-vs", AI.InterpFactorSupport.AnyFloat, new int[] { 2, 3, 4, 5, 6, 7, 8, 9, 10 })
{ Piped = true };
public static AI dainNcnn = new AI(AI.Backend.Ncnn, "DAIN_NCNN", "DAIN (NCNN)",
"Vulkan/NCNN Implementation of DAIN", "dain-ncnn", AI.FactorSupport.AnyFloat, new int[] { 2, 3, 4, 5, 6, 7, 8 });
public static AI flavrCuda = new AI(AI.AiBackend.Pytorch, "FLAVR_CUDA", "FLAVR",
"Experimental Pytorch Implementation of FLAVR (Nvidia Only!)", "flavr-cuda", AI.InterpFactorSupport.Fixed, new int[] { 2, 4, 8 });
public static AI xvfiCuda = new AI(AI.Backend.Pytorch, "XVFI_CUDA", "XVFI",
"CUDA/Pytorch Implementation of XVFI (Nvidia Only!)", "xvfi-cuda", AI.FactorSupport.AnyInteger, new int[] { 2, 3, 4, 5, 6, 7, 8, 9, 10 });
public static AI dainNcnn = new AI(AI.AiBackend.Ncnn, "DAIN_NCNN", "DAIN (NCNN)",
"Vulkan/NCNN Implementation of DAIN", "dain-ncnn", AI.InterpFactorSupport.AnyFloat, new int[] { 2, 3, 4, 5, 6, 7, 8 });
public static List<AI> networks = new List<AI> { rifeCuda, rifeNcnn, flavrCuda, dainNcnn, xvfiCuda };
public static AI xvfiCuda = new AI(AI.AiBackend.Pytorch, "XVFI_CUDA", "XVFI",
"CUDA/Pytorch Implementation of XVFI (Nvidia Only!)", "xvfi-cuda", AI.InterpFactorSupport.AnyInteger, new int[] { 2, 3, 4, 5, 6, 7, 8, 9, 10 });
public static List<AI> networks = new List<AI> { rifeCuda, rifeNcnn, rifeNcnnVs, flavrCuda, dainNcnn, xvfiCuda };
public static AI GetAi (string aiName)
{
foreach(AI ai in networks)
{
if (ai.aiName == aiName)
if (ai.AiName == aiName)
return ai;
}