2021-08-31 00:09:47 +02:00
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using System.Collections.Generic;
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2021-08-23 16:50:18 +02:00
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namespace Flowframes.Data
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{
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class Implementations
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{
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2021-08-31 00:09:47 +02:00
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public static AI rifeCuda = new AI(AI.Backend.Pytorch, "RIFE_CUDA", "RIFE",
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2022-04-06 20:48:47 +02:00
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"CUDA/Pytorch Implementation of RIFE (Nvidia Only!)", "rife-cuda", AI.FactorSupport.AnyInteger, new int[] { 2, 3, 4, 5, 6, 7, 8, 9, 10 });
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2021-08-31 00:09:47 +02:00
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public static AI rifeNcnn = new AI(AI.Backend.Ncnn, "RIFE_NCNN", "RIFE (NCNN)",
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2022-04-06 20:48:47 +02:00
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"Vulkan/NCNN Implementation of RIFE", "rife-ncnn", AI.FactorSupport.AnyFloat, new int[] { 2, 3, 4, 5, 6, 7, 8, 9, 10 });
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2021-08-31 00:09:47 +02:00
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public static AI flavrCuda = new AI(AI.Backend.Pytorch, "FLAVR_CUDA", "FLAVR",
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2022-04-06 20:48:47 +02:00
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"Experimental Pytorch Implementation of FLAVR (Nvidia Only!)", "flavr-cuda", AI.FactorSupport.Fixed, new int[] { 2, 4, 8 });
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2021-08-31 00:09:47 +02:00
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public static AI dainNcnn = new AI(AI.Backend.Ncnn, "DAIN_NCNN", "DAIN (NCNN)",
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2022-04-07 14:20:28 +02:00
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"Vulkan/NCNN Implementation of DAIN", "dain-ncnn", AI.FactorSupport.AnyFloat, new int[] { 2, 3, 4, 5, 6, 7, 8 });
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2021-08-31 00:09:47 +02:00
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public static AI xvfiCuda = new AI(AI.Backend.Pytorch, "XVFI_CUDA", "XVFI",
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"CUDA/Pytorch Implementation of XVFI (Nvidia Only!)", "xvfi-cuda", AI.FactorSupport.AnyInteger, new int[] { 2, 3, 4, 5, 6, 7, 8, 9, 10 });
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2021-08-23 16:50:18 +02:00
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public static List<AI> networks = new List<AI> { rifeCuda, rifeNcnn, flavrCuda, dainNcnn, xvfiCuda };
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public static AI GetAi (string aiName)
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{
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foreach(AI ai in networks)
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{
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if (ai.aiName == aiName)
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return ai;
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}
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return networks[0];
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}
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}
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}
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