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Fixed functions needed for img sequences not running, fixed loop frame count with sequences
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@@ -7,13 +7,12 @@ namespace Flowframes.Data
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public static AI rifeCuda = new AI(AI.AiBackend.Pytorch, "RIFE_CUDA", "RIFE",
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"CUDA/Pytorch Implementation of RIFE (Nvidia Only!)", "rife-cuda", AI.InterpFactorSupport.AnyInteger, new int[] { 2, 3, 4, 5, 6, 7, 8, 9, 10 });
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public static AI rifeNcnnVs = new AI(AI.AiBackend.Ncnn, "RIFE_NCNN_VS", "RIFE (NCNN/VS)",
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"Vulkan/NCNN/VapourSynth Implementation of RIFE", "rife-ncnn-vs", AI.InterpFactorSupport.AnyFloat, new int[] { 2, 3, 4, 5, 6, 7, 8, 9, 10 }) { Piped = true };
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public static AI rifeNcnn = new AI(AI.AiBackend.Ncnn, "RIFE_NCNN", "RIFE (NCNN)",
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"Vulkan/NCNN Implementation of RIFE", "rife-ncnn", AI.InterpFactorSupport.AnyFloat, new int[] { 2, 3, 4, 5, 6, 7, 8, 9, 10 });
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public static AI rifeNcnnVs = new AI(AI.AiBackend.Ncnn, "RIFE_NCNN_VS", "RIFE (NCNN/VS)",
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"Vulkan/NCNN Implementation of RIFE in VS", "rife-ncnn-vs", AI.InterpFactorSupport.AnyFloat, new int[] { 2, 3, 4, 5, 6, 7, 8, 9, 10 })
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{ Piped = true };
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public static AI flavrCuda = new AI(AI.AiBackend.Pytorch, "FLAVR_CUDA", "FLAVR",
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"Experimental Pytorch Implementation of FLAVR (Nvidia Only!)", "flavr-cuda", AI.InterpFactorSupport.Fixed, new int[] { 2, 4, 8 });
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