vs： 新增 ivtc_std

附带修正 nlmeans

Author: hooke007

portable_config/vs/ivtc_std.vpy

@@ -0,0 +1,29 @@
+### 伪25或30帧的源转24帧
+
+import vapoursynth as vs
+from vapoursynth import core
+
+input = video_in
+fps_in = container_fps
+
+############
+# 用户选项 #
+############
+
+Ivtc_core = 1
+## <1|2> ivtc模式
+
+if fps_in < 24.5 or fps_in > 32 :
+	raise Exception("非限定源，已临时禁用该脚本。")
+
+if Ivtc_core == 1 :
+	if fps_in > 24 and fps_in < 26 :
+		output = core.vivtc.VDecimate(clip=input, cycle=25)
+	elif fps_in > 29 and fps_in < 31 :
+		output = core.vivtc.VDecimate(clip=input, cycle=5)
+elif Ivtc_core == 2 :
+	cut0 = core.std.AssumeFPS(clip=input, fpsnum=fps_in * 1000, fpsden=1000)
+	cut1 = core.tivtc.TDecimate(clip=cut0, mode=7, rate=24 / 1.001)
+	output = core.std.AssumeFPS(clip=cut1, fpsnum=24000, fpsden=1001)
+
+output.set_output()

portable_config/vs/nlmeans_cuda.vpy

@@ -15,7 +15,7 @@ Blur_mode = 2
 Frame_num = 1
 Radius_sw = 2
 Radius_snw = 2
-Strength = 3
+Strength = 3.0
 GPU = 0
 GPU_t = 2
 ## <0|1|2> 分离模式。0为不使用
@@ -42,11 +42,11 @@ elif Blur_mode == 2 :
 if Blur_mode :
 	diff = core.std.MakeDiff(clipa=cut0, clipb=blur)
 	cut1 = core.nlm_cuda.NLMeans(clip=diff, d=Frame_num, a=Radius_sw, s=Radius_snw, h=Strength,
-		channels="AUTO", wmode=2, wref=1, rclip=None, device_id=GPU, num_streams=GPU_t)
+		channels="AUTO", wmode=2, wref=1.0, rclip=None, device_id=GPU, num_streams=GPU_t)
 	merge = core.std.MergeDiff(clipa=blur, clipb=cut1)
 else :
 	cut1 = core.nlm_cuda.NLMeans(clip=blur, d=Frame_num, a=Radius_sw, s=Radius_snw, h=Strength,
-		channels="AUTO", wmode=2, wref=1, rclip=None, device_id=GPU, num_streams=GPU_t)
+		channels="AUTO", wmode=2, wref=1.0, rclip=None, device_id=GPU, num_streams=GPU_t)
 
 output = core.resize.Bilinear(clip=merge if Blur_mode else cut1, format=fmt_in)
 

portable_config/vs/nlmeans_std.vpy

@@ -16,9 +16,9 @@ Nlm_core = 1
 Frame_num = 1
 Radius_sw = 2
 Radius_snw = 2
-Strength = 3
+Strength = 3.0
 GPU = 0
-## 分离模式 1=RemoveGrain // 2=Convolution
+## <0|1|2> 分离模式。0为不使用
 ## 降噪核心 1=OpenCL // 2=cpu
 ## 降噪帧数（整数）
 ## 搜索窗口半径（整数）
@@ -28,23 +28,34 @@ GPU = 0
 
 cut0 = core.resize.Bilinear(clip=input, format=vs.YUV444P16)
 
-if Blur_mode == 1 :
-	blur1 = core.rgvs.RemoveGrain(clip=cut0, mode=20)
-	blur2 = core.rgvs.RemoveGrain(clip=blur1, mode=20)
-	blur3 = core.rgvs.RemoveGrain(clip=blur2, mode=20)
-if Blur_mode == 2 :
-	blur1 = core.std.Convolution(clip=cut0, matrix=[1, 1, 1, 1, 1, 1, 1, 1, 1])
-	blur2 = core.std.Convolution(clip=blur1, matrix=[1, 1, 1, 1, 1, 1, 1, 1, 1])
-	blur3 = core.std.Convolution(clip=blur2, matrix=[1, 1, 1, 1, 1, 1, 1, 1, 1])
-
-diff = core.std.MakeDiff(clipa=cut0, clipb=blur3)
-
-if Nlm_core == 1 :
-	cut1 = core.knlm.KNLMeansCL(clip=diff, d=Frame_num, a=Radius_sw, s=Radius_snw, h=Strength, wmode=2, device_type="GPU", device_id=GPU)
-if Nlm_core == 2 :
-	cut1 = core.nlm_ispc.NLMeans(clip=diff, d=Frame_num, a=Radius_sw, s=Radius_snw, h=Strength, wmode=2)
-
-merge = core.std.MergeDiff(clipa=blur3, clipb=cut1)
-output = core.resize.Bilinear(clip=merge, format=fmt_in)
+if Blur_mode == 0 :
+	blur = cut0
+elif Blur_mode == 1 :
+	blur = core.rgvs.RemoveGrain(clip=cut0, mode=20)
+	blur = core.rgvs.RemoveGrain(clip=blur, mode=20)
+	blur = core.rgvs.RemoveGrain(clip=blur, mode=20)
+elif Blur_mode == 2 :
+	blur = core.std.Convolution(clip=cut0, matrix=[1, 1, 1, 1, 1, 1, 1, 1, 1])
+	blur = core.std.Convolution(clip=blur, matrix=[1, 1, 1, 1, 1, 1, 1, 1, 1])
+	blur = core.std.Convolution(clip=blur, matrix=[1, 1, 1, 1, 1, 1, 1, 1, 1])
+
+if Blur_mode :
+	diff = core.std.MakeDiff(clipa=cut0, clipb=blur)
+	if Nlm_core == 1 :
+		cut1 = core.knlm.KNLMeansCL(clip=diff, d=Frame_num, a=Radius_sw, s=Radius_snw, h=Strength,
+			channels="auto", wmode=2, wref=1.0, rclip=None, device_type="GPU", device_id=GPU)
+	elif Nlm_core == 2 :
+		cut1 = core.nlm_ispc.NLMeans(clip=diff, d=Frame_num, a=Radius_sw, s=Radius_snw, h=Strength,
+			channels="AUTO", wmode=2, wref=1.0, rclip=None)
+	merge = core.std.MergeDiff(clipa=blur, clipb=cut1)
+else :
+	if Nlm_core == 1 :
+		cut1 = core.knlm.KNLMeansCL(clip=blur, d=Frame_num, a=Radius_sw, s=Radius_snw, h=Strength,
+			channels="auto", wmode=2, wref=1.0, rclip=None, device_type="GPU", device_id=GPU)
+	elif Nlm_core == 2 :
+		cut1 = core.nlm_ispc.NLMeans(clip=blur, d=Frame_num, a=Radius_sw, s=Radius_snw, h=Strength,
+			channels="AUTO", wmode=2, wref=1.0, rclip=None)
+
+output = core.resize.Bilinear(clip=merge if Blur_mode else cut1, format=fmt_in)
 
 output.set_output()