HuangRuixiao 发表于 2020-12-11 22:38:13

HuangRuixiao 发表于 2020-12-11 22:28
在"mvtools-blksize64"中发现以下两行包含相关关键字
是把下面一行的Block改成Flow还是把下一行直接换成上 ...

实测直接把BlockFPS改成FlowFPS后脚本不在正常工作
只能用启用
clip = core.mv.FlowFPS(clip,_super,mvbw,mvfw,num=dfps,den=vden,mask=0,ml=100.0,thscd1=970,thscd2=255,blend=False)而注释掉
clip = core.mv.BlockFPS(clip,_super,mvbw,mvfw,num=dfps,den=vden,mode=2,ml=100.0,thscd1=970,thscd2=255,blend=False)的办法
实测两种配置的资源占用如下:

Starlight 发表于 2020-12-11 23:54:32

本帖最后由 Starlight 于 2020-12-11 23:55 编辑

HuangRuixiao 发表于 2020-12-11 22:28
在"mvtools-blksize64"中发现以下两行包含相关关键字
是把下面一行的Block改成Flow还是把下一行直接换成上 ...
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
把81行前面的#移到第82行
应该是这样


没事了

Starlight 发表于 2020-12-12 00:10:08

本帖最后由 Starlight 于 2020-12-12 00:11 编辑

flow

block

图为 奥特赛文1998OV 01 遗失的记忆 19:20秒左右 的高速运动、高对比度直线烟花

import vapoursynth as vs

core = vs.core
clip = video_in
clip = core.std.AssumeFPS(clip, fpsnum=container_fps, fpsden=1)
mvsu = core.mv.Super(clip)
mvbw = core.mv.Analyse(mvsu, isb=True)
mvfw = core.mv.Analyse(mvsu, isb=False)
clip = core.mv.FlowFPS(clip, mvsu, mvbw, mvfw, num=display_fps)
# clip = core.mv.BlockFPS(clip, mvsu, mvbw, mvfw, num=display_fps)
clip.set_output()我的简朴vpy
不是很严谨的测试

我的结论:
flow插值的画面会看起来更流畅但画面有扭曲的现象
block插值的画面会有块状缺陷




页: 1 [2]
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