![]() ![]() # but if you want get the return at the same time, # subprocess.call or os.popen can get the call's return, ![]() Run call in python(win 10): input = 'a.mkv'Ĭall = "echo y|ffmpeg -r 25 -i \"%s\" -vcodec h264_nvenc \"%s\"" % (input, output) If that not work, you can try else gpu accelerators: -vcodec My gpu type is nvida, and I got 10 times faster with this command.Įcho y|ffmpeg -r 25 -i "a.mkv" -vcodec h264_nvenc "b.mp4" Video = concatenate_videoclips(clips, method='compose') Txt_mov = txt_col.set_pos(lambda t: (max(w / 30, int(w - 0.5 * w * t)),įinal=CompositeVideoClip() Txt = TextClip(txt=self.arrNames, font='Amiri-regular', TempVideo=VideoFileClip(self.path + "\\" + filename) The code doesnt realy matter but : def Edit_Clips(self):įor i,filename in enumerate(os.listdir(self.path)): My CPU is very strong (i7 10700k), but still, rendering on moviepy takes me for a compilation with a total of 8 minutes 40 seconds, which is a lot. I tried using thread=4 and thread=16 but they are still very very slow and didn't change much. I didn't find an answer to that on the web, so I hope that some of you can help me. Is there a way to improve the speed by running the writing of moviepy on GPU? Like using FFmpeg or something like this? I'm working on something that concatenate videos and adds some titles on through moviepy.Īs I saw on the web and on my on pc moviepy works on the CPU and takes a lot of time to save(render) a movie.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |