vt-vl-lab / FGVC

[ECCV 2020] Flow-edge Guided Video Completion
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CalledProcessError: died with <Signals.SIGKILL: 9>. #14

Closed GrahamboJangles closed 3 years ago

GrahamboJangles commented 3 years ago

Trying

%%shell
cd FGVC
cd tool
python /content/FGVC/tool/video_completion.py \
       --mode video_extrapolation \
       --path /content/FGVC/data/tennis \
       --outroot /content/FGVC/result/tennis_extrapolation \
       --H_scale 2 \
       --W_scale 2 \
       #--seamless

in Google Colab returns:

Pytorch 1.6.0 for flow prediction

Finish Calculating flow.
tcmalloc: large alloc 1651507200 bytes == 0x117076000 @  0x7fb727903001 0x7fb71bdac765 0x7fb71be10bb0 0x7fb71be12a4f 0x7fb71bea9048 0x50a7f5 0x50cfd6 0x509918 0x50a64d 0x50c1f4 0x509918 0x50a64d 0x50c1f4 0x509918 0x50a64d 0x50c1f4 0x507f24 0x50b053 0x634dd2 0x634e87 0x63863f 0x6391e1 0x4b0dc0 0x7fb7274feb97 0x5b26fa
Completing forward flow  0 <--->  1
tcmalloc: large alloc 1767358464 bytes == 0x7fb589f70000 @  0x7fb7279011e7 0x7fb6c1382f9a 0x7fb6c1395254 0x7fb6c1395753 0x7fb6c13932f2 0x7fb6c13930a9 0x7fb6c1382a48 0x50a7f5 0x50cfd6 0x507f24 0x509c50 0x50a64d 0x50c1f4 0x509918 0x50a64d 0x50c1f4 0x507f24 0x509c50 0x50a64d 0x50c1f4 0x507f24 0x509c50 0x50a64d 0x50c1f4 0x509918 0x50a64d 0x50c1f4 0x509918 0x50a64d 0x50c1f4 0x507f24
tcmalloc: large alloc 1767358464 bytes == 0x7fb5209f4000 @  0x7fb7279011e7 0x7fb6c1382f9a 0x7fb6c1395254 0x7fb6c139576a 0x7fb6c13932f2 0x7fb6c13930a9 0x7fb6c1382a48 0x50a7f5 0x50cfd6 0x507f24 0x509c50 0x50a64d 0x50c1f4 0x509918 0x50a64d 0x50c1f4 0x507f24 0x509c50 0x50a64d 0x50c1f4 0x507f24 0x509c50 0x50a64d 0x50c1f4 0x509918 0x50a64d 0x50c1f4 0x509918 0x50a64d 0x50c1f4 0x507f24
tcmalloc: large alloc 1767358464 bytes == 0x7fb4cb160000 @  0x7fb7279011e7 0x7fb6c1382f9a 0x7fb6c1395254 0x7fb6c1395753 0x7fb6c13932f2 0x7fb6c13930a9 0x7fb6c1382a48 0x50a7f5 0x50cfd6 0x507f24 0x509c50 0x50a64d 0x50c1f4 0x509918 0x50a64d 0x50c1f4 0x507f24 0x509c50 0x50a64d 0x50c1f4 0x507f24 0x509c50 0x50a64d 0x50c1f4 0x509918 0x50a64d 0x50c1f4 0x509918 0x50a64d 0x50c1f4 0x507f24
tcmalloc: large alloc 1767358464 bytes == 0x7fb5346dc000 @  0x7fb7279011e7 0x7fb6c1382f9a 0x7fb6c1395254 0x7fb6c139576a 0x7fb6c13932f2 0x7fb6c13930a9 0x7fb6c1382a48 0x50a7f5 0x50cfd6 0x507f24 0x509c50 0x50a64d 0x50c1f4 0x509918 0x50a64d 0x50c1f4 0x507f24 0x509c50 0x50a64d 0x50c1f4 0x507f24 0x509c50 0x50a64d 0x50c1f4 0x509918 0x50a64d 0x50c1f4 0x509918 0x50a64d 0x50c1f4 0x507f24
Completing forward flow  1 <--->  2
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Completing backward flow  0 <--->  1
---------------------------------------------------------------------------
CalledProcessError                        Traceback (most recent call last)
<ipython-input-2-4abcfdc683a5> in <module>()
----> 1 get_ipython().run_cell_magic('shell', '', 'cd FGVC\ncd tool\npython /content/FGVC/tool/video_completion.py \\\n       --mode video_extrapolation \\\n       --path /content/FGVC/data/tennis \\\n       --outroot /content/FGVC/result/tennis_extrapolation \\\n       --H_scale 2 \\\n       --W_scale 2 \\\n       #--seamless')

2 frames
/usr/local/lib/python3.6/dist-packages/google/colab/_system_commands.py in check_returncode(self)
    136     if self.returncode:
    137       raise subprocess.CalledProcessError(
--> 138           returncode=self.returncode, cmd=self.args, output=self.output)
    139 
    140   def _repr_pretty_(self, p, cycle):  # pylint:disable=unused-argument

CalledProcessError: Command 'cd FGVC
cd tool
python /content/FGVC/tool/video_completion.py \
       --mode video_extrapolation \
       --path /content/FGVC/data/tennis \
       --outroot /content/FGVC/result/tennis_extrapolation \
       --H_scale 2 \
       --W_scale 2 \
       #--seamless' died with <Signals.SIGKILL: 9>.
gaochen315 commented 3 years ago

Can you try removing #--seamless? Just run

python /content/FGVC/tool/video_completion.py \
       --mode video_extrapolation \
       --path /content/FGVC/data/tennis \
       --outroot /content/FGVC/result/tennis_extrapolation \
       --H_scale 2 \
       --W_scale 2
GrahamboJangles commented 3 years ago

@gaochen315 This is an old issue that I believe was fixed in the new Colab notebook. Thank you though, for trying to help.