Comments (5)
@sydney0zq Yes you're right. The first conv
should also be counted. Thus the total number of layers should be 9*3*3 + 3 = 84
.
BTW, preresnet.py
was just used for debugging at the beginning. It has never been evaluated for human pose estimation. You should try the hourglass
model instead.
from pytorch-pose.
@bearpaw
Thanks for your check.
And another question in models/hourglass.py
. It may be not an issue, the origin code in Lua puzzles me a lot.
I made several trials on this hourglass. Hourglass._make_hour_glass
actually construct a model which may be like:
When I set depth=1
, one time of Upsampling and Downsampling operation will be forwarded. So it means that depth
controls the Upsampling and Downsampling times?
I am just a novice of pose-estimation, so thanks a lot.
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Yes. The 64x64
feature maps will be down sampled by 2^depth
times and then upsampled to the original resolution (64x64
).
from pytorch-pose.
Hey, thanks for your patience.
But, hmmmmmm, I still have some points that I could not understand. Weeeeell, one more question
in eval_PCKh.m
% 0 - r ankle, 1 - r knee, 2 - r hip, 3 - l hip, 4 - l knee,
% 5 - l ankle, 6 - pelvis, 7 - thorax, 8 - upper neck, 9 - head top,
% 10 - r wrist, 11 - r elbow, 12 - r shoulder, 13 - l shoulder,
% 14 - l elbow, 15 - l wrist
pa = [2, 3, 7, 7, 4, 5, 8, 9, 10, 0, 12, 13, 8, 8, 14, 15];
in showskeletons_joints.m
:
for child = 1:p_no
if pa(child) == 0 % removed pa == 1, I think unnecessary
continue;
end
x1 = x(pa(child));
y1 = y(pa(child));
x2 = x(child);
y2 = y(child);
plot(x1, y1, 'o', 'color', partcolor{child}, ...
'MarkerSize', msize, 'MarkerFaceColor', partcolor{child});
plot(x2, y2, 'o', 'color', partcolor{child}, ...
'MarkerSize', msize, 'MarkerFaceColor', partcolor{child});
line([x1 x2], [y1, y2], 'color', partcolor{child}, 'linewidth', round(msize/2));
end
What pa
corrsponds for?
e.g. When we use pa(i)
, we take the pair joint of i
? If it is, then upper neck
may have two pairs, one for the head and the other for the thorax. Could you explain some mechanism about it?
Thanks again.
from pytorch-pose.
pa means the parent node of the current node. It determines which two body joints should be linked.
from pytorch-pose.
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