Some question about output shape of joint coordinate in cnn-regression
$begingroup$
I have some question about output shape of cnn-regression problem.
Let say I have Image shape with
image shape = (105, 157, 3)
and this image has 14 joint coordinates for each image (14, 3, 10000).
I guess 10000 is the number of pictures
and each joint coordinates looks like
y=array([[145.82985678, 95.5022898 , 1. ],
[111.87785389, 83.38437237, 1. ],
[ 0. , -27.29260682, 0. ],
[146.22287032, 67.62016267, 1. ],
[114.716285 , 89.0394005 , 1. ],
[147.03073148, 90.65512282, 1. ],
[ 0. , -27.29260682, 0. ],
[ 0. , -27.29260682, 0. ],
[ 0. , -27.29260682, 0. ],
[102.99138111, 63.60269094, 1. ],
[107.44553454, 91.85599752, 1. ],
[112.68571505, 118.12240233, 1. ],
[ 95.72063065, 64.38871802, 1. ],
[ 76.74681039, 60.37124629, 1. ]])
If I want to make a neural network then the neural network should have output and output should compare with this y true value
What is the output should shape with?
Which shape do I have to reshape this y true value? and how?
Dataset is from Leeds Sports Dataset (LSP): 11000 training and 1000 testing images from sports activities with challenging in terms of appearance and especially articulations. The majority of people have 150 pixel height. For each person the full body is labeled with total 14 joints.
python deep-learning keras cnn
asked 17 hours ago
kim Yumikim Yumi
92
New contributor
kim Yumi is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
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$endgroup$
add a comment |
$begingroup$
I have some question about output shape of cnn-regression problem.
Let say I have Image shape with
image shape = (105, 157, 3)
and this image has 14 joint coordinates for each image (14, 3, 10000).
I guess 10000 is the number of pictures
and each joint coordinates looks like
y=array([[145.82985678, 95.5022898 , 1. ],
[111.87785389, 83.38437237, 1. ],
[ 0. , -27.29260682, 0. ],
[146.22287032, 67.62016267, 1. ],
[114.716285 , 89.0394005 , 1. ],
[147.03073148, 90.65512282, 1. ],
[ 0. , -27.29260682, 0. ],
[ 0. , -27.29260682, 0. ],
[ 0. , -27.29260682, 0. ],
[102.99138111, 63.60269094, 1. ],
[107.44553454, 91.85599752, 1. ],
[112.68571505, 118.12240233, 1. ],
[ 95.72063065, 64.38871802, 1. ],
[ 76.74681039, 60.37124629, 1. ]])
If I want to make a neural network then the neural network should have output and output should compare with this y true value
What is the output should shape with?
Which shape do I have to reshape this y true value? and how?
Dataset is from Leeds Sports Dataset (LSP): 11000 training and 1000 testing images from sports activities with challenging in terms of appearance and especially articulations. The majority of people have 150 pixel height. For each person the full body is labeled with total 14 joints.
python deep-learning keras cnn
asked 17 hours ago
kim Yumikim Yumi
92
New contributor
kim Yumi is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
$begingroup$
I guess the third coordinate is somehow a label rather than a coordinate location.
$endgroup$
– Vaalizaadeh
17 hours ago
add a comment |
$begingroup$
I have some question about output shape of cnn-regression problem.
Let say I have Image shape with
image shape = (105, 157, 3)
and this image has 14 joint coordinates for each image (14, 3, 10000).
I guess 10000 is the number of pictures
and each joint coordinates looks like
y=array([[145.82985678, 95.5022898 , 1. ],
[111.87785389, 83.38437237, 1. ],
[ 0. , -27.29260682, 0. ],
[146.22287032, 67.62016267, 1. ],
[114.716285 , 89.0394005 , 1. ],
[147.03073148, 90.65512282, 1. ],
[ 0. , -27.29260682, 0. ],
[ 0. , -27.29260682, 0. ],
[ 0. , -27.29260682, 0. ],
[102.99138111, 63.60269094, 1. ],
[107.44553454, 91.85599752, 1. ],
[112.68571505, 118.12240233, 1. ],
[ 95.72063065, 64.38871802, 1. ],
[ 76.74681039, 60.37124629, 1. ]])
If I want to make a neural network then the neural network should have output and output should compare with this y true value
What is the output should shape with?
Which shape do I have to reshape this y true value? and how?
Dataset is from Leeds Sports Dataset (LSP): 11000 training and 1000 testing images from sports activities with challenging in terms of appearance and especially articulations. The majority of people have 150 pixel height. For each person the full body is labeled with total 14 joints.
python deep-learning keras cnn
asked 17 hours ago
kim Yumikim Yumi
92
New contributor
kim Yumi is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
I have some question about output shape of cnn-regression problem.
Let say I have Image shape with
image shape = (105, 157, 3)
and this image has 14 joint coordinates for each image (14, 3, 10000).
I guess 10000 is the number of pictures
and each joint coordinates looks like
y=array([[145.82985678, 95.5022898 , 1. ],
[111.87785389, 83.38437237, 1. ],
[ 0. , -27.29260682, 0. ],
[146.22287032, 67.62016267, 1. ],
[114.716285 , 89.0394005 , 1. ],
[147.03073148, 90.65512282, 1. ],
[ 0. , -27.29260682, 0. ],
[ 0. , -27.29260682, 0. ],
[ 0. , -27.29260682, 0. ],
[102.99138111, 63.60269094, 1. ],
[107.44553454, 91.85599752, 1. ],
[112.68571505, 118.12240233, 1. ],
[ 95.72063065, 64.38871802, 1. ],
[ 76.74681039, 60.37124629, 1. ]])
If I want to make a neural network then the neural network should have output and output should compare with this y true value
What is the output should shape with?
Which shape do I have to reshape this y true value? and how?
Dataset is from Leeds Sports Dataset (LSP): 11000 training and 1000 testing images from sports activities with challenging in terms of appearance and especially articulations. The majority of people have 150 pixel height. For each person the full body is labeled with total 14 joints.
python deep-learning keras cnn
python deep-learning keras cnn
asked 17 hours ago
kim Yumikim Yumi
92
New contributor
kim Yumi is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 17 hours ago
kim Yumikim Yumi
92
New contributor
kim Yumi is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 17 hours ago
kim Yumikim Yumi
92
New contributor
kim Yumi is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 17 hours ago
kim Yumikim Yumi
92
asked 17 hours ago
kim Yumikim Yumi
92
92
New contributor
kim Yumi is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
kim Yumi is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
kim Yumi is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$begingroup$
I guess the third coordinate is somehow a label rather than a coordinate location.
$endgroup$
– Vaalizaadeh
17 hours ago
add a comment |
$begingroup$
I guess the third coordinate is somehow a label rather than a coordinate location.
$endgroup$
– Vaalizaadeh
17 hours ago
$begingroup$
I guess the third coordinate is somehow a label rather than a coordinate location.
$endgroup$
– Vaalizaadeh
17 hours ago
$begingroup$
I guess the third coordinate is somehow a label rather than a coordinate location.
$endgroup$
– Vaalizaadeh
17 hours ago
add a comment |
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$begingroup$
I guess the third coordinate is somehow a label rather than a coordinate location.
$endgroup$
– Vaalizaadeh
17 hours ago