handwriting text recognition (CNN + LSTM + CTC)
0
$begingroup$
I am trying to understand the following code, which is in python & tensorflow. Im trying to implement a handwriting text recognition. I am referring to the following code here
I dont understand why the RNN output is put through a "atrous_conv2d"
This is the architecture of my model, takes a CNN input and pass into this RNN process and then pass it to a CTC.
def build_RNN(self, rnnIn4d):
rnnIn3d = tf.squeeze(rnnIn4d, axis=[2]) # squeeze remove 1 dimensions, here it removes the 2nd index
n_hidden = 256
n_layers = 2
cells =
for _ in range(n_layers):
cells.append(tf.nn.rnn_cell.LSTMCell(num_units=n_hidden))
stacked = tf.nn.rnn_cell.MultiRNNCell(cells) # combine the 2 LSTMCell created
# BxTxF -> BxTx2H
((fw, bw), _) = tf.nn.bidirectional_dynamic_rnn(cell_fw=stacked, cell_bw=stacked, inputs=rnnIn3d,
dtype=rnnIn3d.dtype)
# BxTxH + BxTxH -> BxTx2H -> BxTx1X2H
concat = tf.expand_dims(tf.concat([fw, bw], 2), 2)
# project output to chars (including blank): BxTx1x2H -> BxTx1xC -> BxTxC
kernel = tf.Variable(tf.truncated_normal([1, 1, n_hidden * 2, len(self.char_list) + 1], stddev=0.1))
rnn = tf.nn.atrous_conv2d(value=concat, filters=kernel, rate=1, padding='SAME')
return tf.squeeze(rnn, axis=[2])
python deep-learning tensorflow
asked 2 days ago
RuvRuv
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0
$begingroup$
I am trying to understand the following code, which is in python & tensorflow. Im trying to implement a handwriting text recognition. I am referring to the following code here
I dont understand why the RNN output is put through a "atrous_conv2d"
This is the architecture of my model, takes a CNN input and pass into this RNN process and then pass it to a CTC.
def build_RNN(self, rnnIn4d):
rnnIn3d = tf.squeeze(rnnIn4d, axis=[2]) # squeeze remove 1 dimensions, here it removes the 2nd index
n_hidden = 256
n_layers = 2
cells =
for _ in range(n_layers):
cells.append(tf.nn.rnn_cell.LSTMCell(num_units=n_hidden))
stacked = tf.nn.rnn_cell.MultiRNNCell(cells) # combine the 2 LSTMCell created
# BxTxF -> BxTx2H
((fw, bw), _) = tf.nn.bidirectional_dynamic_rnn(cell_fw=stacked, cell_bw=stacked, inputs=rnnIn3d,
dtype=rnnIn3d.dtype)
# BxTxH + BxTxH -> BxTx2H -> BxTx1X2H
concat = tf.expand_dims(tf.concat([fw, bw], 2), 2)
# project output to chars (including blank): BxTx1x2H -> BxTx1xC -> BxTxC
kernel = tf.Variable(tf.truncated_normal([1, 1, n_hidden * 2, len(self.char_list) + 1], stddev=0.1))
rnn = tf.nn.atrous_conv2d(value=concat, filters=kernel, rate=1, padding='SAME')
return tf.squeeze(rnn, axis=[2])
python deep-learning tensorflow
asked 2 days ago
RuvRuv
1
New contributor
Ruv is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
add a comment |
0
0
0
$begingroup$
I am trying to understand the following code, which is in python & tensorflow. Im trying to implement a handwriting text recognition. I am referring to the following code here
I dont understand why the RNN output is put through a "atrous_conv2d"
This is the architecture of my model, takes a CNN input and pass into this RNN process and then pass it to a CTC.
def build_RNN(self, rnnIn4d):
rnnIn3d = tf.squeeze(rnnIn4d, axis=[2]) # squeeze remove 1 dimensions, here it removes the 2nd index
n_hidden = 256
n_layers = 2
cells =
for _ in range(n_layers):
cells.append(tf.nn.rnn_cell.LSTMCell(num_units=n_hidden))
stacked = tf.nn.rnn_cell.MultiRNNCell(cells) # combine the 2 LSTMCell created
# BxTxF -> BxTx2H
((fw, bw), _) = tf.nn.bidirectional_dynamic_rnn(cell_fw=stacked, cell_bw=stacked, inputs=rnnIn3d,
dtype=rnnIn3d.dtype)
# BxTxH + BxTxH -> BxTx2H -> BxTx1X2H
concat = tf.expand_dims(tf.concat([fw, bw], 2), 2)
# project output to chars (including blank): BxTx1x2H -> BxTx1xC -> BxTxC
kernel = tf.Variable(tf.truncated_normal([1, 1, n_hidden * 2, len(self.char_list) + 1], stddev=0.1))
rnn = tf.nn.atrous_conv2d(value=concat, filters=kernel, rate=1, padding='SAME')
return tf.squeeze(rnn, axis=[2])
python deep-learning tensorflow
asked 2 days ago
RuvRuv
1
New contributor
Ruv is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
$endgroup$
I am trying to understand the following code, which is in python & tensorflow. Im trying to implement a handwriting text recognition. I am referring to the following code here
I dont understand why the RNN output is put through a "atrous_conv2d"
This is the architecture of my model, takes a CNN input and pass into this RNN process and then pass it to a CTC.
def build_RNN(self, rnnIn4d):
rnnIn3d = tf.squeeze(rnnIn4d, axis=[2]) # squeeze remove 1 dimensions, here it removes the 2nd index
n_hidden = 256
n_layers = 2
cells =
for _ in range(n_layers):
cells.append(tf.nn.rnn_cell.LSTMCell(num_units=n_hidden))
stacked = tf.nn.rnn_cell.MultiRNNCell(cells) # combine the 2 LSTMCell created
# BxTxF -> BxTx2H
((fw, bw), _) = tf.nn.bidirectional_dynamic_rnn(cell_fw=stacked, cell_bw=stacked, inputs=rnnIn3d,
dtype=rnnIn3d.dtype)
# BxTxH + BxTxH -> BxTx2H -> BxTx1X2H
concat = tf.expand_dims(tf.concat([fw, bw], 2), 2)
# project output to chars (including blank): BxTx1x2H -> BxTx1xC -> BxTxC
kernel = tf.Variable(tf.truncated_normal([1, 1, n_hidden * 2, len(self.char_list) + 1], stddev=0.1))
rnn = tf.nn.atrous_conv2d(value=concat, filters=kernel, rate=1, padding='SAME')
return tf.squeeze(rnn, axis=[2])
python deep-learning tensorflow
python deep-learning tensorflow
asked 2 days ago
RuvRuv
1
New contributor
Ruv is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 2 days ago
RuvRuv
1
New contributor
Ruv is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 2 days ago
RuvRuv
1
New contributor
Ruv is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
asked 2 days ago
RuvRuv
1
asked 2 days ago
RuvRuv
1
1
New contributor
Ruv is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
New contributor
Ruv is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
Ruv is a new contributor to this site. Take care in asking for clarification, commenting, and answering.
Check out our Code of Conduct.
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add a comment |
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