Mirrors_Framework/FSRCNN-TensorFlow
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Adjust deconvolution filter size for different scaling factors

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igv
2017-09-01 14:14:27 +03:00
parent f8af70e011
commit 5346bcf898
1 changed files with 4 additions and 1 deletions
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5
model.py
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@@ -48,6 +48,8 @@ class FSRCNN(object):
# Different model layer counts and filter sizes for FSRCNN vs FSRCNN-s (fast), (d, s, m) in paper
model_params = [[56, 12, 4], [32, 8, 1]]
self.model_params = model_params[self.fast]
self.deconv_radius = [3, 5, 7][self.scale - 2]
self.checkpoint_dir = config.checkpoint_dir
self.output_dir = config.output_dir
@@ -65,11 +67,12 @@ class FSRCNN(object):
d, s, m = self.model_params
expand_weight, deconv_weight = 'w{}'.format(m + 3), 'w{}'.format(m + 4)
deconv_size = self.deconv_radius * 2 + 1
self.weights = {
'w1': tf.Variable(tf.random_normal([5, 5, 1, d], stddev=0.0378, dtype=tf.float32), name='w1'),
'w2': tf.Variable(tf.random_normal([1, 1, d, s], stddev=0.3536, dtype=tf.float32), name='w2'),
expand_weight: tf.Variable(tf.random_normal([1, 1, s, d], stddev=0.189, dtype=tf.float32), name=expand_weight),
deconv_weight: tf.Variable(tf.random_normal([9, 9, 1, d], stddev=0.0001, dtype=tf.float32), name=deconv_weight)
deconv_weight: tf.Variable(tf.random_normal([deconv_size, deconv_size, 1, d], stddev=0.0001, dtype=tf.float32), name=deconv_weight)
}
expand_bias, deconv_bias = 'b{}'.format(m + 3), 'b{}'.format(m + 4)