PS. Its my first attempt to implement a paper, so please bear with me in case i do/say something really stupid
Can someone help me with this one?
Hi all,
I was trying to implement the model as defined here in this FSRCNN(scroll a bit down until the headline says FSRCNN), but i am pretty sure i messed up with the structure in the end,
Can someone invest their spare time to help me as to where i am wrong?
Thanks,
Aditya.
The problem is that the loss is not decreasing at all…(due to structural defects at the end…)
Also I am getting list index out of range error while trying to apply Deconv op
The dataset
here's the traceback
IndexError Traceback (most recent call last)
<ipython-input-10-5c97c0961611> in <module>()
----> 1 train_cnn(X)
<ipython-input-9-da512eedc9e1> in train_cnn(X)
1 def train_cnn(X):
----> 2 prediction = CNN(X)
3 #mse
4 loss = tf.reduce_mean(tf.pow(tf.subtract(prediction, Y), 2.0))
5 #optimizer
<ipython-input-8-34dbf6cd2f6a> in CNN(X)
74 have a look at the link below...
75 '''
---> 76 op_image = tf.nn.conv2d_transpose(c0, filter = [9, 9, 56, 12], output_shape = [1,320,480,1], strides=[1,2,2,1],padding='same',name='deconv')
77
78 return op_image
C:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\ops\nn_ops.py in conv2d_transpose(value, filter, output_shape, strides, padding, data_format, name)
1017 filter = ops.convert_to_tensor(filter, name="filter")
1018 axis = 3 if data_format == "NHWC" else 1
-> 1019 if not value.get_shape()[axis].is_compatible_with(filter.get_shape()[3]):
1020 raise ValueError("input channels does not match filter's input channels, "
1021 "{} != {}".format(value.get_shape()[3], filter.get_shape(
C:\ProgramData\Anaconda3\lib\site-packages\tensorflow\python\framework\tensor_shape.py in __getitem__(self, key)
498 return TensorShape(self._dims[key])
499 else:
--> 500 return self._dims[key]
501 else:
502 if isinstance(key, slice):
IndexError: list index out of range
I tried to implement it as given in the stack’s link…