When I run either the eval or vis script I am given the error ensorflow.python.framework.errors_impl.InvalidArgumentError: padded_shape[0]=86 is not divisible by block_shape[0]=6
and tensorflow.python.framework.errors_impl.InvalidArgumentError: padded_shape[0]=86 is not divisible by block_shape[0]=6 respectively.
I am really new to all things TF and this has really stumped me - is it something that others have come across?
I have detailed the error in full on my repo - which I have modelled on this one.
Rosie-Brigham/fun-with-deeplab#1
Any help on this gratefully received!
Further info:
system information
What is the top-level directory of the model you are using:
DeepLab v3+
Have I written custom code (as opposed to using a stock example script provided in TensorFlow):
Yes, I have written some code to train a pretrained model with new images
OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
Mac OS Catalina
TensorFlow installed from (source or binary):
With pip3 binary installation
TensorFlow version (use command below):
1.15.0 CPU only
CUDA/cuDNN version:
Not used
GPU model and memory:
Not used
When I run either the
evalorvisscript I am given the errorensorflow.python.framework.errors_impl.InvalidArgumentError: padded_shape[0]=86 is not divisible by block_shape[0]=6and
tensorflow.python.framework.errors_impl.InvalidArgumentError: padded_shape[0]=86 is not divisible by block_shape[0]=6respectively.I am really new to all things TF and this has really stumped me - is it something that others have come across?
I have detailed the error in full on my repo - which I have modelled on this one.
Rosie-Brigham/fun-with-deeplab#1
Any help on this gratefully received!
Further info:
system information
What is the top-level directory of the model you are using:
DeepLab v3+
Have I written custom code (as opposed to using a stock example script provided in TensorFlow):
Yes, I have written some code to train a pretrained model with new images
OS Platform and Distribution (e.g., Linux Ubuntu 16.04):
Mac OS Catalina
TensorFlow installed from (source or binary):
With pip3 binary installation
TensorFlow version (use command below):
1.15.0 CPU only
CUDA/cuDNN version:
Not used
GPU model and memory:
Not used