Error while executing firenet.py- TensorFlow 2.0

[grtdeveloper]

while issuing command python3 firenet.py models/test.mp4 got the following error.
All necessary packages are installed.

import tflearn
File "/usr/local/lib/python3.6/dist-packages/tflearn/init.py", line 4, in
from . import config
File "/usr/local/lib/python3.6/dist-packages/tflearn/config.py", line 5, in
from .variables import variable
File "/usr/local/lib/python3.6/dist-packages/tflearn/variables.py", line 7, in
from tensorflow.contrib.framework.python.ops import add_arg_scope as contrib_add_arg_scope
File "/usr/local/lib/python3.6/dist-packages/tensorflow/contrib/init.py", line 27, in
from tensorflow.contrib import cudnn_rnn
File "/usr/local/lib/python3.6/dist-packages/tensorflow/contrib/cudnn_rnn/init.py", line 28, in
from tensorflow.contrib.cudnn_rnn.python.ops.cudnn_rnn_ops import CudnnGRU
File "/usr/local/lib/python3.6/dist-packages/tensorflow/contrib/cudnn_rnn/python/ops/cudnn_rnn_ops.py", line 21, in
from tensorflow.contrib.cudnn_rnn.ops import gen_cudnn_rnn_ops
File "/usr/local/lib/python3.6/dist-packages/tensorflow/contrib/cudnn_rnn/ops/gen_cudnn_rnn_ops.py", line 940, in
_op_def_lib = _InitOpDefLibrary()
File "/usr/local/lib/python3.6/dist-packages/tensorflow/contrib/cudnn_rnn/ops/gen_cudnn_rnn_ops.py", line 365, in _InitOpDefLibrary
_op_def_registry.register_op_list(op_list)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/framework/op_def_registry.py", line 35, in register_op_list
assert _registered_ops[op_def.name] == op_def
AssertionError

Computing Environment (please complete the following information):

• Linux Ubuntu 17.10
• Tensorflow Version: 2.0
• OpenCV Version: 3.3.1

[tobybreckon]

In essence we do not (and cannot easily) support TensorFlow 2.0 because TFlearn, which this project is based upon, is not available with TensorFlow > 1.15 (google: "tensorflow 2.0 tflearn" for the background).

As you an see - your failure is at the import tflearn line even before you get to the code specific to this project.

[ Why did we use TFlearn ? - because it was 2017 and Pytorch et al., was not mature enough yet and this was the goto "easy to use" package for this type of work ]

A workflow to make this repo work on your system is via a Tensorflow 1 virtual environment. Install the required packages for virtualenv on Linux Ubuntu 18.10 and then ...

virtualenv --system-site-packages -p python3 ./venv/tf-1.1.5-gpu
source ~/venv/tf-1.1.5-gpu/bin/activate
pip install tensorflow-gpu==1.15
pip install tflearn
....
python3 firenet.py models/test.mp4

I am more than happy to be corrected if someone can post a pull request for a set of TF 2.0 fixes (but as far as I can tell the complexity of such a fix is way beyond the TF 1.x -> TF 2.x translation scripts etc).