Upgrade Keras to 2.4.0 to be compatible with Python 3.8

[HiromuHota]

Description of the problems or issues

Is your pull request related to a problem? Please describe.

• Python 3.8 support requires TensorFlow 2.2 or later (https://www.tensorflow.org/install/pip).
• TensorFlow 2.2 or later requires Keras 2.4.0 or later (Keras 2.4 release adds dependency on tensorflow>=2.2.0, which breaks earlier installs keras-team/keras#14129 (comment))

In order for pdftotree to support Python 3.8, its dependency on Keras needs to be 2.4.0 or later.

Does your pull request fix any issue.

Related to #85

Description of the proposed changes

Upgrade Keras to 2.4.0 to be compatible with Python 3.8

Test plan

pdftotree depends on Keras for the vision model.
I'll add a test to make sure the vision model runs without an error and returns results in expected format, but not check the results itself.

Checklist

• I have updated the documentation accordingly.
• I have added tests to cover my changes.
• All new and existing tests passed.
• I have updated the CHANGELOG.md accordingly.

[codecov-io]

Codecov Report

Merging #86 into master will increase coverage by 0.16%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##           master      #86      +/-   ##
==========================================
+ Coverage   65.62%   65.79%   +0.16%     
==========================================
  Files          21       22       +1     
  Lines        2508     2523      +15     
==========================================
+ Hits         1646     1660      +14     
- Misses        862      863       +1     

Flag	Coverage Δ
#unittests	65.79% <100.00%> (+0.16%)	⬆️

Flags with carried forward coverage won't be shown. Click here to find out more.

Impacted Files	Coverage Δ
setup.py	0.00% <ø> (ø)
pdftotree/visual/visual_utils.py	96.92% <100.00%> (+0.09%)	⬆️
tests/test_basic.py	95.08% <100.00%> (+0.08%)	⬆️
tests/test_table_detection.py	100.00% <100.00%> (ø)
pdftotree/utils/pdf/render.py	0.00% <0.00%> (ø)
pdftotree/utils/pdf/vector_utils.py	66.66% <0.00%> (+0.32%)	⬆️

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[lukehsiao]

Thanks!