Multiplanarunet

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* Simplified the functionality of the Validation callback so that it now only
computes the F1/Dice, precision and recall scores. I.e. the callback no longer
computes validation metrics. This choice was made to increase stability between
TensorFlow versions. The callback should work for most versions of TF now, incl.
TF 2.0. Future versions of MultiPlanarUNet will re-introduce validation metrics
in a TF 2.0 only setting.
* Various smaller changes across the code

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* Process has started to re-factor/re-write scripts in the bin module to make
them clearer, remove deprecated command-line arguments etc.
* Evaluation results as stored in .csv files are now always saved and loaded
with an index column as the first column of the file.

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* Various smaller changes and bug-fixes across the code base. Thread pools are now
generally limited to a maximum of 7 threads; The cv_experiment script now correctly
handles using the 'mp' script entry point in the 'script' file (before full paths
to the given script had to be passed to the python interpreter)

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* MultiChannelScaler now ignores values equal to or smaller than the 'bg_value'
for each channel separately.
This value is either set manually by the user and must be a list of values
equal to the number of channels or a single value (that will be applied to
all channels). If bg_value='1pct' is specified (default for most models), or
any other percentage following this specification ('2pct' for 2 percent etc),
the 1st percentile will be computed for each channel individually and used
to define the background value for that channel.
* ViewInterpolator similarly now accepts a channel-wise background value
specification, so that bg_value=[0, 0.1, 1] will cause out-of-bounds
interpolation to generate a pixel of value [0, 0.1, 1] for a 3-channel image.
Before, all channels would share a single, global background value (this
effect is still obtained if bg_value is set to a single integer or float).
* Note that these changes may affect performance negatively if using the v 0.2
software on projects with models trained with version <0.2.0. Users will be
warned if trying to do so.
* v0.2.0 now checks which MultiPlanarUNet version was used to create/run code
in a give project. Using a new version of the software on an older project
folder is no longer allowed. This behaviour may however be overwritten
manually setting the __VERSION__ variable to the current software version in
the hyperparamter file of the project (not recommended, instead, downgrade
to a previous version by running 'git checkout v<VERSION>' inside the
MultiPlanarUNet code folder).

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* Minor changes over 0.1.3, including ability to set a pre-specified set of
GPUs to cycle in mp cv_experiment

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* One-hot encoded targets (set with sparse=False in the fit section of
hyperparameter file) are no longer supported. Setting this value no longer
has any effect and may not be allowed in future versions.
* The Validation callback has been changed significantly and now computes both
loss and any metrics specified in the hyperparamter file as performed on the
training set to facility a more easy comparison. Note that as is the case on
the training set, these computations are averaged batch-wise metrics.
The CB still computes the epoch-wise pr-class and average precision,
recall and dice.
* Default parameter files no longer have pre-specified metrics. Metrics (such
as categorical accuracy, fg_precision, etc.) must be manually specified.