Quevedo

This is a minor release with bug fixes and general quality of life improvements.

New dataset version 2

There are four annotation schemas now, one for graphemes, one for logograms,
another one for graph edges, and a final one for meta tags. The logogram
annotation schema is new, but previously this information could be stored in
the meta tags (now they are separate). See below for more about graphs. The new
dataset version in not compatible, so existing datasets need to be migrated.

Logogram graphs

Logograms can now store a graph which connects bound graphemes with edges. These
edges have their own tags and tag schema, and can be used to capture the
compositional or spatial relations between bound graphemes. The dataset
configuration has been updated, as well as the web interface, to allow
annotating these new values.

Other

- Configuration dictionaries are now merged instead of replaced in network, pipeline and dataset configs.
- "Extend" configurations can be chained.
- In the web interface listing, annotations can be filtered according to flags.
- The color list to use in the logogram editor can now be customized.
- Other bug fixes and documentation

Pipelines

There are now Pipeline objects in Quevedo, which combine trained neural networks
into complex systems able to perform more complicated tasks. See the
[documentation](https://agarsev.github.io/quevedo/latest/pipes/) for more.

Other

- When creating an in-memory annotation, convert image to RGB.
- Remember last function selected in the web app edit page.
- If config key darknet.shutup is false, no stdio redirection is done.
- Allow in-memory images for annotations.
- Lambda function as pipeline step and improved test command.
- Global default config value substitutes default config per net.
- Simplified evaluation code: overall, detection and classification accuracy.
- Add an "extend" key to net configs to allow sharing config values.
- Improve user scripts init function.
- Use Graphemes and Logograms instead of dicts.
- Improved test command with more info and better algos.
- Allow training detector with "no" tag (same tag for every object).
- Allow use of relative paths for darknet library.
- Other bug fixes.
- Added example toy arithmetic dataset to the repo.

New dataset version 1

Before, Quevedo datasets were not versioned. Now, a field has been added to the
`config.toml` file to track the Quevedo dataset schema, and a `migrate` command
has been added to let users upgrade datasets to new versions.

Some of the following additions are incompatible changes to dataset
functionality and annotation files which have made this version upgrading
necessary.

Tags are now a dictionary

Grapheme tags (both free and bound) are now represented with a dictinary, with
keys the names in the dataset `tag_schema`. This makes Annotation objects easier
to use in custom code. The change affects both the library code and the files on
disk, hence the migration.

Splitting now works differently

Instead of assigning annotations to either a train or test split, they are
assigned to a "fold". Groups of folds can then be defined as being available for
train or for test (or none). This is also an incompatible change to annotation
code and file representation. Old partitions will be lost, so after migration
you will need to run the `split` command again.

Net configuration improvements

- Detection networks can now have `width` and `height` parameters to tune
network input size.
- All networks can now have a `max_batches` parameter to customize when to stop
training the net. This can serve to prevent overfitting and shorten training
times.

Annotation flags

A new option "flags" has been added to the `config.toml` file. These flags are
matadata values just like those in `meta_tags`, so assigned to both Logograms
and Free Graphemes. The difference is that they are presented as checkboxes in
the web interface, and shown as icons in annotation listings. This can serve to
quickly mark annotations for annotators, for example if some have dubious or
problematic tags, need some other kind of attention, or simply you want to keep
track of them.

Other

- When building the tag map for darknet, user tags are combined using the ASCII
FS character instead of "_", which can be problematic if tag values in the
dataset contain "_". This is an internal change and user code and data
should not be affected.
- The `dataset.get_network` method now returns the same `Network` object if
called many times with the same network name. This helps save memory, which
in the case of neural networks can be crucial, without requiring the user to
keep the network in their own variable.
- The web interface now can be used with touch on mobile devices.