* Smart Masks - Training
- Reinstate smart mask training code
- Reinstate mask_type back to model.config
- change 'replicate_input_mask to 'learn_mask'
- Add learn mask option
- Add mask loading from alignments to plugins.train.trainer
- Add mask_blur and mask threshold options
- _base.py - Pass mask options through training_opts dict
- plugins.train.model - check for mask_type not None for learn_mask and penalized_mask_loss
- Limit alignments loading to just those faces that appear in the training folder
- Raise error if not all training images have an alignment, and alignment file is required
- lib.training_data - Mask generation code
- lib.faces_detect - cv2 dimension stripping bugfix
- Remove cv2 linting code
* Update mask helptext in cli.py
* Fix Warp to Landmarks
Remove SHA1 hashing from training data
* Update mask training config
* Capture missing masks at training init
* lib.image.read_image_batch - Return filenames with batch for ordering
* scripts.train - Documentation
* plugins.train.trainer - documentation
* Ensure backward compatibility.
Fix convert for new predicted masks
* Update removed masks to components for legacy models.
- Add new serializers (npy + compressed)
- Remove Serializer option from cli
- Revert get_aligned call in scripts/extract
- Default alignments to compressed
- Size masks to 128px and compress
- Remove mask thresholding/blur from generation code
- Add Mask class to lib/faces_detect
- Revert debug landmarks to aligned face
- Revert non-extraction code to staging version
