v21.7.8

[bmaltais]

• Add tkinter to dockerised version (thanks to @burdokow)
• Add option to create caption files from folder names to the group_images.py tool.
• Prodigy optimizer is supported in each training script. It is a member of D-Adaptation and is effective for DyLoRA training. PR #585 Please see the PR for details. Thanks to sdbds!
  • Install the package with pip install prodigyopt. Then specify the option like --optimizer_type="prodigy".
• Arbitrary Dataset is supported in each training script (except XTI). You can use it by defining a Dataset class that returns images and captions.
  • Prepare a Python script and define a class that inherits train_util.MinimalDataset. Then specify the option like --dataset_class package.module.DatasetClass in each training script.
  • Please refer to MinimalDataset for implementation. I will prepare a sample later.
• The following features have been added to the generation script.
  • Added an option --highres_fix_disable_control_net to disable ControlNet in the 2nd stage of Highres. Fix. Please try it if the image is disturbed by some ControlNet such as Canny.
  • Added Variants similar to sd-dynamic-propmpts in the prompt.
    • If you specify {spring|summer|autumn|winter}, one of them will be randomly selected.
    • If you specify {2$$chocolate|vanilla|strawberry}, two of them will be randomly selected.
    • If you specify {1-2$$ and $$chocolate|vanilla|strawberry}, one or two of them will be randomly selected and connected by and.
    • You can specify the number of candidates in the range 0-2. You cannot omit one side like -2 or 1-.
    • It can also be specified for the prompt option.
    • If you specify e or E, all candidates will be selected and the prompt will be repeated multiple times (--images_per_prompt is ignored). It may be useful for creating X/Y plots.
    • You can also specify --am {e$$0.2|0.4|0.6|0.8|1.0},{e$$0.4|0.7|1.0} --d 1234. In this case, 15 prompts will be generated with 5*3.
    • There is no weighting function.