[Research Project] Add AnyText: Multilingual Visual Text Generation And Editing

[tolgacangoz]

Thanks for the opportunity to fix #6407!

AnyText comprises a diffusion pipeline with two primary elements: an auxiliary latent module and a text embedding module. The former uses inputs like text glyph, position, and masked image to generate latent features for text generation or editing. The latter employs an OCR model for encoding stroke data as embeddings, which blend with image caption embeddings from the tokenizer to generate texts that seamlessly integrate with the background. We employed text-control diffusion loss and text perceptual loss for training to further enhance writing accuracy.

Paper: AnyText: Multilingual Visual Text Generation And Editing
Repository: https://github.com/tyxsspa/AnyText
Hugging Face Space: modelscope/AnyText

TODOs:
⏳ AuxiliaryLatentModule
✅ AnyTextControlNetModel -> Inherited and adapted from ControlNetModel. The only difference is that using Gylph Block, Position Block, and Fuse Block instead of input_hint_block or controlnet_cond_embedding from an ordinary ControlNet -ControlNetConditioningEmbedding is different. I deactivated the ControlNetConditioningEmbedding part and moved the new blocks into AuxiliaryLatentModule just to comply with the Figure.
⏳ AnyTextPipeline -> Adapted from StableDiffusionControlNetPipeline.
⏳ TextEmbeddingModule -> Replaces the encode_prompt() function. I may transfer what TextEmbeddingModule does into encode_prompt().
✅ convert_anytext_to_diffusers.py
⏳ Verify outputs with the original implementation
⏳ Finish HF integration & upload converted checkpoints to HF
⏳ README.md
⬜ Make it as simple as possible, but not simpler

[HuggingFaceDocBuilderDev]

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