adds new Haruka LoRA
Browse files- haruka/README.md +52 -0
- haruka/chara-haruka-v1b.safetensors +3 -0
- haruka/example-001-v1b.png +3 -0
- haruka/example-002-v1b.png +3 -0
- haruka/example-003-v1b.png +3 -0
- haruka/lora_chara_haruka_v1b_138i9r-5i4r.json +59 -0
- haruka/tagging methodology.md +93 -0
haruka/README.md
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# Igusa Haruka (Blue Archive)
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伊草ハルカ (ブルーアーカイブ) / 이구사 하루카 (블루 아카이브) / 伊草春香 (碧蓝档案)
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[**Download here.**](https://huggingface.co/khanon/lora-training/blob/main/haruka/chara-haruka-v1c.safetensors)
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## Table of Contents
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- [Preview](#preview)
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- [Usage](#usage)
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- [Training](#training)
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- [Revisions](#revisions)
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## Preview
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![Haruka portrait](chara-haruka-v1c.png)
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![Haruka preview 1](example-001b-v1c.png)
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![Haruka preview 2](example-002b-v1c.png)
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![Haruka preview 3](example-003b-v1c.png)
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## Usage
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Use any or all of the following tags to summon Haruka: `haruka, 1girl, halo, short hair with long locks, purple eyes`
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For her normal outfit: `school uniform, hairclip, purple jacket, collared shirt, juliet sleeves, belt, miniskirt, black skirt, boots`
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- The AI is slightly stubborn with Haruka's normal outfit, likely because she doesn't have much art that does not feature long sleeves of some sort.
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- To remove her jacket sleeves, prompt `sleeveless` and use `long sleeves` in the negative prompt.
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- To remove the purple bowtie/tie clip, prompt `collarbone` and use `bowtie` in the negative prompt.
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For her nervous/creepy smile: `nervous smile, nervous, sweat, wavy mouth, [closed mouth:parted lips:0.75]`
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- Use `sanpaku, constricted pupils, crazy eyes, yandere` or similar for more intense expressions.
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[Here is a list of all tags including in the training dataset, sorted by frequency.](all_tags.txt)
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## Training
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*Exact parameters are provided in the accompanying JSON files.*
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- Trained on a set of 143 images.
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- 138 without "multiple views" (9 repeats)
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- 5 "multiple views" (4 repeats)
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- 3 batch size, 4 epochs
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- `(138 * 9 + 5 * 4) / 3 * 4` = 1683 steps
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- 0.083 loss
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- Initially tagged with WD1.4 swin-v2 model. Tags pruned/edited for consistency.
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- [Tagging methodology detailed here.](tagging%20methodology.md)
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- `constant_with_warmup` scheduler
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- 1.5e-5 text encoder LR
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- 1.5e-4 unet LR
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- 1e-5 optimizer LR
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- Used network_dimension 128 (same as usual) / network alpha 128 (default)
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- Resized to 32 after training
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- Training resolution 832x832.
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- Trained without VAE.
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## Revisions
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- v1b (2023-02-18)
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- Initial release.
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haruka/chara-haruka-v1b.safetensors
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version https://git-lfs.github.com/spec/v1
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oid sha256:b751170286f8135cd25ae375a961fb9c9df68df130d4bf3120cebfade8151168
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size 37882638
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haruka/example-001-v1b.png
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Git LFS Details
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haruka/example-002-v1b.png
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Git LFS Details
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haruka/example-003-v1b.png
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Git LFS Details
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haruka/lora_chara_haruka_v1b_138i9r-5i4r.json
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{
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"pretrained_model_name_or_path": "G:/sd/repo/models/Stable-diffusion/nai-animefull-final-pruned.safetensors",
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"v2": false,
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"v_parameterization": false,
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"logging_dir": "",
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"train_data_dir": "G:/sd/training/datasets/haruka/dataset",
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"reg_data_dir": "",
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"output_dir": "G:/sd/lora/trained/chara/haruka",
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"max_resolution": "832,832",
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"learning_rate": "1e-5",
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"lr_scheduler": "constant_with_warmup",
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"lr_warmup": "5",
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"train_batch_size": 3,
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"epoch": "4",
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"save_every_n_epochs": "",
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"mixed_precision": "fp16",
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"save_precision": "fp16",
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"seed": "31337",
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"num_cpu_threads_per_process": 32,
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"cache_latents": true,
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"caption_extension": ".txt",
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"enable_bucket": true,
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"gradient_checkpointing": false,
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"full_fp16": false,
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"no_token_padding": false,
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"stop_text_encoder_training": 0,
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"use_8bit_adam": true,
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"xformers": true,
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"save_model_as": "safetensors",
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"shuffle_caption": true,
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"save_state": false,
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"resume": "",
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"prior_loss_weight": 1.0,
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"text_encoder_lr": "1.5e-5",
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"unet_lr": "1.5e-4",
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"network_dim": 128,
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"lora_network_weights": "",
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"color_aug": false,
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"flip_aug": false,
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"clip_skip": 2,
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"gradient_accumulation_steps": 1.0,
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"mem_eff_attn": false,
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"output_name": "chara-haruka-v1b-128",
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"model_list": "",
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"max_token_length": "150",
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"max_train_epochs": "",
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"max_data_loader_n_workers": "",
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"network_alpha": 128,
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"training_comment": "Character: `haruka, 1girl, halo, short hair with long locks, purple eyes`\nStandard outfit: `hairclip, garrison cap, purple jacket, collared shirt, black skirt, miniskirt, black belt, boots`\nNew Year alt: `kimono skirt, purple kimono, floral print, purple hairband, hair flower, wide sleeves, obi, geta, tabi`\nNervous expression: `nervous, sweat, wavy mouth`\nVaguely yandere-like smile: `naughty face, nervous smile`\nFlustered: `sanpaku, wide-eyed, shaded face, flustered`\n\nNot all tags are necessary.\n\n(138 normal * 9 repeats + 5 multipleviews * 4 repeats) / 3 batch size * 4 epochs = 1683 steps",
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"keep_tokens": 2,
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"lr_scheduler_num_cycles": "",
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"lr_scheduler_power": "",
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"persistent_data_loader_workers": true,
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"bucket_no_upscale": true,
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"random_crop": false,
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"bucket_reso_steps": 64.0,
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"caption_dropout_every_n_epochs": 0.0,
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"caption_dropout_rate": 0
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}
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haruka/tagging methodology.md
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Tagging methodology for Haruka (blue archive)
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Start with WD1.4 Swinv2 at ~0.25-0.3 confidence.
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- Tag unique features
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- ie. `halo` / `demon horns` / `low wings`
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- Remove when not present or out of view. WD1.4 likes putting `halo` even on images where no halo is visible.
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- Tag outfit variants with a single master tag
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- ie. for Haruka:
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- Uniform: `school uniform`
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- NY Alt: `japanese clothes`
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- Add `official alternate costume`
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- Non-canon costumes
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- Add `alternate costume`
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- Nudity (WD1.4 usually does this accurately)
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- `nude` / `completely nude`
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- Prune eye colors
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- Keep tags which describe unusual eye features (`multicolored eyes`, `heterochromia`, `slit pupils`) as they can otherwise be too subtle and inconsistently drawn for the AI to learn
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- Prune hair colors
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- This includes `two-toned hair`, `gradiant hair`, etc. The AI learns all of these very consistently without the tags, likely because artists tend to draw them consistently
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- Partially prune hair styles
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- Leave key style tags like `twintails`, `ponytail`, `short hair with long locks`.
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- Prune exceedingly common tags like `bangs`, `eyebrows visible through hair`, `hair between eyes`, etc.
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- Prune length, except for images which differ from the character's usual length
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- Add `alternate hairstyle` and/or `alternate hair length` for these
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- Fixup hair ornaments
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- Prune generic `hair ornament` in favor of more specificity
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- `hairclip` / `black headband` / `hair flower` / `hair ribbon`, etc.
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- Consolidate tags that have color variants (`headband` >> `black headband`)
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- Consolidate outfits
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- Only tag an item when it is actually visible. If it is only barely visible along the edge of an image, keep in mind it may be cropped during bucketing.
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- Danbooru's wiki entry for a character often provides a good list of tags commonly used to describe a character's outfits.
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- Haruka outfits:
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- Uniform
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- `garrison cap`
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- `miniskirt`
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- `pleated skirt`
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- `black skirt`
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- `boots`
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- `hairclip`
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- `juliet sleeves`
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- `black belt`
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- `red shirt`
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- `collared shirt`
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- `purple jacket`
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- NY Alt
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- `frilled kimono`
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- `purple kimono`
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- `kimono skirt`
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- `floral print`
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- `purple hairband`
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- `hair flower`
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- `wide sleeves`
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- `obi`
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- `geta`
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- `tabi`
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- Fixup sleeves
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- ie. `long sleeves` / `puffy long sleeves` / `detached sleeves` / `off shoulder`
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- You only need one, but pick one and be consistent. If sleeves aren't tagged properly the tends to add them inappropriately (such as when prompting for sleeveless outfits or nudity)
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- Fixup collars
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- ie. `detached dollar` / `collared shirt` / `choker` / etc.
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- Same deal as sleeves, they tend to appear when unwanted if not consistently tagged according to visibility in the training data.
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- Tag expressions
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- WD1.4 rarely tags these, but doing them manually can help the AI reproduce a character's iconic expressions well.
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- Start by searching for images without one of these, and add them.
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- `open mouth`
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- `closed mouth`
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- `parted lips`
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- Add less common expressions
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- `wavy mouth`
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- `surprised` / `o_o`
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- `embarrassed` / `flustered` / `panicked` / `swirly eyes` / `@_@`
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- `smile` / `light smile` / `:d`
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- `upset` / `annoyed` / `frustrated`
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- `naughty face` / `seductive smile`
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- `smug` / `:3`
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- `eyes closed` / `one eye closed`
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- WD1.4 usually gets these for you.
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- Tag camera angles/composition
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- `cowboy shot`
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- `upper body`
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- `full body`
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- `portrait`
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- `cropped torso` / `cropped legs`
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- `feet out of frame`
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- `from side` / `from above` / `from below` / `from behind`
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- Tag iconic poses/actions
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- ie. `v` / `standing on one leg`
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- Haruka
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- `object hug`
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- `holding weapon`
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- Flip through each image and use Hydrus's "related tags" feature to quickly identify important tags that might be missing.
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- This feature looks at other images with similar tags to provide suggestions.
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