ComfyUI-AnyText/README.md

Unofficial Simple And Rough Implementation Of AnyText | 中文说明

Original Repo: AnyText: Multilingual Visual Text Generation And Editing

For personal reason Suspended maintenance.

Warning:

• I'm not a coder, so many issues i have no idea how to solve.
• Do not install modelscope & tensorflow packages if damo/nlp_csanmt_translation_zh2en translator not needed!!!
• This custom-node results maybe worse than official.
• Tested only on cuda with fp16/fp32 , you can try others options but maybe not work.
• Tested with Official_ComfyUI_Stable_Release using python_embed on windows in my case. Distributions from unofficial or vitural env or other OS(such as linux) maybe not work.
• Tensorflow need specified cuda_version to run on gpu, but on native windows tensorflow 2.10+: look at the note will not work on cuda, we need linux or wsl2 to make gpu work. In this case, damo/nlp_csanmt_translation_zh2en translator will run slowly on cpu.
• If error Input type (torch.cuda.FloatTensor) and weight type (torch.FloatTensor) should be the same raise, try set all_to_device to true, maybe works. Thanks to @602387193c----->issues/17.
• If error expected scalar type Half but found Float, try fp32.

v2 test, more native, not remote_code mode.

Instructions:

• utrobinmv/t5_translate_en_ru_zh_small_1024 (212MB) is faster and smaller, but accurancy is far worse than damo/nlp_csanmt_translation_zh2en(7.3GB).
• Input_prompts will be checked if is_Chinese_prompts to decide whether auto load translator or not.
• Numbers of draw_masks must >= nunbers of string_content (in the "") we want to generate, or it will raise an error "not enough values to unpack".
• works on my pc: ComfyUI official release+(ComfyUI_windows_portable\ComfyUI)start with powershell+python_embed+win10+py311+torch2.3.0+cu121+rtx3050laptop(4GB).
• pillow>=9.5.0(10.3.0) Most packages are the newest.
• Accept any resolution image input, but will resized to <=768, output images will limited to <=768.(Official method)
• If font、ckpt_name、clip、translator set to Auto_DownLoad, default models will automtically download to specified directory. Models will loaded if models already exist.
• AnyText model will download into "ComfyUI\models\checkpoints\15\anytext_v1.1.safetensors" from huggingface(fp16: 2.66 GB).
• We can manually download AnyText-FP32-5.73 GB from modelscope,(fp32 5.73 GB).Then put it into ComfyUI\models\checkpoints.
• Or manually download AnyText-FP16-2.66 GB from huggingface and rename it to anytext_v1.1.safetensors or whatever you like.Then put it into ComfyUI\models\checkpoints.
• clip model clip-vit-large-patch14 will download into C:\Users\username\.cache\huggingface\hub. We can manually download all files from clip_model into ComfyUI\models\clip\openai--clip-vit-large-patch14.
• 
• Font-(SourceHanSansSC-Medium.otf)-18MB will download into ComfyUI\models\fonts from huggingface, we can use any other fonts too.
• Translator model huggingface--utrobinmv/t5_translate_en_ru_zh_small_1024-212MB will download into C:\Users\username\.cache\huggingface\hub or modelscope--damo\nlp_csanmt_translation_zh2en--7.3GB will download into C:\Users\username\.cache\modelscope\hub\damo. We can maually download translator model from link before, then put all files into ComfyUI\models\prompt_generator\models--utrobinmv--t5_translate_en_ru_zh_small_1024 or ComfyUI\models\prompt_generator\nlp_csanmt_translation_zh2en.
• 
• The AnyText model itself is also a standard sd1.5 text2image model.

Example Prompts:

Text-Generation English Prompts:

• An exquisite mug with an ancient Chinese poem engraved on it, including “花落知多少” and “夜来风雨声” and “处处闻啼鸟” and “春眠不觉晓”
• Sign on the clean building that reads “科学” and "과학" and "ステップ" and "SCIENCE"
• An ice sculpture is made with the text "Happy" and "Holidays".Dslr photo.
• A baseball cap with words “要聪明地” and “全力以赴”
• A nice drawing of octopus, sharks, and boats made by a child with crayons, with the words “神奇海底世界”

Text-Editing English Prompts:

• A Minion meme that says "wrong"
• A pile of fruit with "UIT" written in the middle
• photo of clean sandy beach," " " "

Text-Generation Chinese Prompts:

• 一个儿童蜡笔画，森林里有一个可爱的蘑菇形状的房子，标题是"森林小屋"
• 一个精美设计的logo，画的是一个黑白风格的厨师，带着厨师帽，logo下方写着“深夜食堂”
• 一张户外雪地靴的电商广告，上面写着 “双12大促！”，“立减50”，“加绒加厚”，“穿脱方便”，“温暖24小时送达”， “包邮”，高级设计感，精美构图
• 一个精致的马克杯，上面雕刻着一首中国古诗，内容是 "花落知多少" "夜来风雨声" "处处闻啼鸟" "春眠不觉晓"
• 一个漂亮的蜡笔画，有行星，宇航员，还有宇宙飞船，上面写的是"去火星旅行", "王小明", "11月1日"
• 一个装饰华丽的蛋糕，上面用奶油写着“阿里云”和"APSARA"
• 一张关于墙上的彩色涂鸦艺术的摄影作品，上面写着“人工智能" 和 "神经网络"
• 一枚中国古代铜钱, 上面的文字是 "康" "寶" "通" "熙"
• 精美的书法作品，上面写着“志” “存” “高” “远”

Text-Editing Chinese Prompts:

• 一个表情包，小猪说 "下班"
• 一个中国古代铜钱，上面写着"乾" "隆"
• 一个黄色标志牌，上边写着"不要" 和 "大意"
• 一个建筑物前面的字母标牌， 上面写着 " "

Example workflow:

Some Params:

sort_radio: order to draw text.

• ↕ for y axis. It will draw text-content("string") from start-to-end(order) on the mask position from top to bottom.
• ↔ for x axis .It will draw text-content("string") from start-to-end(order) on the mask position from left to right.

revise_pose: correct text position(only works in gen-mode).

• Which uses the bounding box of the rendered text as the revised position. However, it is occasionally found that the creativity of the generated text is slightly lower using this method, It dosen't work in text-edit mode.

Random_Gen: automatic generate mask.

• Automatically generate mask based on the number of text-content("string"). With this checked the manual_draw mask dosen't work.

nonEdit_random_gen_width & nonEdit_random_gen_height:

• For image size control with text-generation and Random_Gen together, works only in this situation.

cpu_offload:

• For multi-turn generation, it will speed up a lot. But we need to turn it off and run once when this node is no more needed and with other process for deleting model from cpu(ram). If single generation, just turn it off.

Citation:

Fork Repo: MaletteAI/anytext

• V2 build native pipeline method inspired by it.

Official Repo: tyxsspa/AnyText

@article{tuo2023anytext,
      title={AnyText: Multilingual Visual Text Generation And Editing}, 
      author={Yuxiang Tuo and Wangmeng Xiang and Jun-Yan He and Yifeng Geng and Xuansong Xie},
      year={2023},
      eprint={2311.03054},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}