Translate texts in manga/images.
中文说明 | Change Log
Join us on discord https://discord.gg/Ak8APNy4vb
Some manga/images will never be translated, therefore this project is born.
- Image/Manga Translator
Please note that the samples may not always be updated, they may not represent the current main branch version.
| Original | Translated |
|---|---|
(Source @09ra_19ra) |
(Mask) |
(Source @VERTIGRIS_ART) |
--detector ctd
(Mask)
|
(Source @hiduki_yayoi) |
--translator none
(Mask)
|
(Source @rikak) |
(Mask) |
Official Demo (by zyddnys): https://touhou.ai/imgtrans/
Browser Userscript (by QiroNT): https://greasyfork.org/scripts/437569
- Note this may not work sometimes due to stupid google gcp kept restarting my instance. In that case you can wait for me to restart the service, which may take up to 24 hrs.
- Note this online demo is using the current main branch version.
Successor to MMDOCR-HighPerformance.
This is a hobby project, you are welcome to contribute!
Currently this only a simple demo, many imperfections exist, we need your support to make this project better!
Primarily designed for translating Japanese text, but also supports Chinese, English and Korean.
Supports inpainting, text rendering and colorization.
# First, you need to have Python(>=3.8) installed on your system
# The latest version often does not work with some pytorch libraries yet
$ python --version
Python 3.10.6
# Clone this repo
$ git clone https://github.com/zyddnys/manga-image-translator.git
# Create venv
$ python -m venv venv
# Activate venv
$ source venv/bin/activate
# For --use-gpu option go to https://pytorch.org/ and follow
# pytorch installation instructions. Add `--upgrade --force-reinstall`
# to the pip command to overwrite the currently installed pytorch version.
# Install the dependencies
$ pip install -r requirements.txtThe models will be downloaded into ./models at runtime.
Before you start the pip install, first install Microsoft C++ Build Tools (Download, Instructions) as some pip dependencies will not compile without it. (See #114).
To use cuda on windows install the correct pytorch version as instructed on https://pytorch.org/.
Requirements:
- Docker (version 19.03+ required for CUDA / GPU acceleration)
- Docker Compose (Optional if you want to use files in the
demo/docfolder) - Nvidia Container Runtime (Optional if you want to use CUDA)
This project has docker support under zyddnys/manga-image-translator:main image.
This docker image contains all required dependencies / models for the project.
It should be noted that this image is fairly large (~ 15GB).
The web server can be hosted using (For CPU)
docker run -p 5003:5003 -v result:/app/result --ipc=host --rm zyddnys/manga-image-translator:main -l ENG --manga2eng -v --mode web --host=0.0.0.0 --port=5003or
docker-compose -f demo/doc/docker-compose-web-with-cpu.yml updepending on which you prefer. The web server should start on port 5003
and images should become in the /result folder.
To use docker with the CLI (I.e in batch mode)
docker run -v <targetFolder>:/app/<targetFolder> -v <targetFolder>-translated:/app/<targetFolder>-translated --ipc=host --rm zyddnys/manga-image-translator:main --mode=batch -i=/app/<targetFolder> <cli flags>Note: In the event you need to reference files on your host machine
you will need to mount the associated files as volumes into the /app folder inside the container.
Paths for the CLI will need to be the internal docker path /app/... instead of the paths on your host machine
Some translation services require API keys to function to set these pass them as env vars into the docker container. For example:
docker run --env="DEEPL_AUTH_KEY=xxx" --ipc=host --rm zyddnys/manga-image-translator:main <cli flags>To use with a supported GPU please first read the initial
Dockersection. There are some special dependencies you will need to use
To run the container with the following flags set:
docker run ... --gpus=all ... zyddnys/manga-image-translator:main ... --use-gpuOr (For the web server + GPU)
docker-compose -f demo/doc/docker-compose-web-with-gpu.yml upTo build the docker image locally you can run (You will require make on your machine)
make build-imageThen to test the built image run
make run-web-server# replace <path> with the path to the image folder or file.
$ python -m manga_translator local -v -i <path>
# results can be found under `<path_to_image_folder>-translated`.# use `--mode web` to start a web server.
$ cd server && python main.py --use-gpu
# the demo will be serving on http://127.0.0.1:5003GUI implementation: BallonsTranslator
Detector:
- ENG: ??
- JPN: ??
- CHS: ??
- KOR: ??
- Using
{"detector":{"detector": "ctd"}}can increase the amount of text lines detected
OCR:
- ENG: ??
- JPN: ??
- CHS: ??
- KOR: 48px
Translator:
- JPN -> ENG: Sugoi
- CHS -> ENG: ??
- CHS -> JPN: ??
- JPN -> CHS: ??
- ENG -> JPN: ??
- ENG -> CHS: ??
Inpainter: ??
Colorizer: mc2
- Small resolutions can sometimes trip up the detector, which is not so good at picking up irregular text sizes. To
circumvent this you can use an upscaler by specifying
--upscale-ratio 2or any other value - If the text being rendered is too small to read specify
--font-size-minimum 30for instance or use the--manga2engrenderer that will try to adapt to detected textbubbles - Specify a font with
--font-path fonts/anime_ace_3.ttffor example
-h, --help show this help message and exit
-v, --verbose Print debug info and save intermediate images in result folder
--attempts ATTEMPTS Retry attempts on encountered error. -1 means infinite times.
--ignore-errors Skip image on encountered error.
--model-dir MODEL_DIR Model directory (by default ./models in project root)
--use-gpu Turn on/off gpu (auto switch between mps and cuda)
--use-gpu-limited Turn on/off gpu (excluding offline translator)
--font-path FONT_PATH Path to font file
--pre-dict PRE_DICT Path to the pre-translation dictionary file
--post-dict POST_DICT Path to the post-translation dictionary file
--kernel-size KERNEL_SIZE Set the convolution kernel size of the text erasure area to
completely clean up text residues
--config-file CONFIG_FILE path to the config file
Used by the translator/language in the config
CHS: Chinese (Simplified)
CHT: Chinese (Traditional)
CSY: Czech
NLD: Dutch
ENG: English
FRA: French
DEU: German
HUN: Hungarian
ITA: Italian
JPN: Japanese
KOR: Korean
PLK: Polish
PTB: Portuguese (Brazil)
ROM: Romanian
RUS: Russian
ESP: Spanish
TRK: Turkish
UKR: Ukrainian
VIN: Vietnames
ARA: Arabic
SRP: Serbian
HRV: Croatian
THA: Thai
IND: Indonesian
FIL: Filipino (Tagalog)| Name | API Key | Offline | Note |
|---|---|---|---|
| Disabled temporarily | |||
| youdao | ✔️ | Requires YOUDAO_APP_KEY and YOUDAO_SECRET_KEY |
|
| baidu | ✔️ | Requires BAIDU_APP_ID and BAIDU_SECRET_KEY |
|
| deepl | ✔️ | Requires DEEPL_AUTH_KEY |
|
| caiyun | ✔️ | Requires CAIYUN_TOKEN |
|
| gpt3 | ✔️ | Implements text-davinci-003. Requires OPENAI_API_KEY |
|
| gpt3.5 | ✔️ | Implements gpt-3.5-turbo. Requires OPENAI_API_KEY |
|
| gpt4 | ✔️ | Implements gpt-4. Requires OPENAI_API_KEY |
|
| papago | |||
| sakura | Requires SAKURA_API_BASE |
||
| offline | ✔️ | Chooses most suitable offline translator for language | |
| sugoi | ✔️ | Sugoi V4.0 Models | |
| m2m100 | ✔️ | Supports every language | |
| m2m100_big | ✔️ | ||
| none | ✔️ | Translate to empty texts | |
| original | ✔️ | Keep original texts |
- API Key: Whether the translator requires an API key to be set as environment variable. For this you can create a .env file in the project root directory containing your api keys like so:
OPENAI_API_KEY=sk-xxxxxxx...
DEEPL_AUTH_KEY=xxxxxxxx...-
Offline: Whether the translator can be used offline.
-
Sugoi is created by mingshiba, please support him in https://www.patreon.com/mingshiba
run python -m manga_translator config-help >> config-info.json
an example can be found in example/config-example.json
{
"$defs": {
"Alignment": {
"enum": [
"auto",
"left",
"center",
"right"
],
"title": "Alignment",
"type": "string"
},
"Colorizer": {
"enum": [
"none",
"mc2"
],
"title": "Colorizer",
"type": "string"
},
"ColorizerConfig": {
"properties": {
"colorization_size": {
"default": 576,
"title": "Colorization Size",
"type": "integer"
},
"denoise_sigma": {
"default": 30,
"title": "Denoise Sigma",
"type": "integer"
},
"colorizer": {
"$ref": "#/$defs/Colorizer",
"default": "none"
}
},
"title": "ColorizerConfig",
"type": "object"
},
"Detector": {
"enum": [
"default",
"dbconvnext",
"ctd",
"craft",
"none"
],
"title": "Detector",
"type": "string"
},
"DetectorConfig": {
"properties": {
"detector": {
"$ref": "#/$defs/Detector",
"default": "default"
},
"detection_size": {
"default": 1536,
"title": "Detection Size",
"type": "integer"
},
"text_threshold": {
"default": 0.5,
"title": "Text Threshold",
"type": "number"
},
"det_rotate": {
"default": false,
"title": "Det Rotate",
"type": "boolean"
},
"det_auto_rotate": {
"default": false,
"title": "Det Auto Rotate",
"type": "boolean"
},
"det_invert": {
"default": false,
"title": "Det Invert",
"type": "boolean"
},
"det_gamma_correct": {
"default": false,
"title": "Det Gamma Correct",
"type": "boolean"
},
"box_threshold": {
"default": 0.7,
"title": "Box Threshold",
"type": "number"
},
"unclip_ratio": {
"default": 2.3,
"title": "Unclip Ratio",
"type": "number"
}
},
"title": "DetectorConfig",
"type": "object"
},
"Direction": {
"enum": [
"auto",
"horizontal",
"vertical"
],
"title": "Direction",
"type": "string"
},
"InpaintPrecision": {
"enum": [
"fp32",
"fp16",
"bf16"
],
"title": "InpaintPrecision",
"type": "string"
},
"Inpainter": {
"enum": [
"default",
"lama_large",
"lama_mpe",
"sd",
"none",
"original"
],
"title": "Inpainter",
"type": "string"
},
"InpainterConfig": {
"properties": {
"inpainter": {
"$ref": "#/$defs/Inpainter",
"default": "none"
},
"inpainting_size": {
"default": 2048,
"title": "Inpainting Size",
"type": "integer"
},
"inpainting_precision": {
"$ref": "#/$defs/InpaintPrecision",
"default": "fp32"
}
},
"title": "InpainterConfig",
"type": "object"
},
"Ocr": {
"enum": [
"32px",
"48px",
"48px_ctc",
"mocr"
],
"title": "Ocr",
"type": "string"
},
"OcrConfig": {
"properties": {
"use_mocr_merge": {
"default": false,
"title": "Use Mocr Merge",
"type": "boolean"
},
"ocr": {
"$ref": "#/$defs/Ocr",
"default": "48px"
},
"min_text_length": {
"default": 0,
"title": "Min Text Length",
"type": "integer"
},
"ignore_bubble": {
"default": 0,
"title": "Ignore Bubble",
"type": "integer"
}
},
"title": "OcrConfig",
"type": "object"
},
"RenderConfig": {
"properties": {
"renderer": {
"$ref": "#/$defs/Renderer",
"default": "default"
},
"alignment": {
"$ref": "#/$defs/Alignment",
"default": "auto"
},
"disable_font_border": {
"default": false,
"title": "Disable Font Border",
"type": "boolean"
},
"font_size_offset": {
"default": 0,
"title": "Font Size Offset",
"type": "integer"
},
"font_size_minimum": {
"default": -1,
"title": "Font Size Minimum",
"type": "integer"
},
"direction": {
"$ref": "#/$defs/Direction",
"default": "auto"
},
"uppercase": {
"default": false,
"title": "Uppercase",
"type": "boolean"
},
"lowercase": {
"default": false,
"title": "Lowercase",
"type": "boolean"
},
"gimp_font": {
"default": "Sans-serif",
"title": "Gimp Font",
"type": "string"
},
"no_hyphenation": {
"default": false,
"title": "No Hyphenation",
"type": "boolean"
},
"font_color": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Font Color"
},
"line_spacing": {
"anyOf": [
{
"type": "integer"
},
{
"type": "null"
}
],
"default": null,
"title": "Line Spacing"
},
"font_size": {
"anyOf": [
{
"type": "integer"
},
{
"type": "null"
}
],
"default": null,
"title": "Font Size"
}
},
"title": "RenderConfig",
"type": "object"
},
"Renderer": {
"enum": [
"default",
"manga2eng",
"none"
],
"title": "Renderer",
"type": "string"
},
"Translator": {
"enum": [
"youdao",
"baidu",
"deepl",
"papago",
"caiyun",
"gpt3",
"gpt3.5",
"gpt4",
"none",
"original",
"sakura",
"deepseek",
"groq",
"offline",
"nllb",
"nllb_big",
"sugoi",
"jparacrawl",
"jparacrawl_big",
"m2m100",
"m2m100_big",
"mbart50",
"qwen2",
"qwen2_big"
],
"title": "Translator",
"type": "string"
},
"TranslatorConfig": {
"properties": {
"translator": {
"$ref": "#/$defs/Translator",
"default": "sugoi"
},
"target_lang": {
"default": "ENG",
"title": "Target Lang",
"type": "string"
},
"no_text_lang_skip": {
"default": false,
"title": "No Text Lang Skip",
"type": "boolean"
},
"skip_lang": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Skip Lang"
},
"gpt_config": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Gpt Config"
},
"translator_chain": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Translator Chain"
},
"selective_translation": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Selective Translation"
}
},
"title": "TranslatorConfig",
"type": "object"
},
"UpscaleConfig": {
"properties": {
"upscaler": {
"$ref": "#/$defs/Upscaler",
"default": "esrgan"
},
"revert_upscaling": {
"default": false,
"title": "Revert Upscaling",
"type": "boolean"
},
"upscale_ratio": {
"anyOf": [
{
"type": "integer"
},
{
"type": "null"
}
],
"default": null,
"title": "Upscale Ratio"
}
},
"title": "UpscaleConfig",
"type": "object"
},
"Upscaler": {
"enum": [
"waifu2x",
"esrgan",
"4xultrasharp"
],
"title": "Upscaler",
"type": "string"
}
},
"properties": {
"filter_text": {
"anyOf": [
{
"type": "string"
},
{
"type": "null"
}
],
"default": null,
"title": "Filter Text"
},
"render": {
"$ref": "#/$defs/RenderConfig",
"default": {
"renderer": "default",
"alignment": "auto",
"disable_font_border": false,
"font_size_offset": 0,
"font_size_minimum": -1,
"direction": "auto",
"uppercase": false,
"lowercase": false,
"gimp_font": "Sans-serif",
"no_hyphenation": false,
"font_color": null,
"line_spacing": null,
"font_size": null
}
},
"upscale": {
"$ref": "#/$defs/UpscaleConfig",
"default": {
"upscaler": "esrgan",
"revert_upscaling": false,
"upscale_ratio": null
}
},
"translator": {
"$ref": "#/$defs/TranslatorConfig",
"default": {
"translator": "sugoi",
"target_lang": "ENG",
"no_text_lang_skip": false,
"skip_lang": null,
"gpt_config": null,
"translator_chain": null,
"selective_translation": null
}
},
"detector": {
"$ref": "#/$defs/DetectorConfig",
"default": {
"detector": "default",
"detection_size": 1536,
"text_threshold": 0.5,
"det_rotate": false,
"det_auto_rotate": false,
"det_invert": false,
"det_gamma_correct": false,
"box_threshold": 0.7,
"unclip_ratio": 2.3
}
},
"colorizer": {
"$ref": "#/$defs/ColorizerConfig",
"default": {
"colorization_size": 576,
"denoise_sigma": 30,
"colorizer": "none"
}
},
"inpainter": {
"$ref": "#/$defs/InpainterConfig",
"default": {
"inpainter": "none",
"inpainting_size": 2048,
"inpainting_precision": "fp32"
}
},
"ocr": {
"$ref": "#/$defs/OcrConfig",
"default": {
"use_mocr_merge": false,
"ocr": "48px",
"min_text_length": 0,
"ignore_bubble": 0
}
},
"kernel_size": {
"default": 3,
"title": "Kernel Size",
"type": "integer"
},
"mask_dilation_offset": {
"default": 0,
"title": "Mask Dilation Offset",
"type": "integer"
}
},
"title": "Config",
"type": "object"
}
Used by the --gpt-config argument.
# The prompt being feed into GPT before the text to translate.
# Use {to_lang} to indicate where the target language name should be inserted.
# Note: ChatGPT models don't use this prompt.
prompt_template: >
Please help me to translate the following text from a manga to {to_lang}
(if it's already in {to_lang} or looks like gibberish you have to output it as it is instead):\n
# What sampling temperature to use, between 0 and 2.
# Higher values like 0.8 will make the output more random,
# while lower values like 0.2 will make it more focused and deterministic.
temperature: 0.5
# An alternative to sampling with temperature, called nucleus sampling,
# where the model considers the results of the tokens with top_p probability mass.
# So 0.1 means only the tokens comprising the top 10% probability mass are considered.
top_p: 1
# The prompt being feed into ChatGPT before the text to translate.
# Use {to_lang} to indicate where the target language name should be inserted.
# Tokens used in this example: 57+
chat_system_template: >
You are a professional translation engine,
please translate the story into a colloquial,
elegant and fluent content,
without referencing machine translations.
You must only translate the story, never interpret it.
If there is any issue in the text, output it as is.
Translate to {to_lang}.
# Samples being feed into ChatGPT to show an example conversation.
# In a [prompt, response] format, keyed by the target language name.
#
# Generally, samples should include some examples of translation preferences, and ideally
# some names of characters it's likely to encounter.
#
# If you'd like to disable this feature, just set this to an empty list.
chat_sample:
Simplified Chinese: # Tokens used in this example: 88 + 84
- <|1|>恥ずかしい… 目立ちたくない… 私が消えたい…
<|2|>きみ… 大丈夫⁉
<|3|>なんだこいつ 空気読めて ないのか…？
- <|1|>好尴尬…我不想引人注目…我想消失…
<|2|>你…没事吧⁉
<|3|>这家伙怎么看不懂气氛的…？
# Overwrite configs for a specific model.
# For now the list is: gpt3, gpt35, gpt4
gpt35:
temperature: 0.3When setting output format to {xcf, psd, pdf} Gimp will be used to generate the file.
On Windows this assumes Gimp 2.x to be installed to C:\Users\<Username>\AppData\Local\Programs\Gimp 2.
The resulting .xcf file contains the original image as the lowest layer and it has the inpainting as a separate layer.
The translated textboxes have their own layers with the original text as the layer name for easy access.
Limitations:
- Gimp will turn text layers to regular images when saving
.psdfiles. - Rotated text isn't handled well in Gimp. When editing a rotated textbox it'll also show a popup that it was modified by an outside program.
- Font family is controlled separately, with the
--gimp-fontargument.
Read openapi docs: 127.0.0.1:5003/docs
A list of what needs to be done next, you're welcome to contribute.
- Use diffusion model based inpainting to achieve near perfect result, but this could be much slower.
IMPORTANT!!!HELP NEEDED!!! The current text rendering engine is barely usable, we need your help to improve text rendering!- Text rendering area is determined by detected text lines, not speech bubbles.
This works for images without speech bubbles, but making it impossible to decide where to put translated English text. I have no idea how to solve this. - Ryota et al. proposed using multimodal machine translation, maybe we can add ViT features for building custom NMT models.
- Make this project works for video(rewrite code in C++ and use GPU/other hardware NN accelerator).
Used for detecting hard subtitles in videos, generating ass file and remove them completely. Mask refinement based using non deep learning algorithms, I am currently testing out CRF based algorithm.Angled text region merge is not currently supported- Create pip repository
GPU server is not cheap, please consider to donate to us.
-
Ko-fi: https://ko-fi.com/voilelabs
-
Patreon: https://www.patreon.com/voilelabs
-
爱发电: https://afdian.net/@voilelabs
