Instructions to use bluolightning/PaddleOCRv5-Server-Det-For-Manga with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PaddleOCR
How to use bluolightning/PaddleOCRv5-Server-Det-For-Manga with PaddleOCR:
# 1. See https://www.paddlepaddle.org.cn/en/install to install paddlepaddle # 2. pip install paddleocr from paddleocr import TextDetection model = TextDetection(model_name="PaddleOCRv5-Server-Det-For-Manga") output = model.predict(input="path/to/image.png", batch_size=1) for res in output: res.print() res.save_to_img(save_path="./output/") res.save_to_json(save_path="./output/res.json") - Notebooks
- Google Colab
- Kaggle
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## Model Description
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This is a fine-tuned version of the **PaddleOCR v5 Server Detection Model**. It has been trained on a dataset of manga speech bubble crops to improve detection
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- **Speech Bubbles Lines:** Standard dialogue detection.
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- **Vertical Text Lines:** Improved bounding boxes for Japanese vertical writing (*tategaki*).
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- **Text Lines Outside Bubbles:** Narration boxes and floating text.
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This model outputs bounding boxes (polygons) for text regions. It does not perform text recognition; you will need a separate recognition model for that.
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Note that this model is still being worked on, and may improve with a better dataset.
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# Training Data
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The dataset consisted largely of synthetic data due to the limited real samples available.
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- PaddlePaddle
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## Model Description
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This is a fine-tuned version of the **PaddleOCR v5 Server Detection Model**. It has been trained on a dataset of manga speech bubble crops to improve detection for:
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- **Speech Bubbles Lines:** Standard dialogue detection.
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- **Vertical Text Lines:** Improved bounding boxes for Japanese vertical writing (*tategaki*).
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- **Text Lines Outside Bubbles:** Narration boxes and floating text.
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- **Text Lines With Furigana:** Greatly reduced the creation of separate bounding regions for furigana.
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This model outputs bounding boxes (polygons) for text regions. It does not perform text recognition; you will need a separate recognition model for that.
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Note that this model is still being worked on, and may improve with a better dataset or hyperparameters.
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# Training Data
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The dataset consisted largely of synthetic data due to the limited real samples available.
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