Yolov11x Codh Char

How to Use

from ultralytics import YOLO

# Load model
model = YOLO("nakamura196/yolov11x-codh-char")

# Run inference
results = model.predict("your_image.jpg", conf=0.25, iou=0.45)

# Process results
for result in results:
    boxes = result.boxes
    print(boxes)

Or download the model file directly:

from huggingface_hub import hf_hub_download

model_path = hf_hub_download(repo_id="nakamura196/yolov11x-codh-char", filename="best.pt")

Training Data

The model was trained on the CODH Kuzushiji Character Shape Dataset, which contains character images from various Japanese historical documents.

Model Architecture

• Base Model: YOLOv11x (extra-large variant)
• Task: Object Detection
• Framework: Ultralytics

Limitations

• Optimized for historical Japanese documents; may not perform well on modern printed text
• Performance may vary depending on the document quality and writing style

Citation

If you use this model, please cite the original dataset:

@misc{codh_kuzushiji,
  title={CODH Kuzushiji Character Shape Dataset},
  author={Center for Open Data in the Humanities (CODH)},
  url={http://codh.rois.ac.jp/char-shape/}
}

License

MIT License

onnx · 38.3 MB · SHA-256 f46267754d40…090c · Hugging Face

--- license: mit library_name: ultralytics tags: - object-detection - yolo - yolov11 - japanese - kuzushiji - character-recognition - historical-documents datasets: - codh/kuzushiji language: - ja pipeline_tag: object-detection --- # YOLOv11x CODH Character ## Model Description This is a YOLOv11x model fine-tuned for detecting and recognizing characters in Japanese historical documents (古典籍/Koten-seki). The model is trained on the [日本古典籍くずし字データセット (CODH Kuzushiji Dataset)](http://codh.rois.ac.jp/char-shape/). ## Intended Uses - Character detection in historical Japanese manuscripts - Kuzushiji (くずし字) character localization - Pre-processing for OCR pipelines on classical Japanese texts ## How to Use ```python from ultralytics import YOLO # Load model model = YOLO("nakamura196/yolov11x-codh-char") # Run inference results = model.predict("your_image.jpg", conf=0.25, iou=0.45) # Process results for result in results: boxes = result.boxes print(boxes) ``` Or download the model file directly: ```python from huggingface_hub import hf_hub_download model_path = hf_hub_download(repo_id="nakamura196/yolov11x-codh-char", filename="best.pt") ``` ## Training Data The model was trained on the [CODH Kuzushiji Character Shape Dataset](http://codh.rois.ac.jp/char-shape/), which contains character images from various Japanese historical documents. ## Model Architecture - **Base Model**: YOLOv11x (extra-large variant) - **Task**: Object Detection - **Framework**: Ultralytics ## Limitations - Optimized for historical Japanese documents; may not perform well on modern printed text - Performance may vary depending on the document quality and writing style ## Citation If you use this model, please cite the original dataset: ``` @misc{codh_kuzushiji, title={CODH Kuzushiji Character Shape Dataset}, author={Center for Open Data in the Humanities (CODH)}, url={http://codh.rois.ac.jp/char-shape/} } ``` ## License MIT License