Object Detection
ultralytics
Czech
cropilot
yolo
document-layout-analysis
document-cropping
digitization
Instructions to use cropilot-community/default_crop_v1 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- ultralytics
How to use cropilot-community/default_crop_v1 with ultralytics:
# Couldn't find a valid YOLO version tag. # Replace XX with the correct version. from ultralytics import YOLOvXX model = YOLOvXX.from_pretrained("cropilot-community/default_crop_v1") source = 'http://images.cocodataset.org/val2017/000000039769.jpg' model.predict(source=source, save=True) - Notebooks
- Google Colab
- Kaggle
Upload 2 files
Browse files- default_crop_v1.md +78 -0
- default_crop_v1.pt +3 -0
default_crop_v1.md
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---
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license: agpl-3.0
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language:
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- cs
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library_name: ultralytics
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pipeline_tag: object-detection
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tags:
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- cropilot
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- yolo
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- document-layout-analysis
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- document-cropping
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- digitization
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---
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# Default Crop v1
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`default_crop_v1.pt` is a Cropilot model for detecting page crop regions in scanned printed documents. It is the general-purpose default crop model, trained on a mixed corpus of books, magazines, and newspapers.
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It is published here as a reusable model artifact for use in the [Cropilot](https://github.com/moravianlibrary/cropilot) document-cropping ecosystem.
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## License
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Released under the GNU Affero General Public License v3.0 (`AGPL-3.0`).
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## Model File
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- File: `default_crop_v1.pt`
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- Base model: YOLO11s
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- Task: object-detection (page crop region)
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## Intended Use
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This model is intended for semi-automated processing in a Cropilot workflow:
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1. Compressed JPEGs are created from original scans (e.g. TIFF).
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2. Cropilot runs AI detection using this model.
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3. A human operator reviews and corrects the result in the Cropilot editor.
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4. Final crops are applied to the original scans by the production tooling.
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The model handles both **single-page** and **double-page (spread)** scans, making it a good general default when the document type is mixed or unknown.
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## Recommended Integration
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Typical Cropilot settings for this model:
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- Crop model: `default_crop`
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- Rotation model: `text`
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## Training Data
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The model was trained on a mixed corpus of digitized printed documents covering both single-page and double-page layouts. Approximate composition:
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- ~80% books
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- ~15% magazines / periodicals
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- ~5% newspapers
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The material spans roughly **1950–2010**.
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## Limitations
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- Performance is strongest on recent books; older material, heavily illustrated layouts, or document types outside the training mix may need validation or further fine-tuning.
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- Book covers are detected poorly.
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## Example Download
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```python
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from huggingface_hub import hf_hub_download
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path = hf_hub_download(
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repo_id="cropilot-community/default_crop_v1",
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filename="default_crop_v1.pt",
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)
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print(path)
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```
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## Versioning
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This repository stores **v1** of the default crop model. Newer fine-tuned models should be published as separate `v<n>` repositories so deployments remain reproducible.
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default_crop_v1.pt
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version https://git-lfs.github.com/spec/v1
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oid sha256:085c797ba97a1145b0a23cb51f8c110d938b9819d3888090e9f998c7444f5b3f
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size 16515394
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