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--- |
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task_categories: |
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- object-detection |
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language: |
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- hy |
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pretty_name: hye_yolo_v0 |
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size_categories: |
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- n<1K |
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tags: |
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- handwritten text |
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- dictation |
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- YOLOv8 |
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--- |
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# Handwritten text detection dataset |
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## Data domain |
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The blanks were provided by youth organization "Armenian Club" ([telegram](https://t.me/armenian_club), [instagram](https://www.instagram.com/armenian.club?igsh=MTJjYTN0dTdjamtxMQ==) ), Russia Moscow. |
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The text on blanks was written during dictation "Teladrutyun" in 2018 |
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The blanks were labeled by [Amir](https://huggingface.co./Agmiyas) and [Renal](https://huggingface.co./Renaxit) during research project in HSE MIEM |
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## Dataset info |
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Contains labeled dictations blanks in YOLO format |
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91 image in total, 73 (80%) for train and 18 (20%) for test |
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No image alignment or any preprocess |
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Resolution 1320x1020, 96 dpi |
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## How to use |
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1) clone repo |
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``` |
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git clone https://huggingface.co./datasets/armvectores/handwritten_text_detection |
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cd handwritten_text_detection |
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``` |
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2) use data.yaml for training |
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``` |
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from ultralytics import YOLO |
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model = YOLO('yolov8n.pt') |
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model.train(data='data.yaml', epochs=20) |
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``` |
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## Data sample |
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<img src="blank_sample.png" width="700" /> |
