Instructions to use zenosai/MonkeyOCRv2-S with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use zenosai/MonkeyOCRv2-S with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-feature-extraction", model="zenosai/MonkeyOCRv2-S", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("zenosai/MonkeyOCRv2-S", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
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#### 3. Text detection results on Total-Text, CTW1500, ICDAR2015 and ArT. We follow the training and evaluation protocols of [MMOCR](https://github.com/open-mmlab/mmocr) and [DPText-DETR](https://github.com/ymy-k/DPText-DETR).
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#### 3. Text detection results on Total-Text, CTW1500, ICDAR2015 and ArT. We follow the training and evaluation protocols of [MMOCR](https://github.com/open-mmlab/mmocr) and [DPText-DETR](https://github.com/ymy-k/DPText-DETR).
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<img src="https://github.com/Yuliang-Liu/MonkeyOCRv2/blob/main/asserts/text_detection.png?raw=true" width="600"/>
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