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--- |
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tags: |
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- object-detection |
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--- |
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## Model description |
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detr-doc-table-detection is a model trained to detect both **Bordered** and **Borderless** tables in documents, based on [facebook/detr-resnet-50](https://huggingface.co/facebook/detr-resnet-50) |
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## Training data |
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The model was trained on ICDAR2019 Table Dataset |
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### How to use |
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```python |
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from transformers import DetrFeatureExtractor, DetrForObjectDetection |
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from PIL import Image |
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image = Image.open("Image path") |
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feature_extractor = DetrFeatureExtractor.from_pretrained('TahaDouaji/detr-doc-table-detection') |
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model = DetrForObjectDetection.from_pretrained('TahaDouaji/detr-doc-table-detection') |
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inputs = feature_extractor(images=image, return_tensors="pt") |
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outputs = model(**inputs) |
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# convert outputs (bounding boxes and class logits) to COCO API |
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target_sizes = torch.tensor([image.size[::-1]]) |
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results = feature_extractor.post_process(outputs, target_sizes=target_sizes)[0] |
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``` |
