| ## Model description | |
| 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) | |
| ## Training data | |
| The model was trained on ICDAR2019 Table Dataset | |
| ### How to use | |
| ```python | |
| from transformers import DetrFeatureExtractor, DetrForObjectDetection | |
| from PIL import Image | |
| import requests | |
| image = Image.open("Image path") | |
| feature_extractor = DetrFeatureExtractor.from_pretrained('TahaDouaji/detr-doc-table-detection') | |
| model = DetrForObjectDetection.from_pretrained('TahaDouaji/detr-doc-table-detection') | |
| inputs = feature_extractor(images=image, return_tensors="pt") | |
| outputs = model(**inputs) | |
| # model predicts bounding boxes and corresponding COCO classes | |
| logits = outputs.logits | |
| bboxes = outputs.pred_boxes | |
| ``` |