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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

Training data

The model was trained on ICDAR2019 Table Dataset

How to use

from transformers import DetrFeatureExtractor, DetrForObjectDetection
from PIL import Image

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)

# convert outputs (bounding boxes and class logits) to COCO API
target_sizes = torch.tensor([image.size[::-1]])
results = feature_extractor.post_process(outputs, target_sizes=target_sizes)[0]
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