28 lines
1.0 KiB
Markdown
28 lines
1.0 KiB
Markdown
```python
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from transformers import DetrImageProcessor, DetrForObjectDetection
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import torch
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from PIL import Image
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import requests
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url = "http://images.cocodataset.org/val2017/000000039769.jpg"
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image = Image.open(requests.get(url, stream=True).raw)
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processor = DetrImageProcessor.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 = processor(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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# let's only keep detections with score > 0.9
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target_sizes = torch.tensor([image.size[::-1]])
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results = processor.post_process_object_detection(outputs, target_sizes=target_sizes, threshold=0.9)[0]
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for score, label, box in zip(results["scores"], results["labels"], results["boxes"]):
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box = [round(i, 2) for i in box.tolist()]
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print(
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f"Detected {model.config.id2label[label.item()]} with confidence "
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f"{round(score.item(), 3)} at location {box}"
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)
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```
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</details> |