Instructions to use microsoft/table-transformer-structure-recognition with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/table-transformer-structure-recognition with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="microsoft/table-transformer-structure-recognition")# Load model directly from transformers import AutoImageProcessor, AutoModelForObjectDetection processor = AutoImageProcessor.from_pretrained("microsoft/table-transformer-structure-recognition") model = AutoModelForObjectDetection.from_pretrained("microsoft/table-transformer-structure-recognition") - Notebooks
- Google Colab
- Kaggle
Make resampling method same as in the original transform - BICUBIC
#10
by qubvel-hf - opened
- preprocessor_config.json +1 -0
preprocessor_config.json
CHANGED
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@@ -3,6 +3,7 @@
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"do_resize": true,
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"feature_extractor_type": "DetrFeatureExtractor",
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"format": "coco_detection",
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"image_mean": [
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0.485,
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| 8 |
0.456,
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"do_resize": true,
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"feature_extractor_type": "DetrFeatureExtractor",
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"format": "coco_detection",
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+
"resample": 3,
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"image_mean": [
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0.485,
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| 9 |
0.456,
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