Instructions to use ustc-community/dfine-large-coco with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ustc-community/dfine-large-coco with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("object-detection", model="ustc-community/dfine-large-coco")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForObjectDetection tokenizer = AutoTokenizer.from_pretrained("ustc-community/dfine-large-coco") model = AutoModelForObjectDetection.from_pretrained("ustc-community/dfine-large-coco", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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README.md
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This is the HF transformers implementation for D-FINE
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Model: D-FINE-L-COCO
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D-FINE, a powerful real-time object detector that achieves outstanding localization precision by redefining the bounding box regression task in DETR models. D-FINE comprises two key components: Fine-grained Distribution Refinement (FDR) and Global Optimal Localization Self-Distillation (GO-LSD).
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Usage:
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This is the HF transformers implementation for D-FINE
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Model: D-FINE-L-COCO
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D-FINE, a powerful real-time object detector that achieves outstanding localization precision by redefining the bounding box regression task in DETR models. D-FINE comprises two key components: Fine-grained Distribution Refinement (FDR) and Global Optimal Localization Self-Distillation (GO-LSD).
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Usage:
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