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| title: D-FINE Demo | |
| emoji: 🤖 | |
| colorFrom: gray | |
| colorTo: blue | |
| sdk: gradio | |
| sdk_version: 5.29.0 | |
| app_file: app.py | |
| python_version: 3.12 | |
| suggested_hardware: cpu-basic | |
| models: | |
| - Laudando-Associates-LLC/d-fine | |
| - Laudando-Associates-LLC/d-fine-nano | |
| - Laudando-Associates-LLC/d-fine-small | |
| - Laudando-Associates-LLC/d-fine-medium | |
| - Laudando-Associates-LLC/d-fine-large | |
| - Laudando-Associates-LLC/d-fine-xlarge | |
| datasets: | |
| - Laudando-Associates-LLC/pucks | |
| tags: | |
| - object-detection | |
| - pytorch | |
| - onnx | |
| - safetensors | |
| - transformers | |
| - agtech | |
| - d_fine | |
| fullWidth: true | |
| disable_embedding: false | |
| ## Citation | |
| If you use `D-FINE` or its methods in your work, please cite the following BibTeX entries: | |
| ```latex | |
| @misc{peng2024dfine, | |
| title={D-FINE: Redefine Regression Task in DETRs as Fine-grained Distribution Refinement}, | |
| author={Yansong Peng and Hebei Li and Peixi Wu and Yueyi Zhang and Xiaoyan Sun and Feng Wu}, | |
| year={2024}, | |
| eprint={2410.13842}, | |
| archivePrefix={arXiv}, | |
| primaryClass={cs.CV} | |
| } | |
| ``` |