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--- |
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license: cc-by-nc-4.0 |
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base_model: |
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- stabilityai/stable-diffusion-xl-base-1.0 |
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tags: |
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- image-to-image |
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inference: false |
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--- |
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# ✨ Latent Bridge Matching for Depth Estimation ✨ |
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Latent Bridge Matching (LBM) is a new, versatile and scalable method proposed in [LBM: Latent Bridge Matching for Fast Image-to-Image Translation](https://arxiv.org/abs/2503.07535) that relies on Bridge Matching in a latent space to achieve fast image-to-image translation. |
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This model was trained to estimate the depth map from a given input image. |
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See also our [live demo](https://huggingface.co/spaces/jasperai/LBM_relighting) for image relighting and official [Github repo](https://github.com/gojasper/LBM). |
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## How to use? |
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To use this model you need first to install the associated `lbm` library by running the following |
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```bash |
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pip install git+https://github.com/gojasper/LBM.git |
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``` |
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Then, you can infer with the model on your input images |
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```python |
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import torch |
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from PIL import Image |
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from lbm.inference import evaluate, get_model |
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# Load model |
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model = get_model( |
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"jasperai/LBM_depth", |
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torch_dtype=torch.bfloat16, |
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device="cuda", |
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) |
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# Load a source image |
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source_image = Image.open("your_image") |
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# Perform inference |
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output_image = evaluate(model, source_image, num_sampling_steps=1) |
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``` |
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## Metrics |
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This model achieves the following metrics |
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| Metrics | AbsRel ↓ | δ1 ↑ | δ2 ↑ | |
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|---------|-----------|------|------| |
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| NYUv2 | 5.6 | 97.2 | 99.2 | |
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| Kitti | 9.4 | 93.0 | 98.9 | |
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| ETH3D | 6.3 | 96.5 | 99.3 | |
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| ScanNet | 5.7 | 97.0 | 99.2 | |
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| DIODE | 30.3 | 77.5 | 89.3 | |
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## License |
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This code is released under the **Creative Commons BY-NC 4.0 license**. |
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## Citation |
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If you find this work useful or use it in your research, please consider citing us |
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```bibtex |
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@article{chadebec2025lbm, |
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title={LBM: Latent Bridge Matching for Fast Image-to-Image Translation}, |
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author={Clément Chadebec and Onur Tasar and Sanjeev Sreetharan and Benjamin Aubin}, |
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year={2025}, |
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journal = {arXiv preprint arXiv:2503.07535}, |
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} |
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``` |