Update README.md

README.md

@@ -1,3 +1,64 @@
----
-license: cc-by-nc-4.0
----
+---
+license: cc-by-nc-4.0
+base_model:
+- stabilityai/stable-diffusion-xl-base-1.0
+tags:
+- image-to-image
+inference: false
+---
+# ✨ Latent Bridge Matching for Depth Estimation ✨
+
+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.
+This model was trained to estimate the depth map from a given input image.
+See also our [live demo](https://huggingface.co/spaces/jasperai/LBM_relighting) for image relighting and official [Github repo](https://github.com/gojasper/LBM).
+
+## How to use?
+To use this model you need first to install the associated `lbm` library by running the following
+```bash
+pip install git+https://github.com/gojasper/LBM.git
+```
+
+Then, you can infer with the model on your input images 
+```python
+import torch
+fron PIL import Image
+from lbm.inference import evaluate, get_model
+
+# Load model
+model = get_model(
+  "jasperai/LBM_relighting",
+  torch_dtype=torch.bfloat16,
+  device="cuda",
+)
+
+# Load a source image
+source_image = Image.open("your_image")
+
+# Perform inference
+output_image = evaluate(model, source_image, num_sampling_steps=1)
+```
+
+## Metrics
+This model achieves the following metrics
+
+| Metrics | AbsRel ↓  | δ1 ↑ | δ2 ↑ |
+|---------|-----------|------|------|
+| NYUv2   | 5.6       | 97.2 | 99.2 |
+| Kitti   | 9.4       | 93.0 | 98.9 |
+| ETH3D   | 6.3       | 96.5 | 99.3 |
+| ScanNet | 5.7       | 97.0 | 99.2 |
+| DIODE   | 30.3      | 77.5 | 89.3 |
+
+## License
+This code is released under the Creative Commons BY-NC 4.0 license.
+
+## Citation
+If you find this work useful or use it in your research, please consider citing us
+```bibtex
+@article{chadebec2025lbm,
+      title={LBM: Latent Bridge Matching for Fast Image-to-Image Translation}, 
+      author={Clément Chadebec and Onur Tasar and Sanjeev Sreetharan and Benjamin Aubin},
+      year={2025},
+      journal = {arXiv preprint arXiv:2503.07535},
+}
+```