File size: 2,070 Bytes
457f311 d589e2b 457f311 764ca30 457f311 27dfb05 457f311 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 | ---
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
from PIL import Image
from lbm.inference import evaluate, get_model
# Load model
model = get_model(
"jasperai/LBM_depth",
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},
}
``` |