[ADD] inference code

.gitignore

@@ -0,0 +1,19 @@
+
+# ignore these folders
+checkpoint/
+data/
+output/
+temp/
+wandb/
+venv/
+
+**/.ipynb_checkpoints/
+.vscode/
+
+# ignore these types
+*.pyc
+*.out
+*.log
+*.mexa64
+*.pdf
+*.tar

README.md

@@ -1,3 +1,108 @@
 # Marigold: Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation
 
-## Code coming soon
+This repository represents the official implementation of the paper titled "Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation".
+
+[![Website](doc/badges/badge-website.svg)](https://marigoldmonodepth.github.io)
+[![Paper](doc/badges/badge-pdf.svg)]()
+[![License](doc/badges/badge-license.svg)](LICENSE)
+<!-- [![GitHub](https://img.shields.io/github/stars/prs-eth/Marigold?style=default&label=GitHub%20★&logo=github)](https://github.com/prs-eth/Marigold) -->
+<!-- [![HF Space](https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-Space-blue)]() -->
+<!-- [![Open In Colab](doc/badges/badge-colab.svg)]() -->
+<!-- [![Docker](doc/badges/badge-docker.svg)]() -->
+<!-- ### [Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation]() -->
+
+[Bingxin Ke](http://www.kebingxin.com/),
+[Anton Obukhov](https://www.obukhov.ai/),
+[Shengyu Huang](https://shengyuh.github.io/),
+[Nando Metzger](https://nandometzger.github.io/),
+[Rodrigo Caye Daudt](https://rcdaudt.github.io/),
+[Konrad Schindler](https://scholar.google.com/citations?user=FZuNgqIAAAAJ&hl=en )
+
+We present Marigold, a diffusion model and associated fine-tuning protocol for monocular depth estimation. Its core principle is to leverage the rich visual knowledge stored in modern generative image models. Our model, derived from Stable Diffusion and fine-tuned with synthetic data, can zero-shot transfer to unseen data, offering state-of-the-art monocular depth estimation results.
+
+![teaser](doc/teaser_collage_transparant.png)
+
+
+## 📢 News
+
+2023-12-04: Upload [arxiv]() paper.
+
+2023-12-04: Release inference code.
+
+
+## 🛠️ Setup
+
+This code has been tested on:
+
+- Python 3.10.12, PyTorch 2.0.1, CUDA 11.7, GeForce RTX 3090
+- python 3.10.4, Pytorch 2.0.1, CUDA 11.7, GeForce RTX 4090
+
+Clone repository
+
+```bash
+git clone git@github.com:prs-eth/Marigold.git
+cd Marigold
+```
+
+Setup Python environment
+
+```bash
+python -m venv venv/marigold
+source venv/marigold/bin/activate
+pip install -r requirements.txt
+```
+
+Download checkpoint
+
+```bash
+bash script/download_weights.sh
+```
+
+## 🚀 Inference on in-the-wild images
+
+📷 Download sample images
+
+```bash
+bash script/download_sample_data.sh
+```
+
+🎮 Run inference
+
+```bash
+python run.py \
+    --input_rgb_dir data/in-the-wild_example\
+    --output_dir output/in-the-wild_example
+```
+
+⚙️ Inference settings
+
+- The inference script by default will resize the input images and resize back to the original resolution.
+
+  - `--resize_to_max_res`: The maximum edge length of resized input image. Default: 768.
+  - `--not_resize_input`: If given, will not resize the input image.
+  - `--not_resize_output`: If given, will not resize the output image back to the original resolution. Only valid without `--not_resize_input` option.
+
+- Trade-offs between **accuracy** and **speed** (for both options, larger value results in more accurate results at the cost of slower inference speed.)
+
+  - `--n_infer`: Number of inference passes to be ensembled. Default: 10.
+  - `--denoise_steps`: Number of diffusion denoising steps of each inference pass. Default: 10.
+
+- `--seed`: Random seed, can be set to ensure reproducibility. Default: None (using current time as random seed).
+- `--depth_cmap`: Colormap used to colorize the depth prediction. Default: Spectral.
+
+## 🎓 Citation
+
+```bibtex
+@misc{ke2023marigold,
+  author    = {Ke, Bingxin and Obukhov, Anton and Huang, Shengyu and Metzger, Nando and Daudt, Rodrigo Caye and Schindler, Konrad},
+  title     = {Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation},
+  year      = {2023},
+}
+```
+[<img src="doc/badges/badge-pdf.svg" height="20"/>]()
+
+## License
+
+This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
+
+[<img src="doc/badges/badge-license.svg" height="20"/>](http://creativecommons.org/licenses/by-nc-sa/4.0/)