add affine-invariant disparity v0.1

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+doc/teaser_collage_transparant.png filter=lfs diff=lfs merge=lfs -text

LICENSE.txt

@@ -0,0 +1,177 @@
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README.md

@@ -1,3 +1,58 @@
----
-license: apache-2.0
----
+---
+license: apache-2.0
+language:
+- en
+pipeline_tag: depth-estimation
+tags:
+- monocular depth estimation
+- single image depth estimation
+- depth
+- in-the-wild
+- zero-shot
+- depth
+---
+# Marigold: Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation
+
+This model represents the internal test checkpoint of affine-invariant disparity version (train_marigold_affine_disparity_iter_24000).
+
+[![Website](doc/badges/badge-website.svg)](https://marigoldmonodepth.github.io)
+[![GitHub](https://img.shields.io/github/stars/prs-eth/Marigold?style=default&label=GitHub%20★&logo=github)](https://github.com/prs-eth/Marigold)
+[![Paper](doc/badges/badge-pdf.svg)](https://arxiv.org/abs/2312.02145)
+[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/drive/12G8reD13DdpMie5ZQlaFNo2WCGeNUH-u?usp=sharing)
+[![Hugging Face Space](https://img.shields.io/badge/🤗%20Hugging%20Face-Space-yellow)](https://huggingface.co/spaces/toshas/marigold)
+[![License](https://img.shields.io/badge/License-Apache--2.0-929292)](https://www.apache.org/licenses/LICENSE-2.0)
+<!-- [![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)
+
+
+## 🎓 Citation
+
+```bibtex
+@InProceedings{ke2023repurposing,
+      title={Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation},
+      author={Bingxin Ke and Anton Obukhov and Shengyu Huang and Nando Metzger and Rodrigo Caye Daudt and Konrad Schindler},
+      booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
+      year={2024}
+}
+```
+
+## 🎫 License
+
+This work is licensed under the Apache License, Version 2.0 (as defined in the [LICENSE](LICENSE.txt)).
+
+By downloading and using the code and model you agree to the terms in the  [LICENSE](LICENSE.txt).
+
+[![License](https://img.shields.io/badge/License-Apache--2.0-929292)](https://www.apache.org/licenses/LICENSE-2.0)

model_index.json

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+{
+    "_class_name":"MarigoldPipeline",
+    "_diffusers_version":"0.24.0",
+    "prediction_type": "disparity",
+    "scale_invariant": true,
+    "shift_invariant": true, 
+    "unet":[
+       "diffusers",
+       "UNet2DConditionModel"
+    ],
+    "vae":[
+       "diffusers",
+       "AutoencoderKL"
+    ],
+    "scheduler":[
+       "diffusers",
+       "DDIMScheduler"
+    ],
+    "text_encoder":[
+       "transformers",
+       "CLIPTextModel"
+    ],
+    "tokenizer":[
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+       "CLIPTokenizer"
+    ]
+ }

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+  "trained_betas": null
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+  "model_type": "clip_text_model",
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+  "num_hidden_layers": 23,
+  "pad_token_id": 1,
+  "projection_dim": 512,
+  "torch_dtype": "float32",
+  "transformers_version": "4.25.0.dev0",
+  "vocab_size": 49408
+}

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tokenizer/special_tokens_map.json

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