add AIBOM

prs-eth_marigold-depth-v1-0.json

@@ -0,0 +1,61 @@
+{
+    "bomFormat": "CycloneDX",
+    "specVersion": "1.6",
+    "serialNumber": "urn:uuid:3a11ce96-81a7-4bc0-a085-2820bc9fc036",
+    "version": 1,
+    "metadata": {
+        "timestamp": "2025-06-05T09:36:35.172916+00:00",
+        "component": {
+            "type": "machine-learning-model",
+            "bom-ref": "prs-eth/marigold-depth-v1-0-6b1a73d3-6054-5433-8afb-7093fb56c7c8",
+            "name": "prs-eth/marigold-depth-v1-0",
+            "externalReferences": [
+                {
+                    "url": "https://huggingface.co/prs-eth/marigold-depth-v1-0",
+                    "type": "documentation"
+                }
+            ],
+            "modelCard": {
+                "modelParameters": {
+                    "task": "depth-estimation"
+                },
+                "properties": [
+                    {
+                        "name": "library_name",
+                        "value": "diffusers"
+                    }
+                ]
+            },
+            "authors": [
+                {
+                    "name": "prs-eth"
+                }
+            ],
+            "licenses": [
+                {
+                    "license": {
+                        "id": "Apache-2.0",
+                        "url": "https://spdx.org/licenses/Apache-2.0.html"
+                    }
+                }
+            ],
+            "description": "- **Developed by:** [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).- **Model type:** Generative latent diffusion-based affine-invariant monocular depth estimation from a single image.- **Language:** English.- **License:** [Apache License License Version 2.0](https://www.apache.org/licenses/LICENSE-2.0).- **Model Description:** This model can be used to generate an estimated depth map of an input image.- **Resolution**: Even though any resolution can be processed, the model inherits the base diffusion model's effective resolution of roughly **768** pixels.This means that for optimal predictions, any larger input image should be resized to make the longer side 768 pixels before feeding it into the model.- **Steps and scheduler**: This model was designed for usage with the **DDIM** scheduler and between **10 and 50** denoising steps.It is possible to obtain good predictions with just **one** step by overriding the `\"timestep_spacing\": \"trailing\"` settingin the [scheduler configuration file](scheduler/scheduler_config.json) or by adding `pipe.scheduler = DDIMScheduler.from_config(pipe.scheduler.config, timestep_spacing=\"trailing\")`after the pipeline is loaded in the code before the first usage. For compatibility reasons we kept this `v1-0` model identical to the paper setting and provided a[newer v1-1 model](https://huggingface.co/prs-eth/marigold-depth-v1-1) with optimal settings for all possible step configurations.- **Outputs**:- **Affine-invariant depth map**: The predicted values are between 0 and 1, interpolating between the near and far planes of the model's choice.- **Uncertainty map**: Produced only when multiple predictions are ensembled with ensemble size larger than 2.- **Resources for more information:** [Project Website](https://marigoldmonodepth.github.io/), [Paper](https://arxiv.org/abs/2312.02145), [Code](https://github.com/prs-eth/marigold).- **Cite as:**```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}}@misc{ke2025marigold,title={Marigold: Affordable Adaptation of Diffusion-Based Image Generators for Image Analysis},author={Bingxin Ke and Kevin Qu and Tianfu Wang and Nando Metzger and Shengyu Huang and Bo Li and Anton Obukhov and Konrad Schindler},year={2025},eprint={2505.09358},archivePrefix={arXiv},primaryClass={cs.CV}}",
+            "tags": [
+                "diffusers",
+                "safetensors",
+                "depth estimation",
+                "image analysis",
+                "computer vision",
+                "in-the-wild",
+                "zero-shot",
+                "depth-estimation",
+                "en",
+                "arxiv:2312.02145",
+                "arxiv:2505.09358",
+                "license:apache-2.0",
+                "diffusers:MarigoldDepthPipeline",
+                "region:us"
+            ]
+        }
+    }
+}