{"id":19815997,"url":"https://github.com/replicate/cog-marigold","last_synced_at":"2026-03-02T02:36:48.176Z","repository":{"id":212631134,"uuid":"731914373","full_name":"replicate/cog-marigold","owner":"replicate","description":"Cog wrapper for Marigold","archived":false,"fork":false,"pushed_at":"2023-12-21T09:53:29.000Z","size":51347,"stargazers_count":7,"open_issues_count":1,"forks_count":2,"subscribers_count":3,"default_branch":"main","last_synced_at":"2025-05-01T04:46:38.303Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/replicate.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.txt","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2023-12-15T07:19:14.000Z","updated_at":"2024-03-12T15:17:41.000Z","dependencies_parsed_at":"2023-12-21T12:13:38.631Z","dependency_job_id":null,"html_url":"https://github.com/replicate/cog-marigold","commit_stats":null,"previous_names":["replicate/cog-marigold"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/replicate%2Fcog-marigold","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/replicate%2Fcog-marigold/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/replicate%2Fcog-marigold/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/replicate%2Fcog-marigold/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/replicate","download_url":"https://codeload.github.com/replicate/cog-marigold/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":251860044,"owners_count":21655666,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-11-12T10:07:59.846Z","updated_at":"2026-03-02T02:36:48.109Z","avatar_url":"https://github.com/replicate.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Cog wrapper for Marigold\n\nA Cog wrapper for Marigold, a diffusion model and associated fine-tuning protocol for monocular depth estimation. See the original [repository](https://github.com/prs-eth/marigold), [paper](https://arxiv.org/abs/2312.02145) and [Replicate demo](https://replicate.com/adirik/marigold) for details.\n\n## API Usage\n\nYou need to have Cog and Docker installed to run this model locally. Follow the [model pushing guide](https://replicate.com/docs/guides/push-a-model) to push your own fork of Marigold to [Replicate](https://replicate.com). To use the model, simply provide the image (ideally RGB or grayscale) you would like to perform depth estimation for. The API returns two depth map images - one grayscale and one spectral.\n\nTo build the docker image with cog and run a prediction:\n```bash\ncog predict -i image=@examples/files_bee.jpg\n```\n\nTo start a server and send requests to your locally or remotely deployed API:\n```bash\ncog run -p 5000 python -m cog.server.http\n```\n\nInput parameters are as follows:  \n- **image:** RGB or grayscale input image for the model, use an RGB image for best results.  \n- **resize_input:** whether to resize the input image to max resolution of 768 x 768 pixels, default to `True`.  \n- **num_infer:** number of inferences to be performed. if \u003e1, multiple depth predictions are ensembled. A higher number yields better results but runs slower.   \n- **denoise_steps:** number of inference denoising steps, more steps results in higher accuracy but slower inference speed.  \n- **regularizer_strength:** ensembling parameter, weight of optimization regularizer.  \n- **reduction_method:** ensembling parameter, method to merge aligned depth maps. Choose between `[\"mean\", \"median\"]`.  \n- **max_iter:** ensembling parameter, max number of optimization iterations.   \n- **seed:** (optional) seed for reproducibility, set to random if left as `None`.   \n\n## References \n```\n@misc{ke2023repurposing,\n      title={Repurposing Diffusion-Based Image Generators for Monocular Depth Estimation}, \n      author={Bingxin Ke and Anton Obukhov and Shengyu Huang and Nando Metzger and Rodrigo Caye Daudt and Konrad Schindler},\n      year={2023},\n      eprint={2312.02145},\n      archivePrefix={arXiv},\n      primaryClass={cs.CV}\n}\n```","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Freplicate%2Fcog-marigold","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Freplicate%2Fcog-marigold","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Freplicate%2Fcog-marigold/lists"}