{"data":{"slug":"adobe-research-custom-diffusion","name":"custom-diffusion","tagline":"Research repository for multi-concept customization in text-to-image synthesis using diffusion models.","github_url":"https://github.com/adobe-research/custom-diffusion","owner":"adobe-research","repo":"custom-diffusion","owner_avatar_url":"https://avatars.githubusercontent.com/u/3536625?v=4","primary_language":"Python","stars":1977,"forks":140,"topics":["computer-vision","customization","diffusion-models","few-shot","fine-tuning","pytorch","text-to-image-generation"],"archived":false,"github_pushed_at":"2026-05-24T19:31:46+00:00","maintenance_label":"Slowing","stars_delta_30d":1,"url":"https://www.graphcanon.com/tools/adobe-research-custom-diffusion","markdown_url":"https://www.graphcanon.com/tools/adobe-research-custom-diffusion.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/adobe-research-custom-diffusion","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=adobe-research-custom-diffusion","description":"Custom Diffusion: Multi-Concept Customization of Text-to-Image Diffusion (CVPR 2023)","homepage_url":"https://www.cs.cmu.edu/~custom-diffusion","license":"Other","open_issues":52,"watchers":30,"ai_summary":"A Python-based project based on PyTorch for enhancing text-to-image generation with customization capabilities in computer vision tasks through diffusion models and fine-tuning techniques.","readme_excerpt":"## Getting Started\n\n```\ngit clone https://github.com/adobe-research/custom-diffusion.git\ncd custom-diffusion\ngit clone https://github.com/CompVis/stable-diffusion.git\ncd stable-diffusion\nconda env create -f environment.yaml\nconda activate ldm\npip install clip-retrieval tqdm\n```\n\nOur code was developed on the following commit `#21f890f9da3cfbeaba8e2ac3c425ee9e998d5229` of [stable-diffusion](https://github.com/CompVis/stable-diffusion).\n\nDownload the stable-diffusion model checkpoint\n`wget https://huggingface.co/CompVis/stable-diffusion-v-1-4-original/resolve/main/sd-v1-4.ckpt`\nFor more details, please refer [here](https://huggingface.co/CompVis/stable-diffusion-v-1-4-original).\n\n**Dataset:** we release some of the datasets used in paper [here](https://huggingface.co/datasets/nupurkmr9/custom-diffusion/resolve/main/data.zip). \nImages taken from UnSplash are under [UnSplash LICENSE](https://unsplash.com/license).\n\n**Models:** all our models can be downloaded from [here](https://huggingface.co/nupurkmr9/custom-diffusion/tree/main/models/).\n\n---\n\n## install requirements \npip install accelerate>=0.24.1\npip install modelcards\npip install transformers>=4.31.0\npip install deepspeed\npip install diffusers==0.21.4\naccelerate config\nexport MODEL_NAME=\"CompVis/stable-diffusion-v1-4\"\n```\n\n**Single-Concept fine-tuning**\n\n```","github_created_at":"2022-12-08T19:18:41+00:00","created_at":"2026-07-11T11:38:36.558402+00:00","updated_at":"2026-08-24T00:01:56.357938+00:00","categories":[{"slug":"computer-vision","name":"Computer Vision","url":"https://www.graphcanon.com/categories/computer-vision","markdown_url":"https://www.graphcanon.com/categories/computer-vision.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/computer-vision"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"}],"tags":[{"slug":"computer-vision","name":"computer-vision"},{"slug":"customization","name":"customization"},{"slug":"diffusion-models","name":"diffusion-models"},{"slug":"few-shot","name":"few-shot"},{"slug":"fine-tuning","name":"fine-tuning"},{"slug":"pytorch","name":"pytorch"},{"slug":"text-to-image-generation","name":"text-to-image-generation"}],"trust":{"provenance":{"is_fork":false,"github_id":575997792,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-24T00:01:55.315Z","maintenance":{"label":"Slowing","score":36,"methodology":"github_public_v1","releases_90d":0,"days_since_push":91,"last_release_at":null,"stars_delta_30d":1,"open_issues_delta_30d":0},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:38:37.703Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-24T00:01:55.904Z"},"languages":{"value":["python"],"source":"github.language","observed_at":"2026-08-24T00:01:55.904Z"},"license_spdx":{"value":"Other","source":"github.license","observed_at":"2026-08-24T00:01:55.904Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":{"min_ram_gb":8,"requires_docker":false},"constraints":{"min_ram_gb":8,"requires_docker":false},"when_to_use":["Use Custom-Diffusion when your project requires incorporating multiple custom concepts into text-to-image synthesis, given its emphasis on handling multi-concept scenarios.","Consider this tool if you are working with limited labeled data for customization purposes due to its support for few-shot learning capabilities."],"when_not_to_use":["Avoid using Custom-Diffusion for immediate production deployments or simple image generation tasks as it is a research repository without extensive documentation meant for broader usability.","Do not opt for Custom-Diffusion if your project prioritizes speed over customization quality, given its focus on high-quality outputs through complex model fine-tuning processes."],"source":"enrich:decision_facts","observed_at":"2026-07-15T10:30:06.032Z"},"constraint_facets":{"min_ram_gb":8,"requires_docker":false},"decision_summary":[{"label":"Requirements","value":"Min 8 GB RAM"},{"label":"Adopt for","value":"Custom-Diffusion is a research-driven repository focusing on enhancing text-to-image generation tasks through multi-concept customization capabilities in diffusion models and fine-tuning techniques."}]}}