[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"project-70960":3},{"id":4,"name":5,"fullName":6,"owner":7,"repo":5,"description":8,"homepage":9,"htmlUrl":10,"language":11,"languages":10,"totalLinesOfCode":10,"stars":12,"forks":13,"watchers":14,"openIssues":15,"contributorsCount":16,"subscribersCount":16,"size":16,"stars1d":17,"stars7d":18,"stars30d":19,"stars90d":16,"forks30d":16,"starsTrendScore":20,"compositeScore":21,"rankGlobal":10,"rankLanguage":10,"license":22,"archived":23,"fork":23,"defaultBranch":24,"hasWiki":23,"hasPages":23,"topics":25,"createdAt":10,"pushedAt":10,"updatedAt":26,"readmeContent":27,"aiSummary":28,"trendingCount":16,"starSnapshotCount":16,"syncStatus":29,"lastSyncTime":30,"discoverSource":31},70960,"AnimateDiff","guoyww\u002FAnimateDiff","guoyww","Official implementation of AnimateDiff.","https:\u002F\u002Fanimatediff.github.io",null,"Python",12140,1077,96,297,0,5,8,23,15,44.1,"Apache License 2.0",false,"main",[],"2026-06-12 02:02:45","# AnimateDiff\n\nThis repository is the official implementation of [AnimateDiff](https:\u002F\u002Farxiv.org\u002Fabs\u002F2307.04725) [ICLR2024 Spotlight].\nIt is a plug-and-play module turning most community text-to-image models into animation generators, without the need of additional training.\n\n**[AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning](https:\u002F\u002Farxiv.org\u002Fabs\u002F2307.04725)** \n\u003C\u002Fbr>\n[Yuwei Guo](https:\u002F\u002Fguoyww.github.io\u002F),\n[Ceyuan Yang✝](https:\u002F\u002Fceyuan.me\u002F),\n[Anyi Rao](https:\u002F\u002Fanyirao.com\u002F),\n[Zhengyang Liang](https:\u002F\u002Fmaxleung99.github.io\u002F),\n[Yaohui Wang](https:\u002F\u002Fwyhsirius.github.io\u002F),\n[Yu Qiao](https:\u002F\u002Fscholar.google.com.hk\u002Fcitations?user=gFtI-8QAAAAJ),\n[Maneesh Agrawala](https:\u002F\u002Fgraphics.stanford.edu\u002F~maneesh\u002F),\n[Dahua Lin](http:\u002F\u002Fdahua.site),\n[Bo Dai](https:\u002F\u002Fdaibo.info)\n(✝Corresponding Author)  \n[![arXiv](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FarXiv-2307.04725-b31b1b.svg)](https:\u002F\u002Farxiv.org\u002Fabs\u002F2307.04725)\n[![Project Page](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FProject-Website-green)](https:\u002F\u002Fanimatediff.github.io\u002F)\n[![Open in OpenXLab](https:\u002F\u002Fcdn-static.openxlab.org.cn\u002Fapp-center\u002Fopenxlab_app.svg)](https:\u002F\u002Fopenxlab.org.cn\u002Fapps\u002Fdetail\u002FMasbfca\u002FAnimateDiff)\n[![Hugging Face Spaces](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002F%F0%9F%A4%97%20Hugging%20Face-Spaces-yellow)](https:\u002F\u002Fhuggingface.co\u002Fspaces\u002Fguoyww\u002FAnimateDiff)\n\n***Note:*** The `main` branch is for [Stable Diffusion V1.5](https:\u002F\u002Fhuggingface.co\u002Frunwayml\u002Fstable-diffusion-v1-5); for [Stable Diffusion XL](https:\u002F\u002Fhuggingface.co\u002Fstabilityai\u002Fstable-diffusion-xl-base-1.0), please refer `sdxl-beta` branch.\n\n\n## Quick Demos\nMore results can be found in the [Gallery](__assets__\u002Fdocs\u002Fgallery.md).\nSome of them are contributed by the community.\n\n\u003Ctable class=\"center\">\n    \u003Ctr>\n    \u003Ctd>\u003Cimg src=\"__assets__\u002Fanimations\u002Fmodel_01\u002F01.gif\">\u003C\u002Ftd>\n    \u003Ctd>\u003Cimg src=\"__assets__\u002Fanimations\u002Fmodel_01\u002F02.gif\">\u003C\u002Ftd>\n    \u003Ctd>\u003Cimg src=\"__assets__\u002Fanimations\u002Fmodel_01\u002F03.gif\">\u003C\u002Ftd>\n    \u003Ctd>\u003Cimg src=\"__assets__\u002Fanimations\u002Fmodel_01\u002F04.gif\">\u003C\u002Ftd>\n    \u003C\u002Ftr>\n\u003C\u002Ftable>\n\u003Cp style=\"margin-left: 2em; margin-top: -1em\">Model：\u003Ca href=\"https:\u002F\u002Fcivitai.com\u002Fmodels\u002F30240\u002Ftoonyou\">ToonYou\u003C\u002Fa>\u003C\u002Fp>\n\n\u003Ctable>\n    \u003Ctr>\n    \u003Ctd>\u003Cimg src=\"__assets__\u002Fanimations\u002Fmodel_03\u002F01.gif\">\u003C\u002Ftd>\n    \u003Ctd>\u003Cimg src=\"__assets__\u002Fanimations\u002Fmodel_03\u002F02.gif\">\u003C\u002Ftd>\n    \u003Ctd>\u003Cimg src=\"__assets__\u002Fanimations\u002Fmodel_03\u002F03.gif\">\u003C\u002Ftd>\n    \u003Ctd>\u003Cimg src=\"__assets__\u002Fanimations\u002Fmodel_03\u002F04.gif\">\u003C\u002Ftd>\n    \u003C\u002Ftr>\n\u003C\u002Ftable>\n\u003Cp style=\"margin-left: 2em; margin-top: -1em\">Model：\u003Ca href=\"https:\u002F\u002Fcivitai.com\u002Fmodels\u002F4201\u002Frealistic-vision-v20\">Realistic Vision V2.0\u003C\u002Fa>\u003C\u002Fp>\n\n\n## Quick Start\n***Note:*** AnimateDiff is also offically supported by Diffusers.\nVisit [AnimateDiff Diffusers Tutorial](https:\u002F\u002Fhuggingface.co\u002Fdocs\u002Fdiffusers\u002Fapi\u002Fpipelines\u002Fanimatediff) for more details.\n*Following instructions is for working with this repository*.\n\n***Note:*** For all scripts, checkpoint downloading will be *automatically* handled, so the script running may take longer time when first executed.\n\n### 1. Setup repository and environment\n\n```\ngit clone https:\u002F\u002Fgithub.com\u002Fguoyww\u002FAnimateDiff.git\ncd AnimateDiff\n\npip install -r requirements.txt\n```\n\n### 2. Launch the sampling script!\nThe generated samples can be found in `samples\u002F` folder.\n\n#### 2.1 Generate animations with comunity models\n```\npython -m scripts.animate --config configs\u002Fprompts\u002F1_animate\u002F1_1_animate_RealisticVision.yaml\npython -m scripts.animate --config configs\u002Fprompts\u002F1_animate\u002F1_2_animate_FilmVelvia.yaml\npython -m scripts.animate --config configs\u002Fprompts\u002F1_animate\u002F1_3_animate_ToonYou.yaml\npython -m scripts.animate --config configs\u002Fprompts\u002F1_animate\u002F1_4_animate_MajicMix.yaml\npython -m scripts.animate --config configs\u002Fprompts\u002F1_animate\u002F1_5_animate_RcnzCartoon.yaml\npython -m scripts.animate --config configs\u002Fprompts\u002F1_animate\u002F1_6_animate_Lyriel.yaml\npython -m scripts.animate --config configs\u002Fprompts\u002F1_animate\u002F1_7_animate_Tusun.yaml\n```\n\n#### 2.2 Generate animation with MotionLoRA control\n```\npython -m scripts.animate --config configs\u002Fprompts\u002F2_motionlora\u002F2_motionlora_RealisticVision.yaml\n```\n\n#### 2.3 More control with SparseCtrl RGB and sketch\n```\npython -m scripts.animate --config configs\u002Fprompts\u002F3_sparsectrl\u002F3_1_sparsectrl_i2v.yaml\npython -m scripts.animate --config configs\u002Fprompts\u002F3_sparsectrl\u002F3_2_sparsectrl_rgb_RealisticVision.yaml\npython -m scripts.animate --config configs\u002Fprompts\u002F3_sparsectrl\u002F3_3_sparsectrl_sketch_RealisticVision.yaml\n```\n\n#### 2.4 Gradio app\nWe created a Gradio demo to make AnimateDiff easier to use. \nBy default, the demo will run at `localhost:7860`.\n```\npython -u app.py\n```\n\u003Cimg src=\"__assets__\u002Ffigs\u002Fgradio.jpg\" style=\"width: 75%\">\n\n\n## Technical Explanation\n\u003Cdetails close>\n\u003Csummary>Technical Explanation\u003C\u002Fsummary>\n\n### AnimateDiff\n\n**AnimateDiff aims to learn transferable motion priors that can be applied to other variants of Stable Diffusion family.**\nTo this end, we design the following training pipeline consisting of three stages.\n\n\u003Cimg src=\"__assets__\u002Ffigs\u002Fadapter_explain.png\" style=\"width:100%\">\n\n- In **1. Alleviate Negative Effects** stage, we train the **domain adapter**, e.g., `v3_sd15_adapter.ckpt`, to fit defective visual aritfacts (e.g., watermarks) in the training dataset.\nThis can also benefit the distangled learning of motion and spatial appearance.\nBy default, the adapter can be removed at inference. It can also be integrated into the model and its effects can be adjusted by a lora scaler.\n\n- In **2. Learn Motion Priors** stage, we train the **motion module**, e.g., `v3_sd15_mm.ckpt`, to learn the real-world motion patterns from videos.\n\n- In **3. (optional) Adapt to New Patterns** stage, we train **MotionLoRA**, e.g., `v2_lora_ZoomIn.ckpt`, to efficiently adapt motion module for specific motion patterns (camera zooming, rolling, etc.).\n\n### SparseCtrl\n\n**SparseCtrl aims to add more control to text-to-video models by adopting some sparse inputs (e.g., few RGB images or sketch inputs).**\nIts technicall details can be found in the following paper:\n\n**[SparseCtrl: Adding Sparse Controls to Text-to-Video Diffusion Models](https:\u002F\u002Farxiv.org\u002Fabs\u002F2311.16933)**  \n[Yuwei Guo](https:\u002F\u002Fguoyww.github.io\u002F),\n[Ceyuan Yang✝](https:\u002F\u002Fceyuan.me\u002F),\n[Anyi Rao](https:\u002F\u002Fanyirao.com\u002F),\n[Maneesh Agrawala](https:\u002F\u002Fgraphics.stanford.edu\u002F~maneesh\u002F),\n[Dahua Lin](http:\u002F\u002Fdahua.site),\n[Bo Dai](https:\u002F\u002Fdaibo.info)\n(✝Corresponding Author)  \n[![arXiv](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FarXiv-2311.16933-b31b1b.svg)](https:\u002F\u002Farxiv.org\u002Fabs\u002F2311.16933)\n[![Project Page](https:\u002F\u002Fimg.shields.io\u002Fbadge\u002FProject-Website-green)](https:\u002F\u002Fguoyww.github.io\u002Fprojects\u002FSparseCtrl\u002F)\n\n\u003C\u002Fdetails>\n\n\n## Model Versions\n\u003Cdetails close>\n\u003Csummary>Model Versions\u003C\u002Fsummary>\n\n### AnimateDiff v3 and SparseCtrl (2023.12)\n\nIn this version, we use **Domain Adapter LoRA** for image model finetuning, which provides more flexiblity at inference.\nWe also implement two (RGB image\u002Fscribble) [SparseCtrl](https:\u002F\u002Farxiv.org\u002Fabs\u002F2311.16933) encoders, which can take abitary number of condition maps to control the animation contents.\n\n\u003Cdetails close>\n\u003Csummary>AnimateDiff v3 Model Zoo\u003C\u002Fsummary>\n\n| Name | HuggingFace | Type | Storage | Description |\n| - | - | - | - | - |\n| `v3_adapter_sd_v15.ckpt` | [Link](https:\u002F\u002Fhuggingface.co\u002Fguoyww\u002Fanimatediff\u002Fblob\u002Fmain\u002Fv3_sd15_adapter.ckpt) | Domain Adapter | 97.4 MB | |\n| `v3_sd15_mm.ckpt.ckpt` | [Link](https:\u002F\u002Fhuggingface.co\u002Fguoyww\u002Fanimatediff\u002Fblob\u002Fmain\u002Fv3_sd15_mm.ckpt) | Motion Module | 1.56 GB | |\n| `v3_sd15_sparsectrl_scribble.ckpt` | [Link](https:\u002F\u002Fhuggingface.co\u002Fguoyww\u002Fanimatediff\u002Fblob\u002Fmain\u002Fv3_sd15_sparsectrl_scribble.ckpt) | SparseCtrl Encoder | 1.86 GB | scribble condition |\n| `v3_sd15_sparsectrl_rgb.ckpt` | [Link](https:\u002F\u002Fhuggingface.co\u002Fguoyww\u002Fanimatediff\u002Fblob\u002Fmain\u002Fv3_sd15_sparsectrl_rgb.ckpt) | SparseCtrl Encoder | 1.85 GB | RGB image condition |\n\u003C\u002Fdetails>\n\n#### Limitations\n1. Small fickering is noticable;\n2. To stay compatible with comunity models, there is no specific optimizations for general T2V, leading to limited visual quality under this setting;\n3. **(Style Alignment) For usage such as image animation\u002Finterpolation, it's recommanded to use images generated by the same community model.**\n\n#### Demos\n\u003Ctable class=\"center\">\n    \u003Ctr style=\"line-height: 0\">\n    \u003Ctd width=25% style=\"border: none; text-align: center\">Input (by RealisticVision)\u003C\u002Ftd>\n    \u003Ctd width=25% style=\"border: none; text-align: center\">Animation\u003C\u002Ftd>\n    \u003Ctd width=25% style=\"border: none; text-align: center\">Input\u003C\u002Ftd>\n    \u003Ctd width=25% style=\"border: none; text-align: center\">Animation\u003C\u002Ftd>\n    \u003C\u002Ftr>\n    \u003Ctr>\n    \u003Ctd width=25% style=\"border: none\">\u003Cimg src=\"__assets__\u002Fdemos\u002Fimage\u002FRealisticVision_firework.png\" style=\"width:100%\">\u003C\u002Ftd>\n    \u003Ctd width=25% style=\"border: none\">\u003Cimg src=\"__assets__\u002Fanimations\u002Fv3\u002Fanimation_fireworks.gif\" style=\"width:100%\">\u003C\u002Ftd>\n    \u003Ctd width=25% style=\"border: none\">\u003Cimg src=\"__assets__\u002Fdemos\u002Fimage\u002FRealisticVision_sunset.png\" style=\"width:100%\">\u003C\u002Ftd>\n    \u003Ctd width=25% style=\"border: none\">\u003Cimg src=\"__assets__\u002Fanimations\u002Fv3\u002Fanimation_sunset.gif\" style=\"width:100%\">\u003C\u002Ftd>\n    \u003C\u002Ftr>\n\u003C\u002Ftable>\n\n\u003Ctable class=\"center\">\n    \u003Ctr style=\"line-height: 0\">\n    \u003Ctd width=25% style=\"border: none; text-align: center\">Input Scribble\u003C\u002Ftd>\n    \u003Ctd width=25% style=\"border: none; text-align: center\">Output\u003C\u002Ftd>\n    \u003Ctd width=25% style=\"border: none; text-align: center\">Input Scribbles\u003C\u002Ftd>\n    \u003Ctd width=25% style=\"border: none; text-align: center\">Output\u003C\u002Ftd>\n    \u003C\u002Ftr>\n    \u003Ctr>\n      \u003Ctd width=25% style=\"border: none\">\u003Cimg src=\"__assets__\u002Fdemos\u002Fscribble\u002Fscribble_1.png\" style=\"width:100%\">\u003C\u002Ftd>\n      \u003Ctd width=25% style=\"border: none\">\u003Cimg src=\"__assets__\u002Fanimations\u002Fv3\u002Fsketch_boy.gif\" style=\"width:100%\">\u003C\u002Ftd>\n      \u003Ctd width=25% style=\"border: none\">\u003Cimg src=\"__assets__\u002Fdemos\u002Fscribble\u002Fscribble_2_readme.png\" style=\"width:100%\">\u003C\u002Ftd>\n      \u003Ctd width=25% style=\"border: none\">\u003Cimg src=\"__assets__\u002Fanimations\u002Fv3\u002Fsketch_city.gif\" style=\"width:100%\">\u003C\u002Ftd>\n    \u003C\u002Ftr>\n\u003C\u002Ftable>\n\n\n### AnimateDiff SDXL-Beta (2023.11)\n\nRelease the Motion Module (beta version) on SDXL, available at [Google Drive](https:\u002F\u002Fdrive.google.com\u002Ffile\u002Fd\u002F1EK_D9hDOPfJdK4z8YDB8JYvPracNx2SX\u002Fview?usp=share_link\n) \u002F [HuggingFace](https:\u002F\u002Fhuggingface.co\u002Fguoyww\u002Fanimatediff\u002Fblob\u002Fmain\u002Fmm_sdxl_v10_beta.ckpt\n) \u002F [CivitAI](https:\u002F\u002Fcivitai.com\u002Fmodels\u002F108836\u002Fanimatediff-motion-modules). High resolution videos (i.e., 1024x1024x16 frames with various aspect ratios) could be produced **with\u002Fwithout** personalized models. Inference usually requires ~13GB VRAM and tuned hyperparameters (e.g., sampling steps), depending on the chosen personalized models.  \nCheckout to the branch [sdxl](https:\u002F\u002Fgithub.com\u002Fguoyww\u002FAnimateDiff\u002Ftree\u002Fsdxl) for more details of the inference.\n\n\u003Cdetails close>\n\u003Csummary>AnimateDiff SDXL-Beta Model Zoo\u003C\u002Fsummary>\n\n| Name | HuggingFace | Type | Storage Space |\n| - | - | - | - |\n| `mm_sdxl_v10_beta.ckpt` | [Link](https:\u002F\u002Fhuggingface.co\u002Fguoyww\u002Fanimatediff\u002Fblob\u002Fmain\u002Fmm_sdxl_v10_beta.ckpt) | Motion Module | 950 MB |\n\u003C\u002Fdetails>\n\n#### Demos\n\u003Ctable class=\"center\">\n    \u003Ctr style=\"line-height: 0\">\n    \u003Ctd width=52% style=\"border: none; text-align: center\">Original SDXL\u003C\u002Ftd>\n    \u003Ctd width=30% style=\"border: none; text-align: center\">Community SDXL\u003C\u002Ftd>\n    \u003Ctd width=18% style=\"border: none; text-align: center\">Community SDXL\u003C\u002Ftd>\n    \u003C\u002Ftr>\n    \u003Ctr>\n    \u003Ctd width=52% style=\"border: none\">\u003Cimg src=\"__assets__\u002Fanimations\u002Fmotion_xl\u002F01.gif\" style=\"width:100%\">\u003C\u002Ftd>\n    \u003Ctd width=30% style=\"border: none\">\u003Cimg src=\"__assets__\u002Fanimations\u002Fmotion_xl\u002F02.gif\" style=\"width:100%\">\u003C\u002Ftd>\n    \u003Ctd width=18% style=\"border: none\">\u003Cimg src=\"__assets__\u002Fanimations\u002Fmotion_xl\u002F03.gif\" style=\"width:100%\">\u003C\u002Ftd>\n    \u003C\u002Ftr>\n\u003C\u002Ftable>\n\n\n### AnimateDiff v2 (2023.09)\n\nIn this version, the motion module `mm_sd_v15_v2.ckpt` ([Google Drive](https:\u002F\u002Fdrive.google.com\u002Fdrive\u002Ffolders\u002F1EqLC65eR1-W-sGD0Im7fkED6c8GkiNFI?usp=sharing) \u002F [HuggingFace](https:\u002F\u002Fhuggingface.co\u002Fguoyww\u002Fanimatediff) \u002F [CivitAI](https:\u002F\u002Fcivitai.com\u002Fmodels\u002F108836\u002Fanimatediff-motion-modules)) is trained upon larger resolution and batch size.\nWe found that the scale-up training significantly helps improve the motion quality and diversity.  \nWe also support **MotionLoRA** of eight basic camera movements.\nMotionLoRA checkpoints take up only **77 MB storage per model**, and are available at [Google Drive](https:\u002F\u002Fdrive.google.com\u002Fdrive\u002Ffolders\u002F1EqLC65eR1-W-sGD0Im7fkED6c8GkiNFI?usp=sharing) \u002F [HuggingFace](https:\u002F\u002Fhuggingface.co\u002Fguoyww\u002Fanimatediff) \u002F [CivitAI](https:\u002F\u002Fcivitai.com\u002Fmodels\u002F108836\u002Fanimatediff-motion-modules).\n\n\u003Cdetails close>\n\u003Csummary>AnimateDiff v2 Model Zoo\u003C\u002Fsummary>\n\n| Name | HuggingFace | Type | Parameter | Storage |\n| - | - | - | - | - |\n| `mm_sd_v15_v2.ckpt` | [Link](https:\u002F\u002Fhuggingface.co\u002Fguoyww\u002Fanimatediff\u002Fblob\u002Fmain\u002Fmm_sd_v15_v2.ckpt) | Motion Module | 453 M | 1.7 GB |\n| `v2_lora_ZoomIn.ckpt` | [Link](https:\u002F\u002Fhuggingface.co\u002Fguoyww\u002Fanimatediff\u002Fblob\u002Fmain\u002Fv2_lora_ZoomIn.ckpt) | MotionLoRA | 19 M | 74 MB |\n| `v2_lora_ZoomOut.ckpt` | [Link](https:\u002F\u002Fhuggingface.co\u002Fguoyww\u002Fanimatediff\u002Fblob\u002Fmain\u002Fv2_lora_ZoomOut.ckpt) | MotionLoRA | 19 M | 74 MB |\n| `v2_lora_PanLeft.ckpt` | [Link](https:\u002F\u002Fhuggingface.co\u002Fguoyww\u002Fanimatediff\u002Fblob\u002Fmain\u002Fv2_lora_PanLeft.ckpt) | MotionLoRA | 19 M | 74 MB |\n| `v2_lora_PanRight.ckpt` | [Link](https:\u002F\u002Fhuggingface.co\u002Fguoyww\u002Fanimatediff\u002Fblob\u002Fmain\u002Fv2_lora_PanRight.ckpt) | MotionLoRA | 19 M | 74 MB |\n| `v2_lora_TiltUp.ckpt` | [Link](https:\u002F\u002Fhuggingface.co\u002Fguoyww\u002Fanimatediff\u002Fblob\u002Fmain\u002Fv2_lora_TiltUp.ckpt) | MotionLoRA | 19 M | 74 MB |\n| `v2_lora_TiltDown.ckpt` | [Link](https:\u002F\u002Fhuggingface.co\u002Fguoyww\u002Fanimatediff\u002Fblob\u002Fmain\u002Fv2_lora_TiltDown.ckpt) | MotionLoRA | 19 M | 74 MB |\n| `v2_lora_RollingClockwise.ckpt` | [Link](https:\u002F\u002Fhuggingface.co\u002Fguoyww\u002Fanimatediff\u002Fblob\u002Fmain\u002Fv2_lora_RollingClockwise.ckpt) | MotionLoRA | 19 M | 74 MB |\n| `v2_lora_RollingAnticlockwise.ckpt` | [Link](https:\u002F\u002Fhuggingface.co\u002Fguoyww\u002Fanimatediff\u002Fblob\u002Fmain\u002Fv2_lora_RollingAnticlockwise.ckpt) | MotionLoRA | 19 M | 74 MB |\n\u003C\u002Fdetails>\n\n\n#### Demos (MotionLoRA)\n\u003Ctable class=\"center\">\n  \u003Ctr style=\"line-height: 0\">\n    \u003Ctd colspan=\"2\" style=\"border: none; text-align: center\">Zoom In\u003C\u002Ftd>\n    \u003Ctd colspan=\"2\" style=\"border: none; text-align: center\">Zoom Out\u003C\u002Ftd>\n    \u003Ctd colspan=\"2\" style=\"border: none; text-align: center\">Zoom Pan Left\u003C\u002Ftd>\n    \u003Ctd colspan=\"2\" style=\"border: none; text-align: center\">Zoom Pan Right\u003C\u002Ftd>\n  \u003C\u002Ftr>\n  \u003Ctr>\n    \u003Ctd style=\"border: none\">\u003Cimg src=\"__assets__\u002Fanimations\u002Fmotion_lora\u002Fmodel_01\u002F01.gif\">\u003C\u002Ftd>\n    \u003Ctd style=\"border: none\">\u003Cimg src=\"__assets__\u002Fanimations\u002Fmotion_lora\u002Fmodel_02\u002F02.gif\">\u003C\u002Ftd>\n    \u003Ctd style=\"border: none\">\u003Cimg src=\"__assets__\u002Fanimations\u002Fmotion_lora\u002Fmodel_01\u002F02.gif\">\u003C\u002Ftd>\n    \u003Ctd style=\"border: none\">\u003Cimg src=\"__assets__\u002Fanimations\u002Fmotion_lora\u002Fmodel_02\u002F01.gif\">\u003C\u002Ftd>\n    \u003Ctd style=\"border: none\">\u003Cimg src=\"__assets__\u002Fanimations\u002Fmotion_lora\u002Fmodel_01\u002F03.gif\">\u003C\u002Ftd>\n    \u003Ctd style=\"border: none\">\u003Cimg src=\"__assets__\u002Fanimations\u002Fmotion_lora\u002Fmodel_02\u002F04.gif\">\u003C\u002Ftd>\n    \u003Ctd style=\"border: none\">\u003Cimg src=\"__assets__\u002Fanimations\u002Fmotion_lora\u002Fmodel_01\u002F04.gif\">\u003C\u002Ftd>\n    \u003Ctd style=\"border: none\">\u003Cimg src=\"__assets__\u002Fanimations\u002Fmotion_lora\u002Fmodel_02\u002F03.gif\">\u003C\u002Ftd>\n  \u003C\u002Ftr>\n  \u003Ctr style=\"line-height: 0\">\n    \u003Ctd colspan=\"2\" style=\"border: none; text-align: center\">Tilt Up\u003C\u002Ftd>\n    \u003Ctd colspan=\"2\" style=\"border: none; text-align: center\">Tilt Down\u003C\u002Ftd>\n    \u003Ctd colspan=\"2\" style=\"border: none; text-align: center\">Rolling Anti-Clockwise\u003C\u002Ftd>\n    \u003Ctd colspan=\"2\" style=\"border: none; text-align: center\">Rolling Clockwise\u003C\u002Ftd>\n  \u003C\u002Ftr>\n  \u003Ctr>\n    \u003Ctd style=\"border: none\">\u003Cimg src=\"__assets__\u002Fanimations\u002Fmotion_lora\u002Fmodel_01\u002F05.gif\">\u003C\u002Ftd>\n    \u003Ctd style=\"border: none\">\u003Cimg src=\"__assets__\u002Fanimations\u002Fmotion_lora\u002Fmodel_02\u002F05.gif\">\u003C\u002Ftd>\n    \u003Ctd style=\"border: none\">\u003Cimg src=\"__assets__\u002Fanimations\u002Fmotion_lora\u002Fmodel_01\u002F06.gif\">\u003C\u002Ftd>\n    \u003Ctd style=\"border: none\">\u003Cimg src=\"__assets__\u002Fanimations\u002Fmotion_lora\u002Fmodel_02\u002F06.gif\">\u003C\u002Ftd>\n    \u003Ctd style=\"border: none\">\u003Cimg src=\"__assets__\u002Fanimations\u002Fmotion_lora\u002Fmodel_01\u002F07.gif\">\u003C\u002Ftd>\n    \u003Ctd style=\"border: none\">\u003Cimg src=\"__assets__\u002Fanimations\u002Fmotion_lora\u002Fmodel_02\u002F07.gif\">\u003C\u002Ftd>\n    \u003Ctd style=\"border: none\">\u003Cimg src=\"__assets__\u002Fanimations\u002Fmotion_lora\u002Fmodel_01\u002F08.gif\">\u003C\u002Ftd>\n    \u003Ctd style=\"border: none\">\u003Cimg src=\"__assets__\u002Fanimations\u002Fmotion_lora\u002Fmodel_02\u002F08.gif\">\u003C\u002Ftd>\n  \u003C\u002Ftr>\n\u003C\u002Ftable>\n\n\n#### Demos (Improved Motions)\nHere's a comparison between `mm_sd_v15.ckpt` (left) and improved `mm_sd_v15_v2.ckpt` (right).\n\n\u003Ctable class=\"center\">\n  \u003Ctr>\n    \u003Ctd>\u003Cimg src=\"__assets__\u002Fanimations\u002Fcompare\u002Fold_0.gif\">\u003C\u002Ftd>\n    \u003Ctd>\u003Cimg src=\"__assets__\u002Fanimations\u002Fcompare\u002Fnew_0.gif\">\u003C\u002Ftd>\n    \u003Ctd>\u003Cimg src=\"__assets__\u002Fanimations\u002Fcompare\u002Fold_1.gif\">\u003C\u002Ftd>\n    \u003Ctd>\u003Cimg src=\"__assets__\u002Fanimations\u002Fcompare\u002Fnew_1.gif\">\u003C\u002Ftd>\n    \u003Ctd>\u003Cimg src=\"__assets__\u002Fanimations\u002Fcompare\u002Fold_2.gif\">\u003C\u002Ftd>\n    \u003Ctd>\u003Cimg src=\"__assets__\u002Fanimations\u002Fcompare\u002Fnew_2.gif\">\u003C\u002Ftd>\n    \u003Ctd>\u003Cimg src=\"__assets__\u002Fanimations\u002Fcompare\u002Fold_3.gif\">\u003C\u002Ftd>\n    \u003Ctd>\u003Cimg src=\"__assets__\u002Fanimations\u002Fcompare\u002Fnew_3.gif\">\u003C\u002Ftd>\n  \u003C\u002Ftr>\n\u003C\u002Ftable>\n\n\n### AnimateDiff v1 (2023.07)\n\nThe first version of AnimateDiff!\n\n\u003Cdetails close>\n\u003Csummary>AnimateDiff v1 Model Zoo\u003C\u002Fsummary>\n\n| Name | HuggingFace | Parameter | Storage Space |\n| - | - | - | - |\n| mm_sd_v14.ckpt | [Link](https:\u002F\u002Fhuggingface.co\u002Fguoyww\u002Fanimatediff\u002Fblob\u002Fmain\u002Fmm_sd_v14.ckpt) | 417 M | 1.6 GB |\n| mm_sd_v15.ckpt | [Link](https:\u002F\u002Fhuggingface.co\u002Fguoyww\u002Fanimatediff\u002Fblob\u002Fmain\u002Fmm_sd_v15.ckpt) | 417 M | 1.6 GB |\n\u003C\u002Fdetails>\n\n\u003C\u002Fdetails>\n\n\n## Training\nPlease check [Steps for Training](__assets__\u002Fdocs\u002Fanimatediff.md) for details.\n\n\n## Related Resources\n\nAnimateDiff for Stable Diffusion WebUI: [sd-webui-animatediff](https:\u002F\u002Fgithub.com\u002Fcontinue-revolution\u002Fsd-webui-animatediff) (by [@continue-revolution](https:\u002F\u002Fgithub.com\u002Fcontinue-revolution))  \nAnimateDiff for ComfyUI: [ComfyUI-AnimateDiff-Evolved](https:\u002F\u002Fgithub.com\u002FKosinkadink\u002FComfyUI-AnimateDiff-Evolved) (by [@Kosinkadink](https:\u002F\u002Fgithub.com\u002FKosinkadink))  \nGoogle Colab: [Colab](https:\u002F\u002Fcolab.research.google.com\u002Fgithub\u002Fcamenduru\u002FAnimateDiff-colab\u002Fblob\u002Fmain\u002FAnimateDiff_colab.ipynb) (by [@camenduru](https:\u002F\u002Fgithub.com\u002Fcamenduru))\n\n\n## Disclaimer\nThis project is released for academic use.\nWe disclaim responsibility for user-generated content.\nAlso, please be advised that our only official website are https:\u002F\u002Fgithub.com\u002Fguoyww\u002FAnimateDiff and https:\u002F\u002Fanimatediff.github.io, and all the other websites are NOT associated with us at AnimateDiff. \n\n\n## Contact Us\nYuwei Guo: [guoyw@ie.cuhk.edu.hk](mailto:guoyw@ie.cuhk.edu.hk)  \nCeyuan Yang: [limbo0066@gmail.com](mailto:limbo0066@gmail.com)  \nBo Dai: [doubledaibo@gmail.com](mailto:doubledaibo@gmail.com)\n\n\n## BibTeX\n```\n@article{guo2023animatediff,\n  title={AnimateDiff: Animate Your Personalized Text-to-Image Diffusion Models without Specific Tuning},\n  author={Guo, Yuwei and Yang, Ceyuan and Rao, Anyi and Liang, Zhengyang and Wang, Yaohui and Qiao, Yu and Agrawala, Maneesh and Lin, Dahua and Dai, Bo},\n  journal={International Conference on Learning Representations},\n  year={2024}\n}\n\n@article{guo2023sparsectrl,\n  title={SparseCtrl: Adding Sparse Controls to Text-to-Video Diffusion Models},\n  author={Guo, Yuwei and Yang, Ceyuan and Rao, Anyi and Agrawala, Maneesh and Lin, Dahua and Dai, Bo},\n  journal={arXiv preprint arXiv:2311.16933},\n  year={2023}\n}\n```\n\n\n## Acknowledgements\nCodebase built upon [Tune-a-Video](https:\u002F\u002Fgithub.com\u002Fshowlab\u002FTune-A-Video).\n","AnimateDiff 是一个将文本到图像模型转换为动画生成器的插件模块，无需额外训练。其核心功能在于能够无缝集成到现有的社区文本到图像模型中，通过简单的配置即可生成高质量的动画内容，支持包括Stable Diffusion V1.5在内的多种模型。技术上，该项目基于Python开发，并遵循Apache License 2.0开源协议，确保了广泛的可用性和灵活性。特别适合于创意设计、动画制作以及任何需要快速从静态图片生成动态视觉效果的应用场景中使用。",2,"2026-06-11 03:35:12","high_star"]