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[NIPS 2024] Official code for FastDrag

FastDrag: Manipulate Anything in One Step

Xuanjia ZhaoJian GuanCongyi FanDongli Xu
Youtian LinHaiwei PanPengming Feng


arXivpage


Installation

To install the required libraries, simply run the following command:

conda env create -f environment.yaml
conda activate fastdrag

Config

If you want download huggingface weights in local, you should download runwayml/stable-diffusion-v1-5 and SimianLuo/LCM_Dreamshaper_v7.

  • Suggestion 1: It is suggested that download the model into the directory "local_pretrained_models";
  • Suggestion 2: runwayml/stable-diffusion-v1-5 might not exist in huggingface, but can be found in other websites like gitee.

Then you can set path in config as below: config

Run Fastdrag

To start with, in command line, run the following to start the gradio user interface:

python drag_ui.py

For users struggling in loading models from huggingface due to internet constraint, please run:

sh run_drag.sh

License

Code related to the FastDrag algorithm is under Apache 2.0 license.

BibTeX

If you find our repo helpful, please consider leaving a star or cite our paper :)

@inproceedings{
zhao2024fastdrag,
title={FastDrag: Manipulate Anything in One Step},
author={Xuanjia Zhao and Jian Guan and Congyi Fan and Dongli Xu and Youtian Lin and Haiwei Pan and Pengming Feng},
booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems},
year={2024}
}

Acknowledgement

The code is built based on DragDiffusion and diffusers, thanks for their outstanding work!

Notice

For the fisrt time to run, it may be slow, but it will perform normally afterwards.

About

[NIPS 2024] Official code for FastDrag

Resources

Readme
Apache-2.0 license
Activity

Stars

28 stars

Watchers

1 watching

Forks

3 forks
Report repository

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

Skip to content
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[NIPS 2024] Official code for FastDrag
FastDrag: Manipulate Anything in One Step
Xuanjia ZhaoJian GuanCongyi FanDongli Xu
Youtian LinHaiwei PanPengming Feng

arXivpage

Installation
To install the required libraries, simply run the following command:
conda env create -f environment.yaml
conda activate fastdrag

Config
If you want download huggingface weights in local, you should download runwayml/stable-diffusion-v1-5 and SimianLuo/LCM_Dreamshaper_v7.
  • Suggestion 1: It is suggested that download the model into the directory "local_pretrained_models";
  • Suggestion 2: runwayml/stable-diffusion-v1-5 might not exist in huggingface, but can be found in other websites like gitee.
Then you can set path in config as below:
config
Run Fastdrag
To start with, in command line, run the following to start the gradio user interface:
python drag_ui.py

For users struggling in loading models from huggingface due to internet constraint, please run:
sh run_drag.sh

License
Code related to the FastDrag algorithm is under Apache 2.0 license.
BibTeX
If you find our repo helpful, please consider leaving a star or cite our paper :)
@inproceedings{
zhao2024fastdrag,
title={FastDrag: Manipulate Anything in One Step},
author={Xuanjia Zhao and Jian Guan and Congyi Fan and Dongli Xu and Youtian Lin and Haiwei Pan and Pengming Feng},
booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems},
year={2024}
}
Acknowledgement
The code is built based on DragDiffusion and diffusers, thanks for their outstanding work!
Notice
For the fisrt time to run, it may be slow, but it will perform normally afterwards.
About
[NIPS 2024] Official code for FastDrag
Resources
Readme
Apache-2.0 license
Activity
Stars
28 stars
Watchers
1 watching
Forks
3 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
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[NIPS 2024] Official code for FastDrag
FastDrag: Manipulate Anything in One Step
Xuanjia ZhaoJian GuanCongyi FanDongli Xu
Youtian LinHaiwei PanPengming Feng

arXivpage

Installation
To install the required libraries, simply run the following command:
conda env create -f environment.yaml
conda activate fastdrag

Config
If you want download huggingface weights in local, you should download runwayml/stable-diffusion-v1-5 and SimianLuo/LCM_Dreamshaper_v7.
  • Suggestion 1: It is suggested that download the model into the directory "local_pretrained_models";
  • Suggestion 2: runwayml/stable-diffusion-v1-5 might not exist in huggingface, but can be found in other websites like gitee.
Then you can set path in config as below:
config
Run Fastdrag
To start with, in command line, run the following to start the gradio user interface:
python drag_ui.py

For users struggling in loading models from huggingface due to internet constraint, please run:
sh run_drag.sh

License
Code related to the FastDrag algorithm is under Apache 2.0 license.
BibTeX
If you find our repo helpful, please consider leaving a star or cite our paper :)
@inproceedings{
zhao2024fastdrag,
title={FastDrag: Manipulate Anything in One Step},
author={Xuanjia Zhao and Jian Guan and Congyi Fan and Dongli Xu and Youtian Lin and Haiwei Pan and Pengming Feng},
booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems},
year={2024}
}
Acknowledgement
The code is built based on DragDiffusion and diffusers, thanks for their outstanding work!
Notice
For the fisrt time to run, it may be slow, but it will perform normally afterwards.
About
[NIPS 2024] Official code for FastDrag
Resources
Readme
Apache-2.0 license
Activity
Stars
28 stars
Watchers
1 watching
Forks
3 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
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[NIPS 2024] Official code for FastDrag
FastDrag: Manipulate Anything in One Step
Xuanjia ZhaoJian GuanCongyi FanDongli Xu
Youtian LinHaiwei PanPengming Feng

arXivpage

Installation
To install the required libraries, simply run the following command:
conda env create -f environment.yaml
conda activate fastdrag

Config
If you want download huggingface weights in local, you should download runwayml/stable-diffusion-v1-5 and SimianLuo/LCM_Dreamshaper_v7.
  • Suggestion 1: It is suggested that download the model into the directory "local_pretrained_models";
  • Suggestion 2: runwayml/stable-diffusion-v1-5 might not exist in huggingface, but can be found in other websites like gitee.
Then you can set path in config as below:
config
Run Fastdrag
To start with, in command line, run the following to start the gradio user interface:
python drag_ui.py

For users struggling in loading models from huggingface due to internet constraint, please run:
sh run_drag.sh

License
Code related to the FastDrag algorithm is under Apache 2.0 license.
BibTeX
If you find our repo helpful, please consider leaving a star or cite our paper :)
@inproceedings{
zhao2024fastdrag,
title={FastDrag: Manipulate Anything in One Step},
author={Xuanjia Zhao and Jian Guan and Congyi Fan and Dongli Xu and Youtian Lin and Haiwei Pan and Pengming Feng},
booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems},
year={2024}
}
Acknowledgement
The code is built based on DragDiffusion and diffusers, thanks for their outstanding work!
Notice
For the fisrt time to run, it may be slow, but it will perform normally afterwards.
About
[NIPS 2024] Official code for FastDrag
Resources
Readme
Apache-2.0 license
Activity
Stars
28 stars
Watchers
1 watching
Forks
3 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

Skip to content
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[NIPS 2024] Official code for FastDrag
FastDrag: Manipulate Anything in One Step
Xuanjia ZhaoJian GuanCongyi FanDongli Xu
Youtian LinHaiwei PanPengming Feng

arXivpage

Installation
To install the required libraries, simply run the following command:
conda env create -f environment.yaml
conda activate fastdrag

Config
If you want download huggingface weights in local, you should download runwayml/stable-diffusion-v1-5 and SimianLuo/LCM_Dreamshaper_v7.
  • Suggestion 1: It is suggested that download the model into the directory "local_pretrained_models";
  • Suggestion 2: runwayml/stable-diffusion-v1-5 might not exist in huggingface, but can be found in other websites like gitee.
Then you can set path in config as below:
config
Run Fastdrag
To start with, in command line, run the following to start the gradio user interface:
python drag_ui.py

For users struggling in loading models from huggingface due to internet constraint, please run:
sh run_drag.sh

License
Code related to the FastDrag algorithm is under Apache 2.0 license.
BibTeX
If you find our repo helpful, please consider leaving a star or cite our paper :)
@inproceedings{
zhao2024fastdrag,
title={FastDrag: Manipulate Anything in One Step},
author={Xuanjia Zhao and Jian Guan and Congyi Fan and Dongli Xu and Youtian Lin and Haiwei Pan and Pengming Feng},
booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems},
year={2024}
}
Acknowledgement
The code is built based on DragDiffusion and diffusers, thanks for their outstanding work!
Notice
For the fisrt time to run, it may be slow, but it will perform normally afterwards.
About
[NIPS 2024] Official code for FastDrag
Resources
Readme
Apache-2.0 license
Activity
Stars
28 stars
Watchers
1 watching
Forks
3 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
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[NIPS 2024] Official code for FastDrag
FastDrag: Manipulate Anything in One Step
Xuanjia ZhaoJian GuanCongyi FanDongli Xu
Youtian LinHaiwei PanPengming Feng

arXivpage

Installation
To install the required libraries, simply run the following command:
conda env create -f environment.yaml
conda activate fastdrag

Config
If you want download huggingface weights in local, you should download runwayml/stable-diffusion-v1-5 and SimianLuo/LCM_Dreamshaper_v7.
  • Suggestion 1: It is suggested that download the model into the directory "local_pretrained_models";
  • Suggestion 2: runwayml/stable-diffusion-v1-5 might not exist in huggingface, but can be found in other websites like gitee.
Then you can set path in config as below:
config
Run Fastdrag
To start with, in command line, run the following to start the gradio user interface:
python drag_ui.py

For users struggling in loading models from huggingface due to internet constraint, please run:
sh run_drag.sh

License
Code related to the FastDrag algorithm is under Apache 2.0 license.
BibTeX
If you find our repo helpful, please consider leaving a star or cite our paper :)
@inproceedings{
zhao2024fastdrag,
title={FastDrag: Manipulate Anything in One Step},
author={Xuanjia Zhao and Jian Guan and Congyi Fan and Dongli Xu and Youtian Lin and Haiwei Pan and Pengming Feng},
booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems},
year={2024}
}
Acknowledgement
The code is built based on DragDiffusion and diffusers, thanks for their outstanding work!
Notice
For the fisrt time to run, it may be slow, but it will perform normally afterwards.
About
[NIPS 2024] Official code for FastDrag
Resources
Readme
Apache-2.0 license
Activity
Stars
28 stars
Watchers
1 watching
Forks
3 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

Skip to content
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[NIPS 2024] Official code for FastDrag
FastDrag: Manipulate Anything in One Step
Xuanjia ZhaoJian GuanCongyi FanDongli Xu
Youtian LinHaiwei PanPengming Feng

arXivpage

Installation
To install the required libraries, simply run the following command:
conda env create -f environment.yaml
conda activate fastdrag

Config
If you want download huggingface weights in local, you should download runwayml/stable-diffusion-v1-5 and SimianLuo/LCM_Dreamshaper_v7.
  • Suggestion 1: It is suggested that download the model into the directory "local_pretrained_models";
  • Suggestion 2: runwayml/stable-diffusion-v1-5 might not exist in huggingface, but can be found in other websites like gitee.
Then you can set path in config as below:
config
Run Fastdrag
To start with, in command line, run the following to start the gradio user interface:
python drag_ui.py

For users struggling in loading models from huggingface due to internet constraint, please run:
sh run_drag.sh

License
Code related to the FastDrag algorithm is under Apache 2.0 license.
BibTeX
If you find our repo helpful, please consider leaving a star or cite our paper :)
@inproceedings{
zhao2024fastdrag,
title={FastDrag: Manipulate Anything in One Step},
author={Xuanjia Zhao and Jian Guan and Congyi Fan and Dongli Xu and Youtian Lin and Haiwei Pan and Pengming Feng},
booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems},
year={2024}
}
Acknowledgement
The code is built based on DragDiffusion and diffusers, thanks for their outstanding work!
Notice
For the fisrt time to run, it may be slow, but it will perform normally afterwards.
About
[NIPS 2024] Official code for FastDrag
Resources
Readme
Apache-2.0 license
Activity
Stars
28 stars
Watchers
1 watching
Forks
3 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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[NIPS 2024] Official code for FastDrag
FastDrag: Manipulate Anything in One Step
Xuanjia ZhaoJian GuanCongyi FanDongli Xu
Youtian LinHaiwei PanPengming Feng

arXivpage

Installation
To install the required libraries, simply run the following command:
conda env create -f environment.yaml
conda activate fastdrag

Config
If you want download huggingface weights in local, you should download runwayml/stable-diffusion-v1-5 and SimianLuo/LCM_Dreamshaper_v7.
  • Suggestion 1: It is suggested that download the model into the directory "local_pretrained_models";
  • Suggestion 2: runwayml/stable-diffusion-v1-5 might not exist in huggingface, but can be found in other websites like gitee.
Then you can set path in config as below:
config
Run Fastdrag
To start with, in command line, run the following to start the gradio user interface:
python drag_ui.py

For users struggling in loading models from huggingface due to internet constraint, please run:
sh run_drag.sh

License
Code related to the FastDrag algorithm is under Apache 2.0 license.
BibTeX
If you find our repo helpful, please consider leaving a star or cite our paper :)
@inproceedings{
zhao2024fastdrag,
title={FastDrag: Manipulate Anything in One Step},
author={Xuanjia Zhao and Jian Guan and Congyi Fan and Dongli Xu and Youtian Lin and Haiwei Pan and Pengming Feng},
booktitle={The Thirty-eighth Annual Conference on Neural Information Processing Systems},
year={2024}
}
Acknowledgement
The code is built based on DragDiffusion and diffusers, thanks for their outstanding work!
Notice
For the fisrt time to run, it may be slow, but it will perform normally afterwards.
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[NIPS 2024] Official code for FastDrag
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