AI prompts
base on Lifting ControlNet for Generalized Depth Conditioning # LooseControl: Lifting ControlNet for Generalized Depth Conditioning
[](https://huggingface.co/spaces/shariqfarooq/LooseControl)
[](https://opensource.org/licenses/MIT) 
This is the official repository for our paper:
>#### [LooseControl: Lifting ControlNet for Generalized Depth Conditioning](#)
> ##### [Shariq Farooq Bhat](https://shariqfarooq123.github.io), [Niloy J. Mitra](http://www0.cs.ucl.ac.uk/staff/n.mitra/), [Peter Wonka](http://peterwonka.net/)
[[Project Page]](https://shariqfarooq123.github.io/loose-control/) [[Paper]](https://arxiv.org/abs/2312.03079) [[Demo 🤗]](https://huggingface.co/spaces/shariqfarooq/LooseControl) [[Weights (3D Box Control)]](https://huggingface.co/shariqfarooq/loose-control-3dbox)
# Usage
```bash
git clone https://github.com/shariqfarooq123/LooseControl && cd LooseControl
```
Start the UI:
```python
gradio app.py
```
or use via python API:
```python
from loosecontrol import LooseControlNet
lcn = LooseControlNet("shariqfarooq/loose-control-3dbox")
boxy_depth = ...
prompt = "A photo of a snowman in a desert"
negative_prompt = "blurry, text, caption, lowquality,lowresolution, low res, grainy, ugly"
gen_image_1 = lcn(prompt, negative_prompt=negative_prompt, control_image=boxy_depth)
```
Style preserving edits:
```python
# Fix the 'style' and edit
# Edit 'boxy_depth' -> 'boxy_depth_edited'
lcn.set_cf_attention()
gen_image_edited = lcn.edit(boxy_depth, boxy_depth_edited, prompt, negative_prompt=negative_prompt)
```
# Credits
The Cross Frame attention is adapted from [Text2Video-Zero](https://github.com/Picsart-AI-Research/Text2Video-Zero)
# Citation
```bibtex
@misc{bhat2023loosecontrol,
title={LooseControl: Lifting ControlNet for Generalized Depth Conditioning},
author={Shariq Farooq Bhat and Niloy J. Mitra and Peter Wonka},
year={2023},
eprint={2312.03079},
archivePrefix={arXiv},
primaryClass={cs.CV}
}
```
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