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---
license: mit
---
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# Re-implementation of ControlNet with Shape Masks
[[`GitHub`]](https://github.com/AlonzoLeeeooo/shape-guided-controlnet) / [[`Dataset`]](https://huggingface.co/datasets/AlonzoLeeeooo/COCO2014-train-u2net-masks)
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A re-implementation of ControlNet with shape masks.
# Model Weights Structure
```
shape-guided-controlnet/
└── annotators <----- Model weights of the shape mask annotator (`U2-Net`)
└── u2net.pth
└── shape-guided-controlnet <----- Model weights of the trained ControlNet with shape masks
├── config.json
└── diffusion_pytorch_model.safetensors
└── stable-diffusion-v1.5 <----- Model weights of Stable Diffusion v1.5
├── feature_extractor
├── scheduler
├── text_encoder
├── tokenizer
├── unet
├── vae
├── model_index.json
├── v1-5-pruned.safetensors
└── v1-inference.yaml
```
# Results
Here are some example results generated by the trained model:
1. "A red bag"
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<img src="assets/bag_total.png" alt="Bag" width="500" />
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2. "A sport car"
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<img src="assets/sport_car_total.png" alt="Sport Car" width="500" />
</div>
3. "A blue truck"
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<img src="assets/truck_total.png" alt="Truck" width="500" />
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