Instructions to use jdopensource/JoyAI-Image-Edit-Diffusers with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use jdopensource/JoyAI-Image-Edit-Diffusers with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline from diffusers.utils import load_image # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("jdopensource/JoyAI-Image-Edit-Diffusers", dtype=torch.bfloat16, device_map="cuda") prompt = "Turn this cat into a dog" input_image = load_image("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/diffusers/cat.png") image = pipe(image=input_image, prompt=prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Upload README.md with huggingface_hub
Browse files
README.md
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@@ -114,8 +114,8 @@ Move the <object> into the red box and finally remove the red box.
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Move the board into the red box and finally remove the red box.
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#### 2. Object Rotation
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Rotate the dog to show the left side view.
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## License Agreement
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Move the board into the red box and finally remove the red box.
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```
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<img src="test_images/input1.png" width="40%" />
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<img src="test_images/output1_predicted.png" width="40%" />
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</p>
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#### 2. Object Rotation
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Rotate the dog to show the left side view.
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```
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<p align="center">
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<img src="test_images/input2.png" width="40%" />
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<img src="test_images/output2_predicted.png" width="40%" />
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</p>
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- Keep the 3D scene static; only change the viewpoint.
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```
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<p align="center">
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<img src="test_images/input3.png" width="40%" />
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<img src="test_images/output3_predicted.png" width="40%" />
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</p>
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## License Agreement
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