Have you ever wanted different objects from different photos to appear in one scene? Manually prompting for Diffusion can be time-consuming as it requires describing the details (shape, color, textual features) of the objects. Alternatively, using GPT to describe the object for us involves multiple steps.

Here, I introduce a complete pipeline that takes two images as input, allowing you to choose which objects from the images you want to fuse seamlessly.

🚀 Features

Combine objects from two different images into a single scene.
Easy selection and customization of objects to be fused.
Optimized integration with ComfyUI.

🖼️ Some Examples

Click to expand/collapse

🛠️ Installation

Clone this repo into the custom_nodes directory in ComfyUI:
```
git clone https://github.com/your-repo/custom_nodes
```
Install the required packages:
```
pip install -r myreqs.txt
```
Clone these amazing repositories and follow their instructions:
- ComfyUI-SD3-nodes
  Note: Place the 3 clips model into models/clip.
- img2txt-comfyui-nodes
- ComfyUI-Custom-Scripts

📌 Note

All the folders, except CROP_OBJECT, are from other repositories. However, I have made some minor modifications to fit this project. Here are the details:

Custom_ComfyUI-YoloWorld-EfficientSAM
- Added 2 output fields: BBOX, categories.
- Displayed ID also in the IMAGE output (e.g., {ID} - {class} - {confidence}).
comfyui-llm-assistant
- Removed input field: prompt.
- Added 4 input fields: object1, desc_obj1, object2, desc_obj2.

🤝 Contributing

Contributions are welcome! Please open an issue or submit a pull request.

📄 License

This project is licensed under the MIT License.