t2i-adapter
Maintainer: cjwbw
3
| Property | Value |
|---|---|
| Run this model | Run on Replicate |
| API spec | View on Replicate |
| Github link | View on Github |
| Paper link | View on Arxiv |
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Model overview
The t2i-adapter is a simple and small (~70M parameters, ~300M storage space) network developed by TencentARC that can provide extra guidance to pre-trained text-to-image models like Stable Diffusion while freezing the original large text-to-image models. The t2i-adapter aligns internal knowledge in text-to-image models with external control signals, allowing users to train various adapters according to different conditions and achieve rich control and editing effects. Unlike the larger Stable Diffusion model, the t2i-adapter is a relatively small and simple network that can be easily integrated as a "plug-and-play" module into other text-to-image models like Anything v4.0.
Model inputs and outputs
The t2i-adapter takes in a text prompt and an input image (or other control signals like sketches, keyposes, or segmentation maps) and generates an output image guided by the provided control signals. The input image can be used to condition the generation, allowing for effects like sketch-to-image translation, keypose-guided generation, and segmentation-based editing.
Inputs
- Prompt: The text prompt describing the desired image
- Input Image: An input image (or other control signal) to guide the text-to-image generation
- Model Checkpoint: The base text-to-image model to use, such as Stable Diffusion or Anything v4.0
- Sampling Settings: Various parameters to control the image generation process, such as number of inference steps, guidance scale, and more
Outputs
- Generated Image(s): One or more images generated based on the provided prompt and input control signal
Capabilities
The t2i-adapter can leverage various control signals like sketches, keyposes, and segmentation maps to guide the text-to-image generation process. For example, with the sketch adapter, users can provide a hand-drawn sketch and the model will generate an image matching the sketch. Similarly, the keypose adapter can generate images based on provided keypose information, and the segmentation adapter can edit images based on segmentation maps.
Additionally, the t2i-adapter can be easily integrated as a "plug-and-play" module into other text-to-image models like Anything v4.0, allowing users to combine the capabilities of the t2i-adapter with the larger and more powerful base model.
What can I use it for?
The t2i-adapter can be used for a variety of creative and practical applications, such as:
- Sketch-to-image generation: Create images from hand-drawn sketches or edge maps
- Keypose-guided generation: Generate images based on provided keypose information, such as the pose of a person or animal
- Segmentation-based editing: Edit images by modifying segmentation maps
- Sequential editing: Perform iterative editing of an image by providing additional control signals
- Composable guidance: Combine multiple control signals (e.g., segmentation and sketch) to guide the image generation process
The small size and plug-and-play nature of the t2i-adapter make it a versatile tool that can be easily integrated into various text-to-image pipelines to enhance their capabilities.
Things to try
One interesting aspect of the t2i-adapter is its ability to combine different concepts and control signals to guide the image generation process. For example, you could try generating an image of "a car with flying wings" by providing a sketch or segmentation map of a car and using the t2i-adapter to incorporate the concept of "flying wings" into the final output.
Another interesting application is local editing, where you can use the sketch adapter to modify specific parts of an existing image, such as changing the head direction of a cat or adding rabbit ears to an Iron Man figure. This allows for fine-grained control and creative experimentation.
Overall, the t2i-adapter is a powerful and versatile tool that can unlock new possibilities in text-to-image generation and editing. By experimenting with the various control signals and integrating it with other models, you can unleash your creativity and explore the full potential of this innovative technology.
This summary was produced with help from an AI and may contain inaccuracies - check out the links to read the original source documents!
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