

Diffree
Overview :
Diffree is a text-guided image restoration model capable of adding new objects to images based on text descriptions while maintaining background consistency, spatial appropriateness, and the quality and relevance of the objects. This model was trained on the OABench dataset, utilizing a stable diffusion model along with an additional mask prediction module, enabling it to uniquely predict the locations of new objects for text-guided object addition.
Target Users :
The target audience includes image editors, designers, researchers, and any users who need to add new objects to images. Diffree is ideal for them as it offers a rapid and natural method to add objects to images without manual intervention.
Use Cases
Use Diffree to add flying birds to landscape photos, enhancing the vividness of the scene.
Add virtual products to promotional images for market testing.
In historical scene reconstructions, add missing elements based on descriptions.
Features
Text-to-image model that realizes text-guided object addition
Trained using advanced image restoration techniques on the OABench dataset
Features a unique mask prediction module that predicts the locations of new objects
Maintains background consistency when adding objects
Supports the iterative addition of multiple objects within the same image
Applicable for object addition in various natural scenes
High success rate ensuring the quality and relevance of added objects
How to Use
1. Visit Diffree's online demo page.
2. Read and comprehend the usage instructions and requirements of Diffree.
3. Provide or input a text description of the object you want to add to the image.
4. Upload the original image or select an existing image sample.
5. Diffree will generate a mask and an image of the new object based on the text description and the original image.
6. Review the generated results to ensure the newly added object meets your expectations.
7. If needed, make iterative adjustments until satisfied.
8. Download or directly use the generated image.
Featured AI Tools

SUPIR
SUPIR is a groundbreaking image repair method utilizing the power of generative priors and model expansion. Through multi-modal techniques and advanced generative priors, SUPIR has made significant strides in intelligent and realistic image repair. Model expansion, a key catalyst within SUPIR, has significantly enhanced its capabilities, revealing new potential in image repair. We trained our model on a dataset of 20 million high-resolution, high-quality images, each accompanied by descriptive textual annotations. SUPIR can repair images based on text prompts, broadening its application range and potential. Furthermore, we introduced negative quality prompts to further improve perceived quality. We also developed a repair-guided sampling method to mitigate the fidelity issues encountered in generative repair. Experiments have demonstrated SUPIR's outstanding repair effects and its novel ability to manipulate repairs through text prompts.
AI Image Restoration
490.5K

Remove Background Webgpu
remove-background-webgpu is a browser-based mini-program that utilizes WebGPU technology to achieve fast image background removal. It allows users to quickly obtain images without backgrounds without downloading any additional software.
AI Image Editing
226.9K