Large Hole Image Inpainting
The MAT model for large hole image inpainting has a wide range of potential use cases for various industries. In the field of digital editing and design, this model can be used to seamlessly remove unwanted objects or structures from images, allowing for more aesthetically pleasing compositions. It can also be employed in the restoration of old or damaged photographs, intelligently filling in missing areas and preserving the integrity of the original image. In the field of surveillance and security, this model can be used for enhancing and reconstructing images with obscured or missing data, aiding in forensic investigations. Additionally, in the realm of virtual reality and gaming, the MAT model can be utilized to generate realistic and immersive environments by efficiently inpainting large areas that are yet to be rendered or captured. In terms of practical applications, this model can be integrated into photo editing software, restoration tools, or even image and video compression algorithms to improve the quality and visual integrity of the final output.
- Cost per run
- Avg run time
- Nvidia T4 GPU
|No other models by this creator|
You can use this area to play around with demo applications that incorporate the Large Hole Image Inpainting model. These demos are maintained and hosted externally by third-party creators. If you see an error, message me on Twitter.
Currently, there are no demos available for this model.
Summary of this model and related resources.
|Model Name||Large Hole Image Inpainting|
MAT: Mask-Aware Transformer for Large Hole Image Inpainting
|Model Link||View on Replicate|
|API Spec||View on Replicate|
|Github Link||View on Github|
|Paper Link||View on Arxiv|
How popular is this model, by number of runs? How popular is the creator, by the sum of all their runs?
How much does it cost to run this model? How long, on average, does it take to complete a run?
|Cost per Run||$0.0011|
|Prediction Hardware||Nvidia T4 GPU|
|Average Completion Time||2 seconds|