The swin2sr model has several potential use cases for technical users. One application could be in the field of image editing and enhancement, where the model can be used to increase the resolution and quality of low-resolution images, improving their overall visual appearance. This could be particularly useful in industries such as photography, graphic design, and advertising, where high-quality visuals are crucial. The model could also be used in the field of video production to enhance the resolution and quality of video footage, resulting in sharper and more detailed final products. Additionally, the swin2sr model could find applications in various scientific fields, such as medical imaging or satellite imaging, where the ability to enhance image resolution and quality could aid in analysis and interpretation. Overall, the model opens up possibilities for developing products or practical tools that leverage its capabilities, such as image editing software, video processing applications, or specialized scientific image analysis tools.
- Cost per run
- Avg run time
- Nvidia T4 GPU
|No other models by this creator|
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Summary of this model and related resources.
3 Million Runs! AI Photorealistic Image Super-Resolution and Restoration
|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||$0.0154|
|Prediction Hardware||Nvidia T4 GPU|
|Average Completion Time||28 seconds|