Arbsr, the Scale-Arbitrary Super-Resolution model, has numerous use cases for a technical audience. One application could be in the field of medical imaging, where low-resolution scans can be improved to enhance diagnostic accuracy. Another possible use case is in surveillance systems, where arbsr could enhance the resolution of low-quality security footage for improved identification and tracking. Additionally, arbsr could be employed in satellite imaging, aiding in the analysis and understanding of high-resolution aerial images. In terms of practical uses, arbsr could be integrated into image editing software, allowing users to enhance the resolution of their photos without sacrificing quality. Furthermore, it could be incorporated into video conferencing platforms to improve the clarity of video streams, especially in low-bandwidth scenarios. Overall, arbsr's flexibility and versatility open up a wide range of possibilities for its integration into various products and applications.
- 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.
|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||$0.0055|
|Prediction Hardware||Nvidia T4 GPU|
|Average Completion Time||10 seconds|