FastSAM has a wide range of potential use cases. In the field of autonomous driving, FastSAM could be used to accurately identify and segment objects such as other vehicles, pedestrians, and traffic signs, allowing self-driving cars to make informed decisions based on a detailed understanding of their surroundings. FastSAM's fast and accurate object segmentation capabilities could also be utilized in object recognition applications, enabling systems to quickly identify and classify objects in real-time. In the field of image editing, FastSAM could be used to efficiently segment objects of interest, allowing users to easily apply targeted edits or remove unwanted elements from photos. Additionally, FastSAM's ability to process high-resolution images in real-time makes it suitable for a range of practical applications, from medical imaging to video analysis. Overall, FastSAM's speed, accuracy, and versatility make it a valuable tool for a variety of industries 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.
Fast Segment Anything
|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||$0.00385|
|Prediction Hardware||Nvidia T4 GPU|
|Average Completion Time||7 seconds|