facebookresearch / facebookresearch/segment-anything
set_image/image embedding runtime
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- Jupyter Notebook
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Description
Hello, I was wondering what sort of run-times you guys are getting for the set_image function. I am using an RTX 2060 and running the vit_l model, averaging ~1.3s for just the image_set function and ~0.3s for the actual NN processing. These numbers seem to be resolution independent. I was curious to see if you guys are getting varying performance for different GPUs and vit_model/checkpoint used, please state both if possible.

Additionally, has anyone managed to lower the image_set time taken?
Contributor guide
Research direction
No file, test, or entry point is named. Start by reproducing the set_image/image_set timing with the vit_l model on the reported RTX 2060, then compare it with the reported neural-network processing time. Done would require identifying whether the overhead varies by GPU or checkpoint and documenting a supported improvement or explanation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook
- Domain
- computer-vision, machine-learning, performance
- Issue type
- Bug
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100