Comments (3)
Hej, thanks for your interest. If you are looking for the point method used to sample points from the mask, it is implemented in the extract_kmedoid_points
function. If you are looking for the Video Object Segmentation (VOS) code where an initial GT mask is given and tracked throughout the video, then you can look into the documentation on running the VOS experiments or look directly into the VOS evaluation script. Have I understood your question correctly? Let me know if I can provide further help!
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extract_kmedoid_points only gives you the +ve points.
How to get the -ve points using the same algorithm ?
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Hi @ManuBN786, the function extract_kmedoid_points
also supports sampling negative points when given the inverted mask as input. For example, if the mask is a float tensor, then you invert it with 1 - mask
. For more context, check how we extract the negative points here. In our experiments, I've always used Mixed Sampling for selecting negative points.
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Related Issues (20)
- How to generate a mask file with a demo program HOT 1
- problem when installing requirements.txt HOT 1
- Disappearing tracked objects HOT 2
- Confused about the key to enter when running demo or test HOT 1
- AssertionError: No frames found in /content/sam-pt/data/demo_data/bees/
- HQ-SAM predictor issue HOT 2
- Model creation outside repo directory HOT 1
- Add feature points in real time HOT 2
- Tracking ability with a small number of frames HOT 1
- How to get evaluation results for DAVIS2016, YouTube2018 and MOSE? HOT 2
- Error in call to target 'sam_pt.point_tracker.pips.tracker.PipsPointTracker' HOT 2
- Error to load model when running the demo HOT 1
- Cab sam-pt automatically track? HOT 4
- Error running the Non-interactivte Demo HOT 1
- detectron2 fails installation HOT 1
- how much gpu and how much memory are required for training and testing? HOT 1
- Is there any Demo Notebook to test on One Image with Positive, negative and occluded points being passed HOT 1
- Fail to download UVO dense dataset HOT 1
- Different number of positive points
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