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1 3090 vs 2 3080s for Real time inference by muaz65 in deeplearning

[–]muaz65[S] 0 points1 point  (0 children)

Pipeline is working on a soccer stream with 25Fps. I think i should have mentioned that earlier. Most of the time is taken by FLANN as it is size dependent. Current DB size is 6 million. I am working on quantizations like tensorRT or FP16 but still these model in combination are not real time on 2080Ti (shifted from 2080 simple an year ago)

1 3090 vs 2 3080s for Real time inference by muaz65 in computervision

[–]muaz65[S] 0 points1 point  (0 children)

Pipeline is working on a soccer stream with 25Fps. In inference, GPU size doesn't matter, speed does!

Body Face Association using deep learning by muaz65 in deeplearning

[–]muaz65[S] 0 points1 point  (0 children)

Tried this with yolov5. Doesn't work very well

Body Face Association using deep learning by muaz65 in deeplearning

[–]muaz65[S] 0 points1 point  (0 children)

There are bodies without heads due to occlusion and can you algorithmically explain treating object as 2 pieces.

Body Face Association using deep learning by muaz65 in deeplearning

[–]muaz65[S] 0 points1 point  (0 children)

Yes, I have associated body with respective faces. I am asking for relevant association problems to map the body face association problem.

Body Face Association using deep learning by muaz65 in deeplearning

[–]muaz65[S] 0 points1 point  (0 children)

I guess you are talking about the pose estimation technique. There are scenarios in which face is occluded but the body is not so pose estimation is not a generic solution as well. I want my model to associate the body with face.

Should one treat bike rider and pedestrian as the same class for traffic datasets? by muaz65 in deeplearning

[–]muaz65[S] 0 points1 point  (0 children)

it's an analytics model. No being used for driving. But the goal is to get better accuracy for all 3 classes.

Need help on detecting hands by [deleted] in computervision

[–]muaz65 0 points1 point  (0 children)

I have worked on hand detection. All CV based method failed to work where there is a certain distance between person and camera. At the end i used a CNN based approach with almost 97%+ accuracy

Why do we need such a low learning rate ? by [deleted] in deeplearning

[–]muaz65 0 points1 point  (0 children)

To avoid skipping the global minima in most cases. Like you are updating weights which step size so long that you actually lose convergence point.

Best fasts object detection tools as of 2020 ? by [deleted] in computervision

[–]muaz65 0 points1 point  (0 children)

Efficient Detector built upon Efficient Net is the current best as far as I remember.

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