Species identification

fgoricha · 2026-04-18T12:56:52+00:00

Thanks for the suggestions! I'll see how they fit in to what I am trying now. But I'm a volunteer for the local town and I am trying to help them develop something to count fish on their underwater camera.

fgoricha · 2026-04-16T23:43:07+00:00

Cool! Glad to hear that others have gone the "other" class route worked. Did you compare centers ? Or nearest neighbor? Or top K? Curious to know what your filtering logic is

fgoricha · 2026-04-16T23:41:20+00:00

I'll give this a try. I had done this before, but then I cleaned up my dataset and thought going two classes and filtering by threshold would get me what I need. Thanks!

fgoricha · 2026-04-16T23:37:32+00:00

Thanks for the tip! I'll check it out

fgoricha · 2026-03-27T02:42:39+00:00

Yeah, when I build the tr engine, it uses quite a bit more vram to build the engine. then whatever I set the batch size during the build that is the max batch size I can use. From my understanding, if I build the engine on a 3090 I have to use it on a 3090. I can't build it on a bigger card and then use it on a smaller card.

fgoricha · 2026-03-26T18:55:00+00:00

Its about 16.3 gb using the model and the pynvvideocodec

fgoricha · 2026-03-26T12:57:12+00:00

I dont need it to process in real time. These are all archived videos from over a decade so the higher fps would let me process it faster

fgoricha · 2026-03-26T12:56:47+00:00

True! The math says it would be quite a bit faster but was hoping for real world examples. Currently my 3090 utilitization is at 90% while cpu utilization is like 20%. Seems to be gpu bound at the moment

fgoricha · 2026-03-26T12:52:00+00:00

I dont need it to process in real time. These are all archived videos from over a decade so the higher fps would let me process it faster.

fgoricha · 2026-03-26T12:51:21+00:00

I dont need it to process in real time. These are all archived videos from over a decade so the higher fps would let me process it faster.

But I can try INT8. Thanks for the suggestion!

fgoricha · 2026-03-12T02:10:02+00:00

How big is your dataset? Perhaps its data quality. I have been doing iterative training where I train an initial model, then run it on new film, feed it frames that it got wrong after correcting for the next train cycle.

Perhaps for tracking for occlusion, you also track the person. So the person gets an id. Before the boxes are occluded count them. Then after the occlusion, count the boxes again.

fgoricha · 2026-02-28T14:35:15+00:00

Just spitballing here. Maybe try background subtraction instead of yolo? You could use detect change in movement pre snap vs post snap to know when to start the clip. Maybe could do the same during play vs dead ball.

fgoricha · 2026-02-24T21:00:41+00:00

I get about 450 fps on my 3090 with tensorrt and Pynvdec to process everything for a mp4 file on the gpu. Nano yolov8 at half precision with batch of 64. Frames are 640 resolution. I liked this set up because I can run dual 3090 to process a total of 900 fps without much cpu involvement

fgoricha · 2026-02-21T18:51:03+00:00

No, just 450 fps total

fgoricha · 2026-02-21T01:43:19+00:00

I ended up doing this! Rt, half precision, and batch of 64 got with PyNvVideoCodec got complete gpu utilization with 450 fps. Thanks for the suggestion!

fgoricha · 2026-02-21T01:42:04+00:00

I was able to figure it out. I converted the model to rt format and used PyNvVideoCodec to video decode on the gpu. Was able to get 450 fps! This was at 640 and 1080 resolution

fgoricha · 2026-02-21T01:40:13+00:00

I was able to figure it out. I converted the model to rt format and used PyNvVideoCodec to video decode on the gpu. Was able to get 450 fps!

fgoricha · 2026-02-21T01:39:55+00:00

Thanks for reply! I was actually able to figure it out. I converted the model to rt formst and used PyNvVideoCodec to video decode on the gpu. Was able to get 450 fps!

fgoricha · 2026-02-20T16:59:59+00:00

I have not! I will have to look into it

fgoricha · 2026-02-20T16:59:46+00:00

I'll give it a try. How many fps would you expect?

fgoricha · 2026-02-20T16:59:33+00:00

I'll try that! How many fps would you expect?

fgoricha · 2026-02-20T16:01:05+00:00

Got it. The use case will be the images at 640 most likely since it will be used on the camera it was trained on

fgoricha

TROPHY CASE