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train YOLOv9 on your dataset tutorial - run inference with a pre-trained COCO model - fine-tune model on custom dataset - evaluate the trained model - run inference with a fine-tuned model blogpost: ↓ read more

111,792 Aufrufe • vor 2 Jahren •via X (Twitter)

11 Kommentare

Profilbild von SkalskiP
SkalskiPvor 2 Jahren

I have also prepared a notebook with an end-to-end example. - notebook: - paper: - code:

Profilbild von SkalskiP
SkalskiPvor 2 Jahren

tutorial covers benchmarking the newly trained model and analyzing the results.

Profilbild von SkalskiP
SkalskiPvor 2 Jahren

and also demonstrates how to use the model for inference.

Profilbild von SkalskiP
SkalskiPvor 2 Jahren

I've also added the example to the notebooks repository; there, you will find tutorials not only about YOLOv9 but also about other SOTA models. notebooks repository:

Profilbild von Christoffer Bjelke
Christoffer Bjelkevor 2 Jahren

hahah when the referee fell, it looked more like a player to the model makes sense

Profilbild von SkalskiP
SkalskiPvor 2 Jahren

hahaha, if I see someone falling on the sidewalk and holding his leg, my first thought is, it is a football player

Profilbild von Aleksandr Kovalev
Aleksandr Kovalevvor 2 Jahren

So many yolo versions) Could you highlight the advantages of yolov9?)

Profilbild von SkalskiP
SkalskiPvor 2 Jahren

Apparently it is the fastest and the most accurate ;)

Profilbild von TechBlend
TechBlendvor 2 Jahren

Thanks for sharing mate. Really accurate.

Profilbild von Noah Christie
Noah Christievor 2 Jahren

Is this then tracking player movement on the field with any sort of accuracy?

Profilbild von SkalskiP
SkalskiPvor 2 Jahren

This demo not, but some time ago I build demo that did this

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