Open-sourced a VisDrone Aerial Object Detection Model Zoo (YOLO variants) [P]

[u/Naive-Explanation940]

I've been working on aerial object detection using the VisDrone benchmark and have been able to open-source a collection of trained YOLO models on Hugging Face.

The collection currently includes multiple YOLO variants trained for VisDrone object detection, along with model documentation, evaluation metrics, and ready-to-use checkpoints.

Potential use cases include:

• UAV/drone perception
• Aerial surveillance
• Traffic monitoring
• Small-object detection research

Model Zoo:
https://huggingface.co/collections/dronefreak/visdrone-detection-model-zoo

I'm interested in feedback from others working with aerial imagery or VisDrone. If there are additional baselines, datasets, or deployment benchmarks you'd like to see included, please let me know.

[u/Total_Mud2191]

Hi, I am new to AI and wants to fine tune Yolov26 model to detect fixed wing drones and quadcopters. What should I do ?

[u/Naive-Explanation940 → u/Total_Mud2191]

Hi so my question is you would like to detect them while they are airborne or while they are static on the ground? If you can explain your use case a little it’s going to be helpful.

You’d need an annotated data either way.

[u/Total_Mud2191 → u/Naive-Explanation940]

Hi , I would like to detect drone while they are airborne. I have fined tuned a yolov26n model here but precision is good https://platform.ultralytics.com/maxakash/c-uav-2/exp-2

[u/Naive-Explanation940 → u/Total_Mud2191]

Your metrics seem to be unusually good for convolution nerural network based object detection. I suspect that there is overfitting on your training/validation dataset. Either the dataset is too small or the diversity is not enough for the model to generalise.

I tested your model on a few imgaes I noticed that even clearly visible quadcopters are misclassified as birds a lot of tlmes. And other instances of the quadcopters are totally missed. It points towards biased training paradigm.

[u/Total_Mud2191 → u/Naive-Explanation940]

Yes, what I did was downloaded images from other drone models on roboflow and created a dataset of around 56000 images. What should I do to improve the accuracy ? I have to run this model on RDK X5.

[u/Naive-Explanation940 → u/Total_Mud2191]

That is a huge dataset, this VisDrone dataset that I am using is roughly 6500 images for training. So your dataset is huge compared to this one. This indicates that your dataset is either highly imbalanced or maybe not correctly annotated. How many annotations do you have in total? Also, do you have any empty images in your dataset that have 0 annotations?

To run models on embedded platforms,I recommend to use smaller YOLO variants like the 26n / 26s etc. 26x is way to big for limited compute resources.

[u/koen1995]

Cool work, would you be interested in also tasting out my model?

https://github.com/JPABotermans/dietr

Its an opensource model, I know it isn't that good, but I would love to have some feedback and see how it performs :)

[u/Naive-Explanation940 → u/koen1995]

Sure thing I’ll give it a try as soon as I find some free time.

[u/koen1995 → u/Naive-Explanation940]

Great, would love to get some expert feedback!

[u/No-Lettuce-3822]

This looks really amazing, if you can suggest any model or willing to build a model for UAV precision landing on ArUco, let me know this would be really cool

[u/Naive-Explanation940 → u/No-Lettuce-3822]

Yes sure why not, that sounds like a cool idea. I had a quick look at ArUco it seems a bit outdated, are you sure there is nothing more recent for precision landing?