Hello, everyone.
Now I am working on object detection from drone.
I want to detect the tank or armored vehicle from 250m, then the size of object is around 20px..
Then current model doesn’t identify object correctly.
How can I fix it?
Please help me
Thanks
There’s a lot to getting a model to detect objects. The most important factor is your dataset. This tutorial is still a great reference point, and I highly recommend reading thru it:
If the smallest an object would be in an image is 20 pixels (assuming that’s 20 x 20 pixels), it should be feasible to detect. It’s impossible to know for certain until collecting and annotating data to train the model.
Another component that’s critical for detection is the quality of the annotations. When objects are smaller and/or difficult to see, it can sometime lead to decreased quality of annotations, which will make it more difficult for the model to learn the objects to detect. You can try to use models like SAM2 or YOLO-World to help with creating quality annotations faster, but you should always check the output.
Where possible, you can also try to improve detection by updating the imaging system where you model will be used and where you’re sourcing data. Of course that means you have to have control of that system, which might not always be the case. When possible, requesting that images are captured that are closer to the object can help to improve detection, since the objects will have a larger overall area in the image. Understandably it’s not always feasible, but it’s just something to be aware of for this or future projects.