Due to that YOLOv10 adopts the different training strategy with others, e.g. YOLOv8, it may thus have different favorable confidence threshold to detect objects. Besides, different thresholds will have no impact on the inference latency of YOLOv10 because it does not rely on NMS. Therefore, we suggest that a smaller threshold can be freely set or tuned for YOLOv10 to detect smaller objects or objects in the distance. For example,

wget https://skalskip-yolo-arena.hf.space/file=/tmp/gradio/048ecf37df927d6d7ed5528076f4133147f797d2/people-walking.png
yolo export model=yolov10m.pt format=onnx opset=13 simplify half=True device=0
# Here, we could use a smaller threshold of 0.05 rather than the default threshold of 0.25 to detect smaller objects 
# or objects in the distance.
yolo predict model=yolov10m.onnx source=people-walking.png half conf=0.05

Thank you all! ❤️