YOLOv8s的FLOPs值为10亿次,UAV-YOLOv8s为530亿次,提升了近一倍,计算资源消耗仍有优化空间。改进后的模型对于自行车等非常小的物体的检测精度仍然不高。
We introduce a sophisticated detection framework named UAV-YOLOv5, which amalgamates the strengths of Swin Transformer V2 and YOLOv5. Firstly, we introduce Focal-EIOU, a refinement of the K-means algorithm tailored to generate anchor boxes better suited for the current dataset, thereby improving ...
UAV:无人机 标注信息 边界框:每个目标在图像中的位置,用中心点坐标(x, y)以及宽度w和高度h表示。 类别ID:每个类别的唯一标识符,通常在YOLO格式中标注为整数。 标注格式示例:深色版本class_id x_center y_center width height其中,x_center, y_center, width, height都是相对于图像尺寸的归一化值,范围在0到...
Compared with YOLOv5, the mAP of UAV-YOLOv5 is improved by 8.5%, which verifies that it has high-precision long-range small-target UAV optoelectronic detection capability. 展开 关键词: Deep learning Small object detection YOLOv5 Swin transformer UAV detection ...
UAV target detection is widely used in commercial, civil and military fields. However, UAV aerial images have few small target pixels and a large number of small targets, so there are omissions and false detections in target detection. Based on the above problems, an advanced YOLOv8n aerial ...
To alleviate the above problems, we propose an object detection model based on UAV aerial photography scenarios, called UAV-YOLOv8, using YOLOv8 as the backbone network. This model not only improves the performance of target detection but also does so without too much resource consumption. The ...
The task of UAV-based maritime rescue object detection faces two significant challenges: accuracy and real-time performance. The YOLO series models, known for their streamlined and fast performance, offer promising solutions for this task. However, existing YOLO-based UAV maritime rescue object detecti...
Small object detection based on YOLOv8 in UAV perspective Unmanned aerial vehicle (UAV) image object detection is a challenging task, primarily due to various factors such as multi-scale objects, a high proportion... T Ning,W Wu,J Zhang - 《Pattern Analysis & Applications》 被引量: 0发表:...
Unmanned aerial vehicle (UAV) object detection plays a crucial role in civil, commercial, and military domains. However, the high proportion of small objects in UAV images and the limited platform resources lead to the low accuracy of most of the existin
bash深色版本 python val.py --data ./drone_dataset/data.yaml --weights runs/train/yolov8_drone_detection/weights/best.pt 使用模型进行检测 假设你已经训练好了模型,并且保存了权重文件(例如best.pt),你可以使用以下代码进行检测: python深色版本 import cv2 import torch from ultralytics import YOLO # 加...