Accuracy
97%
Throughput
12 FPS
Dataset
3000 samples
System ArchitectureINTERACTIVE_DIAGRAM
Summary
YOLOv8 model trained on 3000 samples, deployed on ROSMaster X3 at 97% accuracy and 12 FPS. Integrated ROS inference and visualization nodes for real-time robotic decision-making in precision agriculture.
weed_detector.pyfingerprint
def detect(self, frame):
results = model.predict(
frame, conf=0.5
)
for box in results.boxes:
cls = box.cls.item()
if cls == WEED_ID:
self.flag(box.xyxy)videocamProject Demo
2 CLIPSField Run
Detection Pipeline