Home Intrusion Detection Project

           Home Intrusion Detection Project

Introduction 

YOLO11 is the latest iteration in the Ultralytics YOLO series of real-time object detectors, redefining what's possible with cutting-edge accuracy, speed, and efficiency. Building upon the impressive advancements of previous YOLO versions, YOLO11 introduces significant improvements in architecture and training methods, making it a versatile choice for a wide range of computer vision tasks.

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CODE 

YOLOv11

!pip install ultralytics

from ultralytics import YOLO

model = YOLO('yolo11s.pt')

!pip install roboflow

from roboflow import Roboflow

rf = Roboflow(api_key="")

project = rf.workspace("college-project-s1zbr").project("home-intrusion-detection")

version = project.version(2)

dataset = version.download("yolov11")

TRAIN

results = model.train(data="/content/Home-Intrusion-Detection-2/data.yaml",epochs=20,imgsz=640)

DETECT

results = model.val()

!yolo task=detect mode=predict model=/content/runs/detect/train/weights/best.pt conf=0.2 source=/content/Home-Intrusion-Detection-2/test/images/IMG_20240418_150308_926_jpg.rf.c51d83e5e441ac39531ba13c00a1f15b.jpg save=True

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