Sentinel_Ai

Sentinel AI Crime Model (YOLOv8 Medium)

This is a custom-trained YOLOv8 Medium model explicitly designed to detect real-time threats from surveillance cameras.

Model Description

The Sentinel AI model was trained on thousands of physical crime scene videos and acts as the vision engine for the Sentinel AI Pipeline. It is optimized to track background pedestrians while simultaneously isolating high-threat events like physical violence.

• Developer: Ayush Yele
• Framework: PyTorch & Ultralytics YOLOv8
• Architecture: YOLOv8 (Medium)
• Epochs Trained: 100

Classes

This model predicts 4 specific macro-classes for emergency dispatch scenarios:

• 0: fight (Physical altercations, assault)
• 1: weapon (Knives, handguns, blunt objects)
• 2: violence (Robbery, vandalism, rioting)
• 3: normal (Pedestrians, standing objects)

How to Use

You can plug this model directly into standard Ultralytics YOLO inference code:

from ultralytics import YOLO

# Load the custom trained model
model = YOLO("AyushYele/Sentinel_Ai")

# Run inference on an image
results = model("surveillance_feed.jpg")
results[0].show()