Create README.md

README.md

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+---
+license: mit
+tags:
+- computer-vision
+- object-detection
+- yolov8
+- security
+- real-time
+---
+
+# 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:
+
+```python
+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()