# Known Object Detection (RT-DETR)

## Overview
Pipeline 1 leverages **RT-DETR (Real-Time Detection Transformer)** to deliver fast, highly accurate bounding box predictions for standard object categories.

```
Image Frame ──► RT-DETR Backbone ──► Known Class Bounding Boxes + Confidence
```

## Key Characteristics
- **Predictable Performance**: Extremely consistent bounding boxes and confidence scores.
- **Fixed Vocabulary**: Trained on COCO 80 categories (person, car, dog, bottle, chair, laptop, etc.).
- **Ideal for Real-Time Feeds**: Runs efficiently on both GPU and modern CPU setups.

## Code Example

```python
from object_intelligence import ObjectDetector
import cv2

detector = ObjectDetector()
detector.set_mode("known")

cap = cv2.VideoCapture(0)
while True:
    ret, frame = cap.read()
    if not ret: break
    annotated, detections = detector.detect_and_draw(frame)
    cv2.imshow("Known Objects", annotated)
    if cv2.waitKey(1) & 0xFF == ord('q'): break
cap.release()
```