Car Speed Detector using YOLOv8

A Python-based vehicle speed detection system that uses YOLOv8 object detection to track vehicles in a video, calculate their speed, and classify them as Passed or Failed based on a speed threshold.

---

Demo Output

• Draws a detection line on video.
• Tracks vehicles and calculates their speed using distance between frames.
• Classifies each vehicle as:
  • Passed (within speed limit)
  • Failed (over speed limit)
• Annotates video with:
  • Bounding boxes
  • Speed labels
  • Summary stats (Passed/Failed count)
• Saves cropped images of detected vehicles into:
  • passed/
  • failed/

---

Tech Stack

• Ultralytics YOLOv8
• OpenCV
• Python 3.8+

---

Project Structure

car_speed_detector/
│
├── input/                   # Input videos (e.g., cars.mp4)
│   └── cars.mp4
│
├── output/                  # Processed output video and results
│
├── passed/                 # Cropped images of vehicles within speed limit
├── failed/                 # Cropped images of vehicles over speed limit
│
├── yolov8n.pt              # Pre-trained YOLOv8 model
│
├── config.py               # Configuration settings
├── detector.py             # Core logic for detection and speed check
├── utils.py                # Utility functions (e.g., speed calculations)
└── main.py                 # Entry point for running the pipeline

---

How It Works

1. Loads the video and detects cars frame-by-frame.
2. Tracks each vehicle using YOLOv8 object tracking.
3. Computes pixel displacement between frames.
4. Converts it into speed (km/h) using:

speed = (pixel_distance / PIXELS_PER_METER) * FPS * 3.6

5. If speed > threshold → marked as "Failed", else "Passed".
6. Saves vehicle snapshot into passed/ or failed/ folders.

---

How to Run

1. Install Requirements

pip install ultralytics opencv-python

2. Place Input Video

Put your .mp4 file in the input/ directory (e.g., input/cars.mp4).

3. Run the Detector

python main.py

4. View Output

• Annotated video: output/output_speed_check.mp4
• Image snapshots: passed/, failed/

---

Configuration

Edit config.py to change:

• Speed limit (e.g., 30 or 40 km/h)
• Line position
• Distance calibration (PIXELS_PER_METER)

---

Limitations

• Assumes a fixed camera angle.
• Speed is estimated using pixel displacement — not GPS-accurate.
• Requires calibration (e.g., pixels per meter) to match real-world scale.

---

Credits

Built with:

• Ultralytics YOLOv8
• OpenCV

---