--- comments: true description: Object Counting in Different Region using Ultralytics YOLOv8 keywords: Ultralytics, YOLOv8, Object Detection, Object Counting, Object Tracking, Notebook, IPython Kernel, CLI, Python SDK --- # Object Counting in Different Regions using Ultralytics YOLOv8 🚀 ## What is Object Counting in Regions? Object counting in regions with [Ultralytics YOLOv8](https://github.com/ultralytics/ultralytics/) involves precisely determining the number of objects within specified areas using advanced computer vision. This approach is valuable for optimizing processes, enhancing security, and improving efficiency in various applications.



Watch: Ultralytics YOLOv8 Object Counting in Multiple & Movable Regions

## Advantages of Object Counting in Regions? - **Precision and Accuracy:** Object counting in regions with advanced computer vision ensures precise and accurate counts, minimizing errors often associated with manual counting. - **Efficiency Improvement:** Automated object counting enhances operational efficiency, providing real-time results and streamlining processes across different applications. - **Versatility and Application:** The versatility of object counting in regions makes it applicable across various domains, from manufacturing and surveillance to traffic monitoring, contributing to its widespread utility and effectiveness. ## Real World Applications | Retail | Market Streets | |:------------------------------------------------------------------------------------------------------------------------------------------------------------------:|:-----------------------------------------------------------------------------------------------------------------------------------------------------------------:| | ![People Counting in Different Region using Ultralytics YOLOv8](https://github.com/RizwanMunawar/ultralytics/assets/62513924/5ab3bbd7-fd12-4849-928e-5f294d6c3fcf) | ![Crowd Counting in Different Region using Ultralytics YOLOv8](https://github.com/RizwanMunawar/ultralytics/assets/62513924/e7c1aea7-474d-4d78-8d48-b50854ffe1ca) | | People Counting in Different Region using Ultralytics YOLOv8 | Crowd Counting in Different Region using Ultralytics YOLOv8 | ## Steps to Run ### Step 1: Install Required Libraries Begin by cloning the Ultralytics repository, installing dependencies, and navigating to the local directory using the provided commands in Step 2. ```bash # Clone Ultralytics repo git clone https://github.com/ultralytics/ultralytics # Navigate to the local directory cd ultralytics/examples/YOLOv8-Region-Counter ``` ### Step 2: Run Region Counting Using Ultralytics YOLOv8 Execute the following basic commands for inference. ???+ tip "Region is Movable" During video playback, you can interactively move the region within the video by clicking and dragging using the left mouse button. ```bash # Save results python yolov8_region_counter.py --source "path/to/video.mp4" --save-img # Run model on CPU python yolov8_region_counter.py --source "path/to/video.mp4" --device cpu # Change model file python yolov8_region_counter.py --source "path/to/video.mp4" --weights "path/to/model.pt" # Detect specific classes (e.g., first and third classes) python yolov8_region_counter.py --source "path/to/video.mp4" --classes 0 2 # View results without saving python yolov8_region_counter.py --source "path/to/video.mp4" --view-img ``` ### Optional Arguments | Name | Type | Default | Description | |----------------------|--------|--------------|--------------------------------------------| | `--source` | `str` | `None` | Path to video file, for webcam 0 | | `--line_thickness` | `int` | `2` | Bounding Box thickness | | `--save-img` | `bool` | `False` | Save the predicted video/image | | `--weights` | `str` | `yolov8n.pt` | Weights file path | | `--classes` | `list` | `None` | Detect specific classes i.e. --classes 0 2 | | `--region-thickness` | `int` | `2` | Region Box thickness | | `--track-thickness` | `int` | `2` | Tracking line thickness |