You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
86 lines
5.1 KiB
86 lines
5.1 KiB
--- |
|
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](../guides/object-counting.md) 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. |
|
|
|
<p align="center"> |
|
<br> |
|
<iframe loading="lazy" width="720" height="405" src="https://www.youtube.com/embed/okItf1iHlV8" |
|
title="YouTube video player" frameborder="0" |
|
allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" |
|
allowfullscreen> |
|
</iframe> |
|
<br> |
|
<strong>Watch:</strong> Ultralytics YOLOv8 Object Counting in Multiple & Movable Regions |
|
</p> |
|
|
|
## 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 | 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 |
|
|
|