Object Detection in 60 Seconds using Python and YOLOv5 #shorts

Introduction

Object detection has become increasingly accessible in recent years, and with the help of YOLOv5, you can get started in no time. This article will guide you through the process of performing object detection using a Python script in just 60 seconds.

Step-by-Step Instructions

Clone the YOLOv5 Repository
Start by cloning the YOLOv5 GitHub repository. Open your terminal and run the following command:
```
git clone https://github.com/ultralytics/yolov5.git
```
Navigate into the YOLOv5 Directory
Once you have cloned the repository, change your directory to the YOLOv5 folder:
```
cd yolov5
```
Run the Detection Script
Within this directory, you will find a Python file named detect.py. You can initiate object detection using this script by executing the following command in your terminal:
```
python detect.py --weights yolov5s.pt --source 0
```
Here, --weights refers to the pre-trained model weights, and --source 0 indicates that the source is your second webcam (0 is typically the first webcam, so adjust as needed).
View Live Object Detection
After executing the command, a window will pop up displaying live object detection. This pre-trained model can recognize a variety of objects without needing any additional training. If you prefer, you can also process a video file by specifying its path instead of using a webcam.
Additional Visualization
To visualize the detection results in image format, you can add the --view-img flag to your command. For instance:
```
python detect.py --weights yolov5s.pt --source video.mp4 --view-img
```
Conclusion
YOLOv5 makes it incredibly easy to start with object detection. It's an efficient tool capable of recognizing objects in real-time. For more detailed tutorials and advanced features, subscribe to my channel for longer YouTube tutorials on this subject.

Keywords

YOLOv5
Object Detection
Python
GitHub
Webcam
Pre-trained Model
Command Line
Video Processing

FAQ

Q: What is YOLOv5?
A: YOLOv5 is an open-source object detection algorithm that provides real-time detection capabilities and is easy to use with Python.

Q: How do I run object detection with YOLOv5?
A: You can run object detection by cloning the YOLOv5 repository, navigating to the directory, and executing the detect.py script with your desired input source.

Q: Can YOLOv5 work with video files?
A: Yes, YOLOv5 can process video files by specifying the file path instead of using a webcam.

Q: What kind of objects can YOLOv5 detect?
A: YOLOv5 comes pre-trained on a wide array of common objects, but you can also train it on your own dataset for custom detections.

Q: Is it necessary to train the model before using it?
A: No, YOLOv5 provides pre-trained models that can be used out of the box for detecting various objects without additional training.