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Now that face recognition has become a hot topic, major mobile phone manufacturers are quickly integrating this technology into their devices. But is face recognition really complicated? Actually, it's not. In fact, you can implement face recognition with just a single command. Let’s take a look at how it works!
**System Requirements**
- Ubuntu 17.10
- Python 2.7.14
**Environment Setup**
1. Install Ubuntu 17.10.
2. Python 2.7.14 comes pre-installed on Ubuntu 17.10.
3. Install Git, CMake, and Python-pip.
4. Install and compile dlib, which is a prerequisite for face_recognition.
5. Finally, install the face_recognition library using pip.
Once everything is set up, you can run the `face_recognition` command in the terminal to verify the installation.
**Face Recognition Examples**
**Example 1: One-Line Command for Face Recognition**
1. First, create a folder containing images of all the people you want the system to recognize. Each person should have one image, and the file names should match the person's name.
For example, you can place photos of Babe, Jackie Chan, and Joey Yung in a folder called `known_people`.
2. Then, prepare another folder with the image you want to identify. This image should contain unknown faces.
3. Run the `face_recognition` command with the two folders as parameters. The output will show the recognized faces.
This method allows the system to identify individuals in an image with just one simple command.
**Example 2: Recognize All Faces in an Image and Display Them**
You can also use the tool to detect and label all faces in a single image. For instance, if you input an image with multiple people, the program will identify each face and display them with their corresponding names.
**Example 3: Automatic Facial Feature Detection**
The face_recognition library can automatically detect facial features such as eyes, nose, mouth, and more. This makes it possible to analyze expressions, age, gender, and even emotions from a photo.
**Example 4: Identify Who Is in the Picture**
By running the appropriate command, the system can determine who is present in a given image. This is especially useful for applications like security systems or social media tagging.
**Example 5: Detecting Facial Features and Beauty**
Beyond basic identification, the tool can also analyze facial features and provide insights into beauty, symmetry, and other aesthetic traits. This opens up new possibilities for personalization and entertainment.
Whether you're building a security system, developing a smart app, or simply curious about AI, face recognition is now easier than ever to implement. With just a few commands, you can unlock powerful capabilities right from your terminal.