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Now that face recognition has become a hot topic, major smartphone manufacturers are also rushing to integrate this technology into their devices. But is face recognition really complicated? Actually, it's not. In fact, you can implement face recognition with just one simple command. Let’s explore how!
**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, so no need to install separately.
3. Install essential tools like git, cmake, and python-pip.
4. Install and compile dlib — this is a crucial step before installing face_recognition.
5. Finally, install the face_recognition library.
Once everything is set up, open your terminal and run the `face_recognition` command to verify the installation.
**Face Recognition Examples**
**Example 1: One-Line Command for Face Recognition**
1. First, prepare 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, include images of Babe, Jackie Chan, and Joey Yung in the `known_people` folder.
2. Next, create another folder containing the image you want to analyze. This image should include unknown faces.
- For instance, the `unknown_pic` folder might contain an image of Han Hong, who is not yet recognized by the system.
3. Run the face_recognition command with the two folders as parameters. The output will show the recognized faces.
**Example 2: Recognize All Faces in an Image**
Use the same command to detect and display all faces in a given image. The system can identify multiple individuals in a single photo and label them accordingly.
**Example 3: Automatic Facial Feature Detection**
This feature automatically detects facial landmarks such as eyes, nose, mouth, and more. It provides detailed information about the structure of a face.
**Example 4: Identify Who Is in the Picture**
The system can determine who is present in a given image and provide accurate identification results.
**Example 5: Detect and Analyze Facial Features**
Beyond just identifying faces, the system can also analyze facial features, such as symmetry, age, gender, and even beauty scores.
With these examples, you can see how powerful and easy-to-use face recognition can be. Whether you're building a security system, a personal project, or exploring AI capabilities, face recognition offers a wide range of applications. Try it out today and experience the magic of modern AI!