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. With just one line of command, you can implement face recognition. Let’s dive in and see 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, so no need to install separately.
3. Install necessary tools like git, cmake, and python-pip.
4. Compile and install dlib, which is a prerequisite for face_recognition.
5. Install the face_recognition library using pip.
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 image should be named after the person.
- For example, include photos of Babe, Jackie Chan, and Joey Yung in a folder called `known_people`.
2. Then, create another folder with the image you want to identify.
- In this case, an image of Han Hong is placed in the `unknown_pic` folder.
3. Run the face_recognition command with the two folders as parameters. The system will return the recognized faces.
- The result shows that the machine successfully identified Han Hong.
**Example 2: Recognize All Faces in an Image**
- Use the command to detect and display all faces in an image.
- The output shows that seven faces were detected and labeled correctly.
**Example 3: Automatic Facial Feature Detection**
- This example demonstrates automatic detection of facial features such as eyes, nose, mouth, and more.
- The results show accurate feature mapping on the input image.
**Example 4: Identify Who Is in the Picture**
- Run the command to identify specific individuals in a group photo.
- The output clearly labels each person in the image.
**Example 5: Detect and Analyze Facial Features**
- This example goes further by analyzing facial features and even assessing beauty.
- The results include detailed facial landmarks and a beauty score.
With these examples, you can see how easy it is to implement face recognition using just a few commands. Whether you're identifying people, detecting faces, or analyzing facial features, the face_recognition library makes it simple and powerful. Try it out and see how it can enhance your projects!
ZOOKE provides you with safe and reliable connector products, with 2.5 spacing products providing more possibilities for limited space and creating more value for the research and development and production of terminal products.
2.50 wire to board connectors,2.5 connectors,ZOOKE connectors
Zooke Connectors Co., Ltd. , https://www.zooke.com