# Dlib_face_detection_from_camera

**Repository Path**: yangzl/Dlib_face_detection_from_camera

## Basic Information

- **Project Name**: Dlib_face_detection_from_camera
- **Description**: No description available
- **Primary Language**: Python
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2021-11-09
- **Last Updated**: 2021-11-09

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

Face detection with landmarks
#############################

Introduction
************

检测人脸, 并进行 5/68 特征点检测 / Detect faces from camera, and draw the 5/68 facial landmarks of faces;

#. Use "shape_predictor_5_face_landmarks.dat", which is trained on the dlib 5-point face landmark dataset with 7198 faces.
   and identify the corners of the eyes and bottom of the nose:

   .. image:: for_readme/5_landmarks.png
      :align: center


#. Use "shape_predictor_68_face_landmarks.dat", which is trained on the ibug 300-W
   dataset (https://ibug.doc.ic.ac.uk/resources/facial-point-annotations/)

   This model is designed to work well with dlib's HOG face detector
   and the CNN face detector.

   It won't work as well when used with a face detector that produces differently aligned boxes

   .. image:: for_readme/68_landmarks.png
      :align: center


* 先安装依赖环境 / Please install python packages: dlib and numpy at first:

.. code-block:: bash

   pip3 install -r requirements.txt

About Source Code
*****************

Python 源码介绍如下:

#. Use camera in Python / Python OpenCV 调用摄像头;

   .. code-block:: python

      python3 how_to_use_camera.py:

#. Show the 68 features points from local images / 显示本地图像文件中的人脸特征;

   .. code-block:: python

      python3 get_features_from_images.py:


#. Real-time facial landmarks detection and draw feature points /这一步将调用摄像头进行实时人脸检测和特征点绘制;

   .. code-block:: python

      python3 get_features_from_camera.py:


More
****

* Author:   coneypo
* Mail:     coneypo@foxmail.com
* Blog:     https://www.cnblogs.com/AdaminXie/p/8472743.html

Thanks for your support.