Python 基于 dlib 的实时人脸识别，可作为毕业设计.zip

# Face Recognition _You can also read a translated version of this file [in Chinese 简体中文版](https://github.com/ageitgey/face_recognition/blob/master/README_Simplified_Chinese.md) or [in Korean 한국어](https://github.com/ageitgey/face_recognition/blob/master/README_Korean.md) or [in Japanese 日本語](https://github.com/m-i-k-i/face_recognition/blob/master/README_Japanese.md)._ Recognize and manipulate faces from Python or from the command line with the world's simplest face recognition library. Built using [dlib](http://dlib.net/)'s state-of-the-art face recognition built with deep learning. The model has an accuracy of 99.38% on the [Labeled Faces in the Wild](http://vis-www.cs.umass.edu/lfw/) benchmark. This also provides a simple `face_recognition` command line tool that lets you do face recognition on a folder of images from the command line! [](https://pypi.python.org/pypi/face_recognition) [](https://github.com/ageitgey/face_recognition/actions?query=workflow%3ACI) [](http://face-recognition.readthedocs.io/en/latest/?badge=latest) ## Features #### Find faces in pictures Find all the faces that appear in a picture:  ```python import face_recognition image = face_recognition.load_image_file("your_file.jpg") face_locations = face_recognition.face_locations(image) ``` #### Find and manipulate facial features in pictures Get the locations and outlines of each person's eyes, nose, mouth and chin.  ```python import face_recognition image = face_recognition.load_image_file("your_file.jpg") face_landmarks_list = face_recognition.face_landmarks(image) ``` Finding facial features is super useful for lots of important stuff. But you can also use it for really stupid stuff like applying [digital make-up](https://github.com/ageitgey/face_recognition/blob/master/examples/digital_makeup.py) (think 'Meitu'):  #### Identify faces in pictures Recognize who appears in each photo.  ```python import face_recognition known_image = face_recognition.load_image_file("biden.jpg") unknown_image = face_recognition.load_image_file("unknown.jpg") biden_encoding = face_recognition.face_encodings(known_image)[0] unknown_encoding = face_recognition.face_encodings(unknown_image)[0] results = face_recognition.compare_faces([biden_encoding], unknown_encoding) ``` You can even use this library with other Python libraries to do real-time face recognition:  See [this example](https://github.com/ageitgey/face_recognition/blob/master/examples/facerec_from_webcam_faster.py) for the code. ## Online Demos User-contributed shared Jupyter notebook demo (not officially supported): [](https://beta.deepnote.org/launch?template=face_recognition) ## Installation ### Requirements * Python 3.3+ or Python 2.7 * macOS or Linux (Windows not officially supported, but might work) ### Installation Options: #### Installing on Mac or Linux First, make sure you have dlib already installed with Python bindings: * [How to install dlib from source on macOS or Ubuntu](https://gist.github.com/ageitgey/629d75c1baac34dfa5ca2a1928a7aeaf) Then, make sure you have cmake installed: ```brew install cmake``` Finally, install this module from pypi using `pip3` (or `pip2` for Python 2): ```bash pip3 install face_recognition ``` Alternatively, you can try this library with [Docker](https://www.docker.com/), see [this section](#deployment). If you are having trouble with installation, you can also try out a [pre-configured VM](https://medium.com/@ageitgey/try-deep-learning-in-python-now-with-a-fully-pre-configured-vm-1d97d4c3e9b). #### Installing on an Nvidia Jetson Nano board * [Jetson Nano installation instructions](https://medium.com/@ageitgey/build-a-hardware-based-face-recognition-system-for-150-with-the-nvidia-jetson-nano-and-python-a25cb8c891fd) * Please follow the instructions in the article carefully. There is current a bug in the CUDA libraries on the Jetson Nano that will cause this library to fail silently if you don't follow the instructions in the article to comment out a line in dlib and recompile it. #### Installing on Raspberry Pi 2+ * [Raspberry Pi 2+ installation instructions](https://gist.github.com/ageitgey/1ac8dbe8572f3f533df6269dab35df65) #### Installing on FreeBSD ```bash pkg install graphics/py-face_recognition ``` #### Installing on Windows While Windows isn't officially supported, helpful users have posted instructions on how to install this library: * [@masoudr's Windows 10 installation guide (dlib + face_recognition)](https://github.com/ageitgey/face_recognition/issues/175#issue-257710508) #### Installing a pre-configured Virtual Machine image * [Download the pre-configured VM image](https://medium.com/@ageitgey/try-deep-learning-in-python-now-with-a-fully-pre-configured-vm-1d97d4c3e9b) (for VMware Player or VirtualBox). ## Usage ### Command-Line Interface When you install `face_recognition`, you get two simple command-line programs: * `face_recognition` - Recognize faces in a photograph or folder full for photographs. * `face_detection` - Find faces in a photograph or folder full for photographs. #### `face_recognition` command line tool The `face_recognition` command lets you recognize faces in a photograph or folder full for photographs. First, you need to provide a folder with one picture of each person you already know. There should be one image file for each person with the files named according to who is in the picture:  Next, you need a second folder with the files you want to identify:  Then in you simply run the command `face_recognition`, passing in the folder of known people and the folder (or single image) with unknown people and it tells you who is in each image: ```bash $ face_recognition ./pictures_of_people_i_know/ ./unknown_pictures/ /unknown_pictures/unknown.jpg,Barack Obama /face_recognition_test/unknown_pictures/unknown.jpg,unknown_person ``` There's one line in the output for each face. The data is comma-separated with the filename and the name of the person found. An `unknown_person` is a face in the image that didn't match anyone in your folder of known people. #### `face_detection` command line tool The `face_detection` command lets you find the location (pixel coordinatates) of any faces in an image. Just run the command `face_detection`, passing in a folder of images to check (or a single image): ```bash $ face_detection ./folder_with_pictures/ examples/image1.jpg,65,215,169,112 examples/image2.jpg,62,394,211,244 examples/image2.jpg,95,941,244,792 ``` It prints one line for each face that was detected. The coordinates reported are the top, right, bottom and left coordinates of the face (in pixels). ##### Adjusting Tolerance / Sensitivity If you are getting multiple matches for the same person, it might be that the people in your photos look very similar and a lower tolerance value is needed