face_recognitionface_recognition 是github上一个非常有名气的人脸识别开源工具包，我们可以通过以下指令安装到python环境内$ pip
代码import numpy as npimport cv2def cv_display(name,img): cv2.imshow(name,im
第一部下载对应源码： https://github.com/tensorflow/models建立工程目录复制mo
所需模块安装pip3 install python-opencvpip3 install dlibpip3 install imutils dlib面部关键点信息图我们实现的是嘴巴识别，
# -*- coding:utf-8 -*-import numpy as npimport argparseimport cv2points=[]opencv
github.com/tzutalin/labelImg安装对应模块，调试环境即可利用标注工具制作自己的数据集，并生成xml文件生成csv# -*- coding:utf-8 -*-import osimport globimport pandas as pdimport xml.etree.ElementTree as ETimport randomdef x
均值哈希算法# -*- coding: utf-8 -*-import cv2import numpy as np# Hash值对比def cmpHash(hash1, hash2,shape=(10,10))
参考：https://google.github.io/mediapipe/solutions/hands函数式import cv2import m
图像直方图def img_dislay(img): hist = cv2.calcHist([img],[0],None,[256],[0,256]) plt.hist(i
低通滤波# -*- coding:utf-8 -*-import numpy as npimport cv2from matplotlib import
i
# -*- coding:utf-8 -*-import cv2import numpy as npdef vid
# -*- coding:utf-8 -*-import cv2import numpy as npdef video_operate(): capture = c
# -*- coding=utf-8 -*-import numpy as np import cv2import dlibfrom scipy.spatial import dis
图像轮廓import cv2 as cvimport numpy as npimport matplotl
图片组成[[[245 227 220][245 226 219][245 227 220]…[ 82 123 78][ 83 125 78][ 88 1
调用SSD模型# -*- coding: utf-8 -*-from tensorflow.python.keras.preprocessing.imag
import randomfrom sklearn import datasetsimport numpy as npimport matplotlib.pyplot as pltfrom mpl_toolkits.mplot3d import
#-*- coding: UTF-8 -*- import cv2import numpy as np from matplotlib
Sobel算子def sobel_(src): sobel_x = cv2.Sobel(src,cv2.CV_64F,1,0,ksize=3) sobel_y = cv2.Sobel(src,cv2.CV_64F,0,1,
# -*- coding: utf-8 -*-import cv2 as cvimport numpy as npdef display_img(img): cv.imshow('image',img) cv.waitKey(0)
import cv2 as cvimport matplotlib.pyplot as pltthresh_type = [ cv.THRESH_BINARY, cv.THRESH_BINARY_INV, cv.THRESH_TRUNC,
图片对比import cv2 as cvimport numpy as npdef display_img(img): cv.imshow('image',img) cv.
import cv2 as cvimport numpy as npimport matplotlib.pyplot as pltdef display_img(label,img): cv.imshow(label,img) c
import cv2 as cvimport numpy as npimport matplotlib.pyplot as pltdef display_img(img): cv.imshow('image',img) cv.waitKey(0
模板单个匹配def all_operate(file1="lena.jpg",file2="face.jpg"): img = cv.imread(file1,0) template = cv.imread(file2,
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