女做受网站,wordpress 过滤词,源码免费下载,有哪些建设网站的人脸识别三部曲 首先看目录结构图像信息采集 采集图片.py模型训练 训练模型.py人脸识别 人脸识别.py效果 首先看目录结构 引用文121本 opencv
│ 采集图片.py
│ 训练模型.py
│ 人脸识别.py
│
└───trainer
│ │ trainer.yml
│
└───data
│ └──… 人脸识别三部曲 首先看目录结构图像信息采集 采集图片.py模型训练 训练模型.py人脸识别 人脸识别.py效果 首先看目录结构 引用文121本 opencv
│ 采集图片.py
│ 训练模型.py
│ 人脸识别.py
│
└───trainer
│ │ trainer.yml
│
└───data
│ └───00_Wang
│ │ 0_00001.jpg
│ │ 0_00002.jpg
│ │ ...
│
│ └───01_Liu
│ │ 1_00001.jpg
│ │ 1_00001.jpg
│ │ ...
│ 图像信息采集 采集图片.py 开始运行时输入待录入的人脸姓名。 按下s键后开始录入人脸图像录入两百张后结束程序。 import cv2
import shutil
import os
采集图片.py
path ./data/
file_num len(os.listdir(path))name input(input name:\n)
name_dir os.path.join(path,str(file_num).zfill(2) _name)
if os.path.exists(name_dir): # 存在则清空不存在则重建shutil.rmtree(name_dir)
os.makedirs(name_dir)cap cv2.VideoCapture(0, cv2.CAP_DSHOW)
face_detector cv2.CascadeClassifier(haarcascade_frontalface_alt2.xml)count 0while cap.isOpened():ret, frame cap.read()if ret is True:gray cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)faces face_detector.detectMultiScale(gray, 1.3, 5)for (x, y, w, h) in faces:cv2.rectangle(frame, (x, y), (x w, y w), (255, 0, 0))cv2.imshow(image, frame)k cv2.waitKey(1) 0xFF # 按键判断if (k ord(s)): # 保存count 1cv2.imwrite(name_dir / str(file_num) _ str(count).zfill(5) .jpg, gray)print(success to save str(file_num) _ str(count).zfill(5) .jpg)elif count 200:breakelif k ord( ): # 退出breakcap.release()
cv2.destroyAllWindows()模型训练 训练模型.py
import os
import cv2
import numpy as np
from PIL import Image训练模型.py
path ./data/
recognizer cv2.face.LBPHFaceRecognizer_create()
detector cv2.CascadeClassifier(haarcascade_frontalface_alt2.xml)def get_images_and_labels(path):image_paths []name_dirs [os.path.join(path, f) for f in os.listdir(path)]for i in range(0, len(name_dirs) ):print(name_dirs[{0}] : .format(i) , name_dirs[i])image_paths [os.path.join(name_dirs[i], f) for f in os.listdir(name_dirs[i])]face_samples []ids []for image_path in image_paths:img Image.open(image_path).convert(L)img_np np.array(img, uint8)if os.path.split(image_path)[-1].split(.)[-1] ! jpg:continueid int((os.path.split(image_path)[-1].split(.)[0])[0])faces detector.detectMultiScale(img_np)for (x, y, w, h) in faces:face_samples.append(img_np[y:y h, x:x w])ids.append(id)return face_samples, idsfaces, ids get_images_and_labels(path)
recognizer.train(faces, np.array(ids))
recognizer.save(trainer/trainer.yml)人脸识别 人脸识别.py
import cv2
import os
人脸识别.py
recognizer cv2.face.LBPHFaceRecognizer_create()
recognizer.read(trainer/trainer.yml)
face_cascade cv2.CascadeClassifier(haarcascade_frontalface_alt2.xml)
font cv2.FONT_HERSHEY_SIMPLEX
idnum 0cam cv2.VideoCapture(0, cv2.CAP_DSHOW)
cam.set(6, cv2.VideoWriter.fourcc(M, J, P, G))
minW 0.1 * cam.get(3)
minH 0.1 * cam.get(4)path ./data/
names []
for name in os.listdir(path):names.append(name.split(_)[1])print(names)while True:ret, img cam.read()gray cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)faces face_cascade.detectMultiScale(gray,scaleFactor1.2,minNeighbors5,minSize(int(minW), int(minH)))for (x, y, w, h) in faces:cv2.rectangle(img, (x, y), (x w, y h), (0, 255, 0), 2)idnum, confidence recognizer.predict(gray[y:y h, x:x w])if confidence 80:idum names[idnum-1]confidence {0}%.format(round(100 - confidence))else:idum unknownconfidence {0}%.format(round(100 - confidence))cv2.putText(img, str(idum), (x 5, y - 5), font, 1, (0, 0, 255), 1)cv2.putText(img, str(confidence), (x 5, y h - 5), font, 1, (0, 0, 0), 1)cv2.imshow(camera, img)k cv2.waitKey(1) 0xFF # 按键判断if k ord( ): # 退出breakcam.release()
cv2.destroyAllWindows()效果
