라즈베리파이에서 OpenCV 정리_2

안녕하세요. 개알못입니다~

 

저번에 이어서 opencv 관련 내용입니다.

좀더 여유가 있을 때 내용르 보충하겠습니다 :)

 

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1. 실시간 데이터 수집

# 개알못

import cv2
import os

cam = cv2.VideoCapture(0)
cam.set(3, 640) # set video width
cam.set(4, 480) # set video height

face_detector = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')

face_id = input(" Write your registration number")
print(" Look at the camera and wait a minute")

count = 0

while(True):
    ret, img = cam.read()
    img = cv2.flip(img, -1)
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)

    faces = face_detector.detectMultiScale(gray, 1.3, 5)
    
    for (x,y,w,h) in faces:
    
        cv2.rectangle(img, (x,y), (x+w,y+h), (255,0,0), 2)     
        count += 1
        
        cv2.imwrite("dataset/User." + str(face_id) + '.' + str(count) + ".jpg", gray[y:y+h,x:x+w])
        cv2.imshow('image', img)
        
    k = cv2.waitKey(100) & 0xff # ESC 누르면 종료
    if k == 27:
        break
        
    elif count >= 30: # 원하는 횟수만큼 데이터가 저장 됨.
         break
         
cam.release()
cv2.destroyAllWindows()

 

2. 수집한 데이터를 학습하기

# 개알못

import cv2
import numpy as np
import os
from PIL import Image

path = 'dataset'
recognizer = cv2.face.LBPHFaceRecognizer_create()
detector = cv2.CascadeClassifier("haarcascade_frontalface_default.xml");

def getImagesAndLabels(path):

    imagePaths = [os.path.join(path,f) for f in os.listdir(path)]     
    faceSamples=[]
    ids = []
    
    for imagePath in imagePaths:
    
        PIL_img = Image.open(imagePath).convert('L')
        img_numpy = np.array(PIL_img,'uint8')
        id = int(os.path.split(imagePath)[-1].split(".")[1])
        faces = detector.detectMultiScale(img_numpy)
        
        for (x,y,w,h) in faces:
        
            faceSamples.append(img_numpy[y:y+h,x:x+w])
            ids.append(id)
            
    return faceSamples,ids

faces,ids = getImagesAndLabels(path)
recognizer.train(faces, np.array(ids))

recognizer.write('trainer/trainer.yml')

 

3.  학습한 파일에 일치하는지 인식하기

# 개알못

import cv2
import numpy as np
import os

recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read('trainer/trainer.yml')
cascadePath = "haarcascade_frontalface_default.xml"

faceCascade = cv2.CascadeClassifier(cascadePath);
font = cv2.FONT_HERSHEY_SIMPLEX

id = 0

names = ['None', 'changhwan']

cam = cv2.VideoCapture(0)
cam.set(3, 640) # set video widht
cam.set(4, 480) # set video height

minW = 0.1*cam.get(3)
minH = 0.1*cam.get(4)

while True:
    ret, img =cam.read()
    img = cv2.flip(img, -1) # 상하반전
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    
    faces = faceCascade.detectMultiScale( 
        gray,
        scaleFactor = 1.2,
        minNeighbors = 5,
        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)
        id, confidence = recognizer.predict(gray[y:y+h,x:x+w])

        if (confidence < 100):
            id = names[id]
            confidence = "  {0}%".format(round(100 - confidence))
            
        else:
            id = "unknown"
            confidence = "  {0}%".format(round(100 - confidence))
        
        cv2.putText(img, str(id), (x+5,y-5), font, 1, (255,255,255), 2)
        cv2.putText(img, str(confidence), (x+5,y+h-5), font, 1, (255,255,0), 1)  
    
    cv2.imshow('camera',img) 
    
    k = cv2.waitKey(10) & 0xff # ESC 누르면 종료
    if k == 27:
        break
        
cam.release()
cv2.destroyAllWindows()