라즈베리파이에서 OpenCV 정리_1

안녕하세요. 개알못입니다~

 

좀더 여유 있을 때 자세한 설명으로 돌아오겠습니다...!!

 

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1. 라즈베리파이에서 카메라 촬영하기

# 'test_1'는 파일명

raspistill -o test_1.jpg

 

2. opencv 설치 확인하기

pkg-config --modversion opencv

 

3. opencv로 카메라 이용하기 (상하반전, 색 변경)

# 개알못

import numpy as np
import cv2

cap = cv2.VideoCapture(0)
cap.set(3,640) # set Width
cap.set(4,480) # set Height

while(True):
    ret, frame = cap.read()
    frame = cv2.flip(frame, -1) # 상하 반전
#   gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)	# gray color
    
    cv2.imshow('frame', frame)	# 'frame' 이름
#   cv2.imshow('gray', gray)	# gray color
    
    k = cv2.waitKey(30) & 0xff
    if k == 27: # ESC 누르면 종료
        break
        
cap.release()
cv2.destroyAllWindows()

 

4. Haar feature로 얼굴 인식하기

# 개알못

import numpy as np
import cv2

cap = cv2.VideoCapture(0)
cap.set(3,640) # set Width
cap.set(4,480) # set Height

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

while True:
    ret, img = cap.read()
    img = cv2.flip(img, -1) # 상하반전
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    
    faces = faceCascade.detectMultiScale(
        gray,
        scaleFactor=1.2,
        minNeighbors=5,
        minSize=(20, 20)
    )
    
    for (x,y,w,h) in faces:
    
        cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
        roi_gray = gray[y:y+h, x:x+w]
        roi_color = img[y:y+h, x:x+w]
        
    cv2.imshow('video',img) # 'video' 이름
    
    k = cv2.waitKey(30) & 0xff
    if k == 27: # ESC 누르면 종료
        break
        
cap.release()
cv2.destroyAllWindows()

 

5. Haar feature로 얼굴 and 눈 인식하기

# 개알못

import numpy as np
import cv2

cap = cv2.VideoCapture(0)
cap.set(3,640) # set Width
cap.set(4,480) # set Height

faceCascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
eyeCascade = cv2.CascadeClassifier('haarcascade_eye.xml')

while True:
    ret, img = cap.read()
    img = cv2.flip(img, -1) # 상하반전
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    
    faces = faceCascade.detectMultiScale(
        gray,
        scaleFactor=1.2,
        minNeighbors=5,
        minSize=(20, 20)
	)

    for (x,y,w,h) in faces:
    
        cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
        roi_gray = gray[y:y+h, x:x+w]
        roi_color = img[y:y+h, x:x+w]

        eyes = eyeCascade.detectMultiScale(
            roi_gray,
            scaleFactor= 1.5,
            minNeighbors=10,
            minSize=(5, 5),
        )
        
       for (ex, ey, ew, eh) in eyes:
       
           cv2.rectangle(roi_color, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 2)
                
    cv2.imshow('video',img) 
    
    k = cv2.waitKey(30) & 0xff
    if k == 27: # ESC 누르면 종료
        break
        
cap.release()
cv2.destroyAllWindows()

 

6. Haar feature로 얼굴 and 미소 인식하기

# 개알못

import numpy as np
import cv2

cap = cv2.VideoCapture(0)
cap.set(3,640) # set Width
cap.set(4,480) # set Height

faceCascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
smileCascade = cv2.CascadeClassifier('haarcascade_smile.xml')

while True:
    ret, img = cap.read()
    img = cv2.flip(img, -1) # 상하반전
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    
    faces = faceCascade.detectMultiScale(
        gray,
        scaleFactor=1.2,
        minNeighbors=5,
        minSize=(20, 20)
	)

    for (x,y,w,h) in faces:
    
        cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
        roi_gray = gray[y:y+h, x:x+w]
        roi_color = img[y:y+h, x:x+w]

		smile = smileCascade.detectMultiScale(
            roi_gray,
            scaleFactor = 1.5,
            minNeighbors = 15,
            minSize = (25, 25),
            )
        
       for (xx, yy, ww, hh) in smile:
       
           cv2.rectangle(roi_color, (xx, yy), (xx + ww, yy + hh), (0, 255, 0), 2)
                
    cv2.imshow('video',img) 
    
    k = cv2.waitKey(30) & 0xff
    if k == 27: # ESC 누르면 종료
        break
        
cap.release()
cv2.destroyAllWindows()

 

7. Haar feature로 얼굴 and 눈 and 미소 인식하기

# 개알못

import numpy as np
import cv2

cap = cv2.VideoCapture(0)
cap.set(3,640) # set Width
cap.set(4,480) # set Height

faceCascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
eyeCascade = cv2.CascadeClassifier('haarcascade_eye.xml')
smileCascade = cv2.CascadeClassifier('haarcascade_smile.xml')

while True:
    ret, img = cap.read()
    img = cv2.flip(img, -1) # 상하반전
    gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
    
    faces = faceCascade.detectMultiScale(
        gray,
        scaleFactor=1.2,
        minNeighbors=5,
        minSize=(20, 20)
    )

    for (x,y,w,h) in faces:
    
        cv2.rectangle(img,(x,y),(x+w,y+h),(255,0,0),2)
        roi_gray = gray[y:y+h, x:x+w]
        roi_color = img[y:y+h, x:x+w]
        
        eyes = eyeCascade.detectMultiScale(
            roi_gray,
            scaleFactor= 1.5,
            minNeighbors=10,
            minSize=(5, 5),
        )

        for (ex, ey, ew, eh) in eyes:
       
            cv2.rectangle(roi_color, (ex, ey), (ex + ew, ey + eh), (0, 255, 0), 2)
              
        smile = smileCascade.detectMultiScale(
            roi_gray,
            scaleFactor = 1.5,
            minNeighbors = 15,
            minSize = (25, 25),
            )
        
        for (xx, yy, ww, hh) in smile:
       
           cv2.rectangle(roi_color, (xx, yy), (xx + ww, yy + hh), (0, 255, 0), 2)
                
    cv2.imshow('video',img) 
    
    k = cv2.waitKey(30) & 0xff
    if k == 27: # ESC 누르면 종료
        break
        
cap.release()
cv2.destroyAllWindows()