Object Detection using Raspberry pi and OpenCv
import numpy as np
import cv2
import io
import picamera
stream = io.BytesIO()
with picamera.PiCamera() as camera:
camera.resolution = (320, 240)
camera.capture(stream, format='jpeg')
buff = numpy.fromstring(stream.getvalue(), dtype=numpy.uint8)
img = cv2.imdecode(buff, 1)
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')
watch_cascade = cv2.CascadeClassifier('haarcascade_watch.xml')
while 1:
ret, img = cap.read()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
watches = watch_cascade.detectMultiScale(gray, 50, 50)
for (x,y,w,h) in watches:
cv2.rectangle(img,(x,y),(x+w,y+h),(255,255,0),2)
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 = eye_cascade.detectMultiScale(roi_gray)
for (ex,ey,ew,eh) in eyes:
cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
cv2.imshow('picture.jpg',img)
import numpy as np
import cv2
import io
import picamera
stream = io.BytesIO()
with picamera.PiCamera() as camera:
camera.resolution = (320, 240)
camera.capture(stream, format='jpeg')
buff = numpy.fromstring(stream.getvalue(), dtype=numpy.uint8)
img = cv2.imdecode(buff, 1)
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml')
watch_cascade = cv2.CascadeClassifier('haarcascade_watch.xml')
while 1:
ret, img = cap.read()
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.3, 5)
watches = watch_cascade.detectMultiScale(gray, 50, 50)
for (x,y,w,h) in watches:
cv2.rectangle(img,(x,y),(x+w,y+h),(255,255,0),2)
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 = eye_cascade.detectMultiScale(roi_gray)
for (ex,ey,ew,eh) in eyes:
cv2.rectangle(roi_color,(ex,ey),(ex+ew,ey+eh),(0,255,0),2)
cv2.imshow('picture.jpg',img)
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