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vision.py
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vision.py
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#!/usr/bin/env python
import rospy
import math
import cv2
from PIL import Image
from imutils.object_detection import non_max_suppression
import numpy as np
import imutils
def isPerson(img):
par=0
hog = cv2.HOGDescriptor()
hog.setSVMDetector(cv2.HOGDescriptor_getDefaultPeopleDetector())
image = imutils.resize(img, width=min(400, img.shape[1]))
orig = img.copy()
(rects, weights) = hog.detectMultiScale(image, winStride=(4, 4),
padding=(8, 8), scale=1.05)
for (x, y, w, h) in rects:
cv2.rectangle(orig, (x, y), (x + w, y + h), (0, 0, 255), 2)
rects = np.array([[x, y, x + w, y + h] for (x, y, w, h) in rects])
pick = non_max_suppression(rects, probs=None, overlapThresh=0.65)
for (xA, yA, xB, yB) in pick:
par+=1
cv2.rectangle(image, (xA, yA), (xB, yB), (0, 255, 0), 2)
if(par==1):
x=False
return True
else:
return False
def isFace(img):
face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml')
gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 1.2, 5)
picList=[]
for (x,y,w,h) in faces:
xC=x
yC=y
width=w
height=h
a = np.zeros([width,height,3],dtype=np.uint8)
for i in range (0,width):
for j in range (0,height):
pic[x][y]=gray[i+xC][j+yC]
picList.append(pic)
if (xC==0):
return picList,False
else:
print "Face found..."
return picList,True