import sys
import numpy as np
from ldgp import calcgrad
from ldgp import hist
import easygui
def dist(x,y):
return np.sqrt(np.sum((x-y)**2))
path=easygui.fileopenbox("select the image")
image=cv2.imread(path,0)
image=cv2.resize(image,(240,240))
naming=np.load("database/naming.npy")
labels=np.load("database/labels.npy")
data=np.load("database/data.npy")
grad=calcgrad(image)
histogram=hist(grad)
a=[]
for i in xrange(len(data)):
a.append(dist(histogram,data[i]))
b=np.copy(a)
temp=np.copy(labels)
temp2=np.copy(labels)
a,temp=zip(*sorted(zip(a,temp)))
b,locations=zip(*sorted(zip(b,temp2)))
for i in xrange(10):
print "USAGE python client1.py <ip of server> <port of server>"
ip = sys.argv[1]
port = int(sys.argv[2])
ret = s.connect((ip, port))
#print ret
while True:
ret, frame = camera.read()
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
faces = face_cascade.detectMultiScale(gray, 2.5, 3)
for (x, y, w, h) in faces:
face = gray[y:y + h, x:x + w]
face = cv2.resize(face, (240, 240))
gradient = calcgrad(face)
#gradient=4*gradient
#gradient=np.array(gradient,dtype='uint8')
histogram = hist(gradient)
histogram = str(histogram)
print 'histogram', histogram
s.sendall(histogram)
print 'histogram sent'
name = s.recv(4096)
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 0), 3)
font = cv2.FONT_HERSHEY_SIMPLEX
#cv2.putText(frame,naming[labels[0]],(x,y), font, 0.5,(255,255,255),2,cv2.LINE_AA)
cv2.putText(frame, name, (x, y), font, 0.5, (255, 255, 255), 2,
cv2.LINE_AA)
print ""
cv2.imshow("original", frame)
k = cv2.waitKey(5) & 0xFF
if k == 27:
break
import os
import sys
import numpy as np
import cv2
from ldgp import calcgrad
from ldgp import hist
path = sys.argv[1]
naming = []
labels = []
locations = []
data = []
k = 0
for folders in os.listdir(path):
folder = path + '/' + folders
naming.append(folders)
for images in os.listdir(folder):
image = folder + '/' + images
print image
locations.append(image)
labels.append(k)
data.append(
hist(calcgrad(cv2.resize(cv2.imread(image, 0), (240, 240)))))
k += 1
os.chdir("database")
np.save("naming", np.array(naming))
np.save("labels", np.array(labels))
np.save("locations", np.array(locations))
np.save("data", np.array(data))
