def recognizeFace(photo_url): from face_client import FaceClient client = FaceClient(settings.FACES_API,settings.FACES_SECRET) try: photo = client.faces_detect(photo_url)['photos'][0] except: return False if len(photo['tags']) > 0: return getFace(photo) else: return False
def __init__(self, api_key, api_secret):
"""
Python wrapper for the Skybiometry API
:param api_key: The authorization key of the Skybiometry API
:param api_secret: The secret of the Skybiometry API
"""
self._face_client = FaceClient(api_key, api_secret)
def emo_proc(data, coll_name):
coll_name += '_emo'
client = FaceClient('3662cdd27df1426c9d3634cbc47342d5', '8606203f879b4d9e956e691fae0ac6d3')
i = 0
k = 0
for each in data:
try:
result = client.faces_detect(each.img_url)
except Exception as err:
if str(err).find("202") != -1:
print "limit err"
if k==0:
time.sleep(3600)
k = 1
else:
time.sleep(60)
k = 0
else:
write_to_db(coll_name, result)
def recognize_photo(request_id):
"""
This task execute the recognizer function
"""
request = RequestRecognizer.objects.get(id=request_id)
request.imagenByteArray = request.image_to_binary
request.save()
# Create one instance of library for connect to webservice
client = FaceClient(
'245c8bb50b2f42228a6a998863f5a1e0',
'c1800f96cf0647fb8412ae8d3dae1202',
)
# Call function web service
result = client.faces_recognize(
'all',
file=request.image,
aggressive=True,
namespace='CompareFaces',
)
# Validate if there are results
if result['photos'][0]['tags']:
recognize = None
level_recognize = ''
for item in result['photos'][0]['tags'][0]['uids']: # If exists coincidences
if item['confidence'] >= 80:
level_recognize = LEVEL_RECOGNIZE_HIGH
elif item['confidence'] >= 60 and item['confidence'] < 80:
level_recognize = LEVEL_RECOGNIZE_MEDIUM
if not recognize and item['confidence'] < 60:
request.access = False
request.status = DEACTIVE_STATUS
if not recognize or (recognize and item['confidence'] > recognize['confidence']):
recognize = item
recognize['uid'] = recognize['uid'].split('@')[0]
recognize['level'] = level_recognize
request.result_recognizer = recognize
request.save()
def training(request):
if not request.user.is_superuser:
return HttpResponseForbidden('Only for Superuser')
if request.method == 'POST':
f = request.POST
form = ImageUploadForm(request.POST, request.FILES)
if form.is_valid():
if not Senior.objects.filter(student_id=f['student_id']):
senior = Senior.objects.create(
name=f['name'],
image=form.cleaned_data['image'],
student_id=f['student_id']
)
senior.save()
else:
senior = Senior.objects.get(student_id=f['student_id'])
senior.image = form.cleaned_data['image']
senior.save()
image_url = 'http://150.95.135.222:8000' + senior.image.url
client = FaceClient('ac38c745411845ce89698e1e2469df79', '9d70c1da17fd49609327c8ca154061f1')
response = client.faces_detect(image_url)
tid = response['photos'][0]['tags'][0]['tid']
client.tags_save(tids=tid, uid=f['student_id']+'@senior', label=f['student_id'])
result = client.faces_train(f['student_id']+'@senior')
return render(request, 'software/training.html', {'result': result})
else:
return HttpResponseForbidden('form is invalid')
else:
return render(request, 'software/training.html', {})
def recognizeFace(theImg,filenameFull):
font = ImageFont.truetype("/usr/share/fonts/truetype/ttf-dejavu/DejaVuSans-Bold.ttf", 14)
theFileLocation = "http://" + config.publicIP + "/temp.jpg"
client = FaceClient(keyring.get_password('skybio','api_key'),keyring.get_password('skybio','api_secret'))
img = Image.open(theImg)
width, height = img.size
draw = ImageDraw.Draw(img)
print theFileLocation
photo = client.faces_recognize('all',theFileLocation, namespace = 'python')
print photo
# Number of people in photo
numFaces = len(photo['photos'][0]['tags'])
print "Detected " + str(numFaces) + " faces."
textCaption = ""
iii=0
theSpeech = ""
while iii<numFaces:
for person in config.personList:
# for j, person in enumerate(personList):
try:
theId = photo['photos'][0]['tags'][iii]['uids'][0]['uid']
foundName = theId
print "I see " + foundName
xPos = width*(int(photo['photos'][0]['tags'][iii]['eye_right']['x']))/100
yPos = height*(int(photo['photos'][0]['tags'][iii]['eye_right']['y']))/100
if person.name in foundName: #and photo['photos'][0]['tags'][iii]['attributes']['gender']['value'] == person.gender:
theSpeech = theSpeech + "%s" % person.greeting
timeDifference = datetime.datetime.now() - person.lastSeen
person.lastSeen = datetime.datetime.now()
#personList[j].lastSeen = person.lastSeen
days = math.floor(timeDifference.total_seconds() / 60 / 60 / 24)
hours = math.floor(timeDifference.total_seconds() / 60 / 60 )
minutes = math.floor(timeDifference.total_seconds() / 60 )
if days > 0:
theSpeech = theSpeech + "It's been %d days since I have seen you, %s. " % (days,person.name)
elif hours > 4:
theSpeech = theSpeech + "It's been %d hours since I have seen you, %s. " % (hours,person.name)
elif minutes > 0:
theSpeech = theSpeech + "It's been %d minutes since I have seen you, %s. " % (minutes,person.name)
draw.text((xPos, yPos),person.name,(255,255,0),font=font)
draw.text((0, 0),time.strftime("%c"),(255,255,0),font=font)
collection = ['eyes','sadness','mood','glasses']
for x in collection:
try:
eyes = photo['photos'][0]['tags'][iii]['attributes'][x]['value']
conf = photo['photos'][0]['tags'][iii]['attributes'][x]['confidence']
if conf > 20:
print " " + x + " = " + eyes
yPos = yPos + 20
draw.text((xPos, yPos)," " + x + ": " + eyes,(255,255,0),font=font)
if x == 'mood':
theSpeech = theSpeech + "Why are you " + eyes + "? "
except:
print "No " + x
except:
print "Error locating face in person database."
print "Unexpected error:", sys.exc_info()[0]
raise
iii = iii + 1
if len(theSpeech)>2: # proxy for if something happened
img.save(filenameFull)
img.save("/var/www/face.jpg")
pickle.dump(config.personList, open("ai_data/personlist.p","wb") )
return theSpeech
from std_srvs.srv import Empty
import numpy as np
import cv2
import os
from datetime import datetime
import dlib
import openface
from face_client import FaceClient
from timeout import Timeout
# For attributes
face_client = FaceClient('69efefc20c7f42d8af1f2646ce6742ec',
'5fab420ca6cf4ff28e7780efcffadb6c')
def _external_request_with_timeout(buffers):
timeout_duration = 60
rospy.loginfo("Trying external API request for %d seconds",
timeout_duration)
timeout_function = Timeout(face_client.faces_recognize, timeout_duration)
return timeout_function(buffers)
def _set_label(img, label, origin):
font = cv2.FONT_HERSHEY_SIMPLEX
scale = 0.4
thickness = 1
# Copyright (c) 2010, 2011, Tomaž Muraus
# All rights reserved.
from face_client import FaceClient
import json
import csv
import time
client = FaceClient('88c2f662703642d99d67bce4400bbebf', 'd5d89a3b8a8c42dfafb94a19728a183d')
# print response['photos'][0]['tags'][0]['attributes']['gender']['value']
# print response['photos'][0]['tags'][0]['attributes']['gender']['confidence']
url_list =[]
with open('final_male.txt','r') as f:
for line in f.readlines():
url_list.append(line.strip('\n'))
if __name__ == '__main__':
csv_file = open('sky_male.csv','ab')
writer = csv.writer(csv_file)
writer.writerow(["ID","URL","GENDER","CONFIDENCE"])
total_count = 1
for url in url_list:
try:
response = client.faces_detect(url)
# print response
if response['photos'][0]['tags'] == []:
import argparse
import vision
import track
parser = argparse.ArgumentParser()
parser.add_argument("-c",
"--conf",
default="./conf.json",
help="path to JSON config file")
args = vars(parser.parse_args())
conf = json.load(open(args["conf"]))
API_KEY = 'egk0ko9neatt4ftsgmhsmklf2r'
API_SECRET = '67doedp6s4dcnm5kmuhkgetj8p'
client = FaceClient(API_KEY, API_SECRET)
metrics = ['mood', 'smiling']
domain_name = 'sherrywangspi.ddns.net'
filename = "/var/www/html/temp.jpg"
img_addr = 'http://{}/temp.jpg'.format(domain_name)
ref_frame = cv2.imread(conf['ref_img'])
KNOWN_PIXEL_WIDTH = track.calculate_pixel_width(ref_frame)
camera = picamera.PiCamera()
camera.resolution = conf['resolution']
camera.framerate = conf['frame_rate']
rawCapture = PiRGBArray(camera, size=conf['resolution'])
time.sleep(conf["camera_warmup_time"])
def recognizeFace(theImg, filenameFull):
font = ImageFont.truetype(
"/usr/share/fonts/truetype/ttf-dejavu/DejaVuSans-Bold.ttf", 14)
theFileLocation = "http://" + config.publicIP + "/temp.jpg"
client = FaceClient(keyring.get_password('skybio', 'api_key'),
keyring.get_password('skybio', 'api_secret'))
img = Image.open(theImg)
width, height = img.size
draw = ImageDraw.Draw(img)
print theFileLocation
photo = client.faces_recognize('all', theFileLocation, namespace='python')
print photo
# Number of people in photo
numFaces = len(photo['photos'][0]['tags'])
print "Detected " + str(numFaces) + " faces."
textCaption = ""
iii = 0
theSpeech = ""
while iii < numFaces:
for person in config.personList:
# for j, person in enumerate(personList):
try:
theId = photo['photos'][0]['tags'][iii]['uids'][0]['uid']
foundName = theId
print "I see " + foundName
xPos = width * (int(
photo['photos'][0]['tags'][iii]['eye_right']['x'])) / 100
yPos = height * (int(
photo['photos'][0]['tags'][iii]['eye_right']['y'])) / 100
if person.name in foundName: #and photo['photos'][0]['tags'][iii]['attributes']['gender']['value'] == person.gender:
theSpeech = theSpeech + "%s" % person.greeting
timeDifference = datetime.datetime.now() - person.lastSeen
person.lastSeen = datetime.datetime.now()
#personList[j].lastSeen = person.lastSeen
days = math.floor(timeDifference.total_seconds() / 60 /
60 / 24)
hours = math.floor(timeDifference.total_seconds() / 60 /
60)
minutes = math.floor(timeDifference.total_seconds() / 60)
if days > 0:
theSpeech = theSpeech + "It's been %d days since I have seen you, %s. " % (
days, person.name)
elif hours > 4:
theSpeech = theSpeech + "It's been %d hours since I have seen you, %s. " % (
hours, person.name)
elif minutes > 0:
theSpeech = theSpeech + "It's been %d minutes since I have seen you, %s. " % (
minutes, person.name)
draw.text((xPos, yPos),
person.name, (255, 255, 0),
font=font)
draw.text((0, 0),
time.strftime("%c"), (255, 255, 0),
font=font)
collection = ['eyes', 'sadness', 'mood', 'glasses']
for x in collection:
try:
eyes = photo['photos'][0]['tags'][iii][
'attributes'][x]['value']
conf = photo['photos'][0]['tags'][iii][
'attributes'][x]['confidence']
if conf > 20:
print " " + x + " = " + eyes
yPos = yPos + 20
draw.text((xPos, yPos),
" " + x + ": " + eyes, (255, 255, 0),
font=font)
if x == 'mood':
theSpeech = theSpeech + "Why are you " + eyes + "? "
except:
print "No " + x
except:
print "Error locating face in person database."
print "Unexpected error:", sys.exc_info()[0]
raise
iii = iii + 1
if len(theSpeech) > 2: # proxy for if something happened
img.save(filenameFull)
img.save("/var/www/face.jpg")
pickle.dump(config.personList, open("ai_data/personlist.p", "wb"))
return theSpeech
#upload pictures from dir one at a time
for file in captureList:
#debug later had to hard code this one for some unknown EOL string error
filename = "C:/facerecog/images/" +file
response = auth.InsertPhotoSimple(album_url, file, 'FaceRecog', filename, content_type='image/jpeg')
uploadCount = uploadCount + 1
#Writing to file instead of passing directly into memory not using buffer
with open('picasa_response.xml', 'a') as debugUpload:
debugUpload.write(str(response))
#Looking for direct URL images of the detected faces
'''
Using regex string searching instead because ElementTree
child element attribute does not contain end tag needed for easy parsing
of direct URL image of face to utilize in face training API
'''
xmlFile = open('picasa_response.xml', 'r')
urls = re.findall('ns0:content src="https://\w+.googleusercontent.com/\S+', xmlFile.read())
scrubURLa = re.sub('ns0:content src="', '', str(urls))
scrubURLb = re.sub("[\[|\]|\"|\']", '', str(scrubURLa))
scrubURLc = re.sub(", ", ',', str(scrubURLb))
faceCompareURL = scrubURLc
#SkyBiometry API Client Object and Auth
client = FaceClient(skyBiometryAPI_ID, skyBiometryAPI_KEY)
response = client.faces_recognize('all', faceCompareURL, namespace = 'facetrain')
print response
def recognize(request):
if request.method == 'POST':
user = request.user
profile = Profile.objects.get(user=user)
f = request.POST
form = ImageUploadForm(request.POST, request.FILES)
if form.is_valid():
catching = Catching.objects.create(
image=form.cleaned_data['image'],
senior=None,
profile=profile,
comment=""
)
catching.save()
image_url = 'http://150.95.135.222:8000' + catching.image.url
client = FaceClient('ac38c745411845ce89698e1e2469df79', '9d70c1da17fd49609327c8ca154061f1')
result = client.faces_recognize('all', image_url, namespace='senior')
try:
student_id1 = result['photos'][0]['tags'][0]['uids'][0]['uid'].split('@')[0]
confidence1 = result['photos'][0]['tags'][0]['uids'][0]['confidence']
senior1 = Senior.objects.get(student_id=student_id1)
senior1_name = senior1.name
student_id2 = result['photos'][0]['tags'][0]['uids'][1]['uid'].split('@')[0]
confidence2 = result['photos'][0]['tags'][0]['uids'][1]['confidence']
senior2 = Senior.objects.get(student_id=student_id2)
senior2_name = senior2.name
student_id3 = result['photos'][0]['tags'][0]['uids'][2]['uid'].split('@')[0]
confidence3 = result['photos'][0]['tags'][0]['uids'][2]['confidence']
senior3 = Senior.objects.get(student_id=student_id3)
senior3_name = senior3.name
catchsenior = f['catchsenior']
if len(result['photos'][0]['tags']) > 1:
student_id4 = result['photos'][0]['tags'][1]['uids'][0]['uid'].split('@')[0]
confidence4 = result['photos'][0]['tags'][1]['uids'][0]['confidence']
senior4 = Senior.objects.get(student_id=student_id4)
senior4_name = senior4.name
student_id5 = result['photos'][0]['tags'][1]['uids'][1]['uid'].split('@')[0]
confidence5 = result['photos'][0]['tags'][1]['uids'][1]['confidence']
senior5 = Senior.objects.get(student_id=student_id5)
senior5_name = senior5.name
student_id6 = result['photos'][0]['tags'][1]['uids'][2]['uid'].split('@')[0]
confidence6 = result['photos'][0]['tags'][1]['uids'][2]['confidence']
senior6 = Senior.objects.get(student_id=student_id6)
senior6_name = senior6.name
return render(request, 'software/recognize.html', {'catching': catching,
'image_url': image_url,
'senior1_name': senior1_name,
'confidence1': confidence1,
'student_id1': student_id1,
'senior2_name': senior2_name,
'confidence2': confidence2,
'student_id2': student_id2,
'senior3_name': senior3_name,
'confidence3': confidence3,
'student_id3': student_id3,
'senior4_name': senior4_name,
'confidence4': confidence4,
'student_id4': student_id4,
'senior5_name': senior5_name,
'confidence5': confidence5,
'student_id5': student_id5,
'senior6_name': senior6_name,
'confidence6': confidence6,
'student_id6': student_id6,
'catchsenior': catchsenior,
'person_num': '2',
})
return render(request, 'software/recognize.html', {'catching': catching,
'image_url': image_url,
'senior1_name': senior1_name,
'confidence1': confidence1,
'student_id1': student_id1,
'senior2_name': senior2_name,
'confidence2': confidence2,
'student_id2': student_id2,
'senior3_name': senior3_name,
'confidence3': confidence3,
'student_id3': student_id3,
'catchsenior': catchsenior,
'person_num': '1',
})
except IndexError as err:
return HttpResponse("Index Error - Please contact to kakaotalk ID : mnmnm059")
except Exception as err:
return HttpResponse(str(err) + "- Please contact to kakaotalk ID : mnmnm059")
else:
return HttpResponseForbidden('form is invalid')
else:
return HttpResponseForbidden('Allowed via POST')
