def faceDetect(imgurl):
imgbytes = image_helpers.get_image_from_url(imgurl)
exp = client.detect_faces(Image={'Bytes': imgbytes}, Attributes=['ALL'])
numfaces = len(exp['FaceDetails'])
for facedeets in exp['FaceDetails']:
# construct a printf (almost) style format string for printing the info
fmtstr = '{gender} age {lowage}-{highage},'
# mustache and beard detection
if facedeets['Mustache']['Value'] and facedeets['Beard']['Value']:
fmtstr += ' with beard and mustache,'
elif facedeets['Mustache']['Value']:
fmtstr += ' with mustache,'
elif facedeets['Beard']['Value']:
fmtstr += ' with beard,'
# sunglasses/eyeglasses detection
if facedeets['Sunglasses']['Value']:
fmtstr += ' wearing sunglasses,'
elif facedeets['Eyeglasses']['Value']:
fmtstr += ' wearing glasses,'
fmtstr += ' looks {emotion}'
return (fmtstr.format(
gender=facedeets['Gender']['Value'],
lowage=facedeets['AgeRange']['Low'],
highage=facedeets['AgeRange']['High'],
emotion=facedeets['Emotions'][0]['Type'].lower()), numfaces)
def on_new_camera_image(evt, **kwargs):
global processing
global takePicture
global detected
if takePicture:
if not processing:
print('takepicture is true')
if detected:
print('Taking a picture of it...')
processing = True
#print('Invoke OpenWhisk at ...')
#print(datetime.datetime.now().time())
#print(kwargs['image'].image_number)
pilImage = kwargs['image'].raw_image
pilImage.save("pictures/fromcozmo.jpg", "JPEG")
time.sleep(2)
print('Waiting for image...')
if upload_file('pictures/fromcozmo.jpg','ctec280'):
print('File uploaded successfully!')
# now identify image
# grab the image from URL
client = boto3.client('rekognition')
imgurl = 'https://s3.amazonaws.com/ctec280/pictures/fromcozmo.jpg'
imgbytes = image_helpers.get_image_from_url(imgurl)
print('Sending to AWS Rekognition...')
rekresp = client.detect_labels(Image={'Bytes': imgbytes},MinConfidence=75)
print('Here are the results from Rekognition:')
#pprint(rekresp)
pprint(rekresp['Labels'])
def celeb(imgurl):
img = image_helpers.get_image_from_url(imgurl)
exp = client.recognize_celebrities(Image={'Bytes': img})
try:
Name = exp['CelebrityFaces'][0]['Name']
Confidence = exp['CelebrityFaces'][0]['MatchConfidence']
return "Found Celebrity is " + Name + " with confidence: " + str(
Confidence) + " percent!"
except:
return ""
def faceCompare(imgtargetbytes):
client = boto3.client('rekognition')
# bucket = 'bucket-name'
sourceFile = 'https://blog.njsnet.co/content/images/2017/02/trumprecognition.png'
#targetFile = 'image/102824056.jpg'
#targetFile = 'image/IMG_20160402_155147.jpg'
# grab the image from local
imgsourcebytes = image_helpers.get_image_from_url(sourceFile)
#imgtargetbytes = image_helpers.get_image_from_url(targetFile)
response = client.compare_faces(SimilarityThreshold=70,
SourceImage={'Bytes': imgsourcebytes},
TargetImage={'Bytes': imgtargetbytes})
# for faceMatch in response['FaceMatches']:
# position = faceMatch['Face']['BoundingBox']
# confidence = str(faceMatch['Face']['Confidence'])
# print('The face at ' +
# str(position['Left']) + ' ' +
# str(position['Top']) +
# ' matches with ' + confidence + '% confidence')
for faceMatch in response['FaceMatches']:
if faceMatch == "":
pprint("The face does not match")
else:
pprint("The face matches")
pprint(faceMatch['Similarity'])
pprint(faceMatch['Face']['BoundingBox'])
img = Image.open(BytesIO(imgtargetbytes))
(img_width, img_height) = img.size
draw = ImageDraw.Draw(img)
draw.rectangle(face_detect_draw.bbox_to_coords(
faceMatch['Face']['BoundingBox'], img_width, img_height),
outline=(0, 200, 0))
del draw
img.show()
import boto3
from pprint import pprint
import image_helpers
client = boto3.client('rekognition')
imgurl = "https://thefertilechickonline.com/wp-content/uploads/2017/12/mengroup.jpg"
imgbytes = image_helpers.get_image_from_url(imgurl)
rekesp = client.detect_faces(Image={'Bytes': imgbytes}, Attributes=['ALL'])
pprint(rekesp)
print(len(rekesp['FaceDetails']))
def get_labels(imgurl):
img = image_helpers.get_image_from_url(imgurl)
exp = client.detect_labels(Image={'Bytes': imgbytes}, MinConfidence=50)
return (exp['Labels'])
import boto3
import image_helpers
client = boto3.client('rekognition')
# Dummy image for testing
imgUrl = 'https://www.newreleasetoday.com/images/article_images/art_img_2608.jpg'
imgBytes = image_helpers.get_image_from_url(imgUrl)
result = client.detect_labels(Image={'Bytes': imgBytes})
print(result)
