def get_gender():
"""
This API returns the predicted gender of all faces detected in an image.
Call this api passing a coloured image.
---
tags:
- Image Analyzer
consumes:
- multipart/form-data
produces:
-application/json
parameters:
- in: formData
name: upfile
type: file
required: true
description: Upload your file
responses:
500:
description: Error, something went wrong!
200:
description: Detection success!
"""
response = None
iFile = request.files.getlist('upfile')[0]
img = load_image(iFile)
img = rotate_image(img, iFile)
img = limit_size_image(img)
model = Gender(img)
response = model.get_prediction()
return jsonify(response)
def lambda_handler(event, context):
if 'body' in event:
item = json.loads(event.pop('body', event))
else:
item = event
dto = Gender(item)
ret_val = dto.update()
response = {'statusCode': 200, 'body': json.dumps({'result': ret_val})}
return response
def lambda_handler(event, context):
if 'queryStringParameters' in event:
item = event.pop('queryStringParameters')
if isinstance(item, str):
item = literal_eval(item)
else:
item = event
dto = Gender(item)
ret_val = dto.delete()
response = {'statusCode': 200, 'body': json.dumps({'result': ret_val})}
return response
def lambda_handler(event, context):
if 'queryStringParameters' in event:
item = event.pop('queryStringParameters')
if isinstance(item, str):
item = literal_eval(item)
else:
item = event
dto = Gender(item)
return_item = dto.read()
response = {
'statusCode': 200,
"body": json.dumps(return_item),
}
return response
def scrap_profiles(self):
instadir = open("instarank.csv", "w")
output = csv.writer(instadir, delimiter=',')
profiles = []
while (True):
time.sleep(1)
profileName = self.get_post_profName()
profileLocation = self.get_post_location()
postTime = self.get_post_time()
likes = self.get_post_likes()
imageAlt = self.get_image_alt()
tgender = Gender(profileName)
print(profileName + ' @ ' + profileLocation + ' ' +
str(postTime) + ' ' + str(likes) + " " + str(tgender))
if (tgender == "null" or tgender == "female"):
tprofile = [
profileName, profileLocation, postTime, imageAlt, likes,
tgender
]
self.writeToCsv(tprofile, output)
print("t scraped")
time.sleep(1)
try:
self.go_to_next()
except Exception as e:
print('No next')
def load_models(path):
global gender, expression, multiple, face_detection, landmarks2d, landmarks3d
gender = Gender(os.path.join(path, "gender.zip"))
expression = Expression(os.path.join(path, "expression.zip"))
multiple = Multiple(os.path.join(path, "multiple"))
face_detection = FaceDetection(os.path.join(path, "face_detection"))
landmarks2d = LandMarks2D(path)
landmarks3d = LandMarks3D(path)
def gender():
name = request.form['name']
test = Gender(name)
answer = test.run()
print answer
return render_template('gender.html', data=answer)