Face Expression Estimation¶
Are people in front looking happy or surprised?
Getting Started¶
Using Angus Python SDK:
# -*- coding: utf-8 -*-
from pprint import pprint
import angus.client
conn = angus.client.connect()
service = conn.services.get_service('face_expression_estimation', version=1)
job = service.process({'image': open('./macgyver.jpg', 'rb')})
pprint(job.result)
Input¶
The API takes a stream of 2d still images as input, of format jpg
or png
, without constraints on resolution.
Note however that the bigger the resolution, the longer the API will take to process and give a result.
The function process()
takes a dictionary as input formatted as follows:
{'image' : file}
image
: a pythonFile Object
as returned for example byopen()
or aStringIO
buffer.
Output¶
Events will be pushed to your client following that format:
{
"input_size" : [480, 640],
"nb_faces" : 1,
"faces" : [
{
"roi" : [345, 223, 34, 54],
"roi_confidence" : 0.89,
"neutral" : 0.1,
"happiness" : 0.2,
"surprise" : 0.7,
"anger" : 0.01,
"sadness" : 0.1,
}
]
}
input_size
: width and height of the input image in pixels (to be used as reference toroi
output.nb_faces
: number of faces detected in the given imageroi
: contains[pt.x, pt.y, width, height]
where pt is the upper left point of the rectangle outlining the detected face.roi_confidence
: an estimate of the probability that a real face is indeed located at the givenroi
.neutral
,happiness
,surprise
,anger
,sadness
: a float in[0, 1]
measuring the intensity of the corresponding face expression.
Code Sample¶
requirements: opencv2, opencv2 python bindings
This code sample retrieves the stream of a web cam and display in a GUI the result of the face_expression_estimation
service.
# -*- coding: utf-8 -*-
import StringIO
import cv2
import numpy as np
import angus.client
def main(stream_index):
camera = cv2.VideoCapture(stream_index)
camera.set(cv2.cv.CV_CAP_PROP_FRAME_WIDTH, 640);
camera.set(cv2.cv.CV_CAP_PROP_FRAME_HEIGHT, 480);
camera.set(cv2.cv.CV_CAP_PROP_FPS, 10)
if not camera.isOpened():
print("Cannot open stream of index {}".format(stream_index))
exit(1)
print("Input stream is of resolution: {} x {}".format(camera.get(3), camera.get(4)))
conn = angus.client.connect()
service = conn.services.get_service('face_expression_estimation', 1)
service.enable_session()
while camera.isOpened():
ret, frame = camera.read()
if not ret:
break
### angus.ai computer vision services require gray images right now.
gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
ret, buff = cv2.imencode(".jpg", gray, [cv2.IMWRITE_JPEG_QUALITY, 80])
buff = StringIO.StringIO(np.array(buff).tostring())
job = service.process({"image": buff})
res = job.result
for face in res['faces']:
x, y, dx, dy = face['roi']
cv2.rectangle(frame, (x, y), (x+dx, y+dy), (0,255,0))
### Sorting of the 5 expressions measures
### to display the most likely on the screen
exps = [(face[exp], exp) for exp in
['sadness', 'happiness', 'neutral', 'surprise', 'anger']]
exps.sort()
max_exp = exps[-1]
cv2.putText(frame, str(max_exp[1]), (x, y),
cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 255, 255))
cv2.imshow('original', frame)
if cv2.waitKey(1) & 0xFF == ord('q'):
break
### Disabling session on the server
service.disable_session()
camera.release()
cv2.destroyAllWindows()
if __name__ == '__main__':
### Web cam index might be different from 0 on your setup.
### To grab a given video file instead of the host computer cam, try:
### main("/path/to/myvideo.avi")
main(0)