Face Detection

The face detection API detects faces and returns their coordinates. It functions similarly to the face recognition API except that it does not perform recognition.

Example

../_images/family.jpg
python
import requests

image_data = open("family.jpg","rb").read()

response = requests.post("http://localhost:80/v1/vision/face",files={"image":image_data}).json()

print(response)

Response

json
{'predictions': [{'x_max': 712, 'y_max': 261, 'x_min': 626, 'confidence': 0.99990666, 'y_min': 145}, {'x_max': 620, 'y_max': 288, 'x_min': 543, 'confidence': 0.99986553, 'y_min': 174}, {'x_max': 810, 'y_max': 242, 'x_min': 731, 'confidence': 0.99986434, 'y_min': 163}, {'x_max': 542, 'y_max': 279, 'x_min': 477, 'confidence': 0.99899536, 'y_min': 197}], 'success': True}

We can use the coordinates returned to extract the faces from the image.

python
import requests
from PIL import Image

image_data = open("family.jpg","rb").read()
image = Image.open("family.jpg").convert("RGB")

response = requests.post("http://localhost:80/v1/vision/face",files={"image":image_data}).json()
i = 0
for face in response["predictions"]:

    y_max = int(face["y_max"])
    y_min = int(face["y_min"])
    x_max = int(face["x_max"])
    x_min = int(face["x_min"])
    cropped = image.crop((x_min,y_min,x_max,y_max))
    cropped.save("image{}.jpg".format(i))

    i += 1
../_images/family1.jpg
../_images/family2.jpg
../_images/family3.jpg
../_images/family4.jpg