write workflow of code
explain deployment parameters
Run docker-compose up with the b/m docker-compose.yml and test endpoint with b/m API, body and check against expected results
version: '3.3'
services:
facial_recognition:
ports:
- '7777:7777'
volumes:
- '/home:/home'
restart: unless-stopped
environment:
- MODEL_DIR=../20170512-110547
image: echizen321/facial_recognition
# workflow:
# 1) check if have vehicle
# 2)
# a) if have, check the vehicle for LP (tighter constraint for LP detection)
# b) else check original image for LP anyway
# 3) if have LP, check LP for contents (OCR)
#
# env variables:
# - LP_THRESHOLD (default 0.2)
# - OCR_THRESHOLD (default 0.4)
# - MIN_LP_LENGTH (default 3)
POST
http://172.17.0.1:7777/FacialRecognition
{
"fileLocation": "/home/plato/Desktop/few_images/faces.jpg"
}
{
"bounding_box_format": "top, left, bottom, right",
"results": [
{
"boundingBox": [
169,
410,
17,
542
],
"confidence": 0.055359518990338016,
"embedding": [ ... ],
"name": "Unknown"
},
...
]
}
...
Content type
Image
Digest
Size
2.1 GB
Last updated
about 6 years ago
docker pull echizen321/facial_recognition