faceserver/apiserver

API server

Frontend server written in golang. Technology demo - do not use in production !

Main purpose:

• serve stored images
• send images to vectorizer
• store vectors in database
• compare vectors and return ids

No local state, can be scaled.

Configuration

Edit apiserver.yaml file:

Key	Value	Description
port	8080	Port to listen
vectorizer	http://vectorizer:8080/vectorize	Vectorizer url
dbuser	faceserver	DB user
dbpassword	secret	DB password
dbname	faceserver	DB name
dbhost	db	DB host

Do not change configuration if you want run prepared docker-compose.

DB configuration

Only postgresql is supported now. Create new role and user:

createuser -D -P -S faceserver
createdb -E UTF8 -O faceserver faceserver

Create API server tables:

psql -U faceserver -h localhost faceserver <../init.sql

Instalation

Docker image

Build docker image - preferred method:

docker build -t apiserver:latest .

Local compilation

Golang 1.12 is required. Run:

go build main.go

HTTP API

Learn

curl -X POST -F 'person=PID' -F 'directory=DIR' -F 'file=@portrait.jpg' http://localhost:8080/learn

Replace PID with person's id (e.g. database id or name) and DIR with your directory name (e.g. company name). People are recognized only within same directory. png or jpeg images are supported. Only images with one face are allowed for learning !

Result:

{
"status":"OK",
"url":"/files/01e66d8f-536e-4e5ab3b1-521672739d15.jpg",
"filename":"photo.jpg",
"directory":"mydir",
"persons":[
{"id":"PID","box":[0,15,65,88],"score":0.9909800887107849}
]}

Field	Description
status	Status message - either OK or error text
url	Relative url to original image
filename	Original image filename
directory	Directory name
persons	Recognized people array
id	Person's id
box	Box around face
score	Face detection score (i.e. probability)

Recognize

curl -X POST -F 'directory=DIR' -F 'file=@photo.jpg' http://localhost:8080/recognize

Replace DIR with your directory name (e.g. company name). People are recognized only within same directory. For each detected face the most probable person's id is returned. png or jpeg images are supported.

Result:

{
"status":"OK",
"url":"/files/00636b47-e6a5-4fab-8a02-9e44d052c193.jpg",
"filename":"photo.jpg",
"directory":"mydir",
"persons":[
{"id":"PID1","box":[2797,1164,2918,1285],"score":0.999998927116394,"probability":0.8342},
{"id":"PID2","box":[2398,1854,2590,2046],"score":0.9999780654907227,"probability":0.32546},
{"id":"PID3","box":[1753,1148,1905,1300],"score":0.9999217987060547,"probability":0.65785}
]}

Field	Description
status	Status message - either OK or error text
url	Relative url to original image
filename	Original image filename
directory	Directory name
persons	Recognized people array
id	Person's id
box	Box around face
score	Face detection score (i.e. probability)
probability	Person recognition probability

Files

/files/... path contains all learned or recognized images.

Licensing

Code in this repository is licensed under the Apache 2.0. See LICENSE.