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Sample Object Detection and Face Recognition

introduction

sample object detection and face recognition function

environment

  • Docker
    • if you need to play face recognition codes, don't use docker container.

install

Create Docker Image

$ docker build -t human_detection:0.1 -f docker/DockerFile .

If you don't use cache, set "--no-cache=true".

Run Docker Container

$ docker run -v `pwd`/script:/home/development/script -it --name human_detection_container human_detection:0.1 /bin/bash

use object detection scripts

  • if you use the object detection scripts, please run these scripts on docker container.

use sample inference script

$ python3 /home/development/script/sample_infer.py

use face recognition scripts

add face images

Please do the following process to add the face information.

  • add the face images into "script/data/face_data"
  • add the face images path and face names into "script/data/face_list.csv"
    • ex) write like ""obama.jpg","obama""

use sample face recognition scripts

$ cd script
$ streamlit run run_face_recognition.py

use face recognition api

Please do the following process to start api server of face recognition

$ cd script
$ python3 web_api.py

You need to call following command to use face recognition api

$ curl localhost:5000/face

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