NCS2 experiment on Raspberry Pi

extract_emotion_and_gender.pl

#!/usr/bin/perl

$| = 1;

my($data);

sub emit_if_complete {
    my($d) = @_;
    if ($d->{'g'} && $d->{'e'}) {
        print qq/{"g":"$d->{'g'}","e":"$d->{'e'}"}\n/;
    }
}

while (<>) {
    if (/^\[0,1\]/) {
        # reset
        $data = {};
    }

    if (!$data->{'g'} && /Predicted gender, age = ([FM]),(\d+)/) {
        $data->{'g'} = $1;
        &emit_if_complete($data)
    }

    if (!$data->{'e'} && /Predicted emotion = (\w+)/) {
        $data->{'e'} = $1;
        &emit_if_complete($data);
    }
}

face.sh

device=MYRIAD
fpmode=FP16

bin/interactive_face_detection_demo \
	-d ${device} -m intel_models/face-detection-retail-0004/${fpmode}/face-detection-retail-0004.xml \
	-d_ag ${device} -m_ag intel_models/age-gender-recognition-retail-0013/${fpmode}/age-gender-recognition-retail-0013.xml \
	-d_em ${device} -m_em intel_models/emotions-recognition-retail-0003/${fpmode}/emotions-recognition-retail-0003.xml \
 	-d_hp ${device} -m_hp intel_models/head-pose-estimation-adas-0001/${fpmode}/head-pose-estimation-adas-0001.xml \
	$*

face_display.sh

./face.sh -r $* | tee >(./extract_emotion_and_gender.pl | sudo ./show_emotion_and_gender.py)

mobilenet-ssd.sh

./bin/object_detection_demo_ssd_async -d MYRIAD -m mobilenet-ssd/FP16/mobilenet-ssd.xml $*

model_downloader.sh

model=$1
url_base=https://download.01.org/openvinotoolkit/2018_R4/open_model_zoo
out_base=intel_models
cmd="wget --no-check-certificate"

function get_files {
  fpmode=$1
  p=$model/$fpmode
  mkdir -p $out_base/$p
  $cmd $url_base/$p/$model.bin -O $out_base/$p/$model.bin
  $cmd $url_base/$p/$model.xml -O $out_base/$p/$model.xml
}

get_files FP16
# get_files FP32

show_emotion_and_gender.py

#!/usr/bin/env python

import unicornhat as unicorn
import time
import json
import sys
import os

unicorn.set_layout(unicorn.AUTO)
unicorn.rotation(270)
unicorn.brightness(0.4)
width,height=unicorn.get_shape()

faces = {
    'neutral': [
        "00000000",
        "01000010",
        "01000010",
        "00000000",
        "00000000",
        "01111110",
        "00000000",
        "00000000",
        ],
    'happy': [
        "00000000",
        "01000010",
        "10100101",
        "00000000",
        "01000010",
        "00100100",
        "00011000",
        "00000000",
        ],
    'sad': [
        "00000000",
        "01100110",
        "10000001",
        "00000000",
        "00011000",
        "00100100",
        "01000010",
        "00000000",
        ],
    'surprise': [
        "01000010",
        "10100101",
        "01000010",
        "00000000",
        "00011000",
        "00100100",
        "00100100",
        "00011000",
        ],
    'anger': [
        "00000000",
        "11000011",
        "00100100",
        "00000000",
        "00011000",
        "00100100",
        "01000010",
        "00000000",
        ],
};

def show_matrix(matrix, r, g, b):
    for y, row in enumerate(matrix):
        for x, p in enumerate(row):
            if p == '1':
                unicorn.set_pixel(x, y, r, g, b)
            else:
                unicorn.set_pixel(x, y, 0, 0, 0)
    unicorn.show()

def process(data):
    f = faces[data['e']]
    if data['g'] == 'F':
        r, g, b = 255, 0, 200
    else :
        r, g, b = 0, 200, 255
        
    show_matrix(f, r, g, b)

while True:
    line = sys.stdin.readline()
    data = json.loads(line)
    process(data)