# Copyright (C) 2015 Ross D Milligan
# GNU GENERAL PUBLIC LICENSE Version 3 (full notice can be found at https://github.com/rdmilligan/SaltwashAR)
from features.base import *
import ConfigParser
import numpy as np
import cv2
from constants import *
class HappyColour(Feature, Speaking, Emotion):
def __init__(self, text_to_speech):
Feature.__init__(self)
Speaking.__init__(self, text_to_speech)
Emotion.__init__(self)
self._load_config()
def _load_config(self):
config = ConfigParser.ConfigParser()
config.read('scripts/features/happycolour/happycolour.ini')
# get colour range from config
self.lower_colour = np.array(map(int, config.get('Colour', 'Lower').split(',')))
self.upper_colour = np.array(map(int, config.get('Colour', 'Upper').split(',')))
# get threshold from config
self.lower_threshold = config.getint('Threshold', 'Lower')
self.upper_threshold = config.getint('Threshold', 'Upper')
def _thread(self, args):
image = args
# convert image from BGR to HSV
hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
# only get colours in range
mask = cv2.inRange(hsv, self.lower_colour, self.upper_colour)
# obtain colour count
colour_count = cv2.countNonZero(mask)
# check whether to stop thread
if self.is_stop: return
# respond to colour count
if colour_count < self.lower_threshold:
self._text_to_speech("I just feel sad")
self._display_emotion(SAD)
elif colour_count > self.upper_threshold:
self._text_to_speech("I'm so happy!")
self._display_emotion(HAPPY)
