#!/usr/bin/python3
#supervised ML apple & orange
# assume smooth =0 and bumpy=1

from sklearn import tree
import os

smooth=0
bumpy=1

features =[[120,smooth],[130,smooth],[140,bumpy],[150,bumpy]]
label=["apple","apple","orange","orange"]

algo=tree.DecisionTreeClassifier()
trained=algo.fit(features,label)
x=[[129,bumpy]]
output=trained.predict(x)

print(output[0])
sound="echo "+str(output[0])+" | festival --tts"
print("sound=",sound)
os.system(sound)


if(output=="apple"):
	print("apple show")
	os.system('eog apple.png')
else:
	print("orange show")
	os.system('eog orange.jpg')