def fetchFeatures(filepath):
print(filepath)
paths = filepath.split("/")
c = classes.index(paths[1])
# print(paths[1], c)
vec = audio.showFeatures(filepath)
return str(c) + "," + vec
def test(sc):
files = ["sounds/flushing/20150227_193109-flushing-04.wav",
"sounds/bike/20150227_193806-bici-14.wav",
"sounds/blender/20150227_193606-licuadora-14.wav"
]
rfmodel = RandomForestModel.load(sc, RF_PATH)
dtmodel = DecisionTreeModel.load(sc, DT_PATH)
print dtmodel.toDebugString()
for f in files:
vec = audio.showFeatures(f)
testfeatures = Vectors.dense([float(x) for x in vec.split(' ')])
print(vec)
pred = dtmodel.predict(testfeatures)
print("DT Prediction is " + str(pred), classes[int(pred)])
pred = rfmodel.predict(testfeatures)
print("RF Prediction is " + str(pred), classes[int(pred)])
