From c05562f63cad19c66c41a1855aab17223d333d22 Mon Sep 17 00:00:00 2001
From: Apostolof <apotwohd@gmail.com>
Date: Sat, 19 Jan 2019 17:45:27 +0200
Subject: [PATCH] Fix batch_feature_extractor, Remove streamClassify

---
 .../batch_feature_extractor.py                |  5 +-
 classifier/streamClassify.py                  | 85 -------------------
 2 files changed, 4 insertions(+), 86 deletions(-)
 delete mode 100644 classifier/streamClassify.py

diff --git a/classifier/feature_extraction/batch_feature_extractor.py b/classifier/feature_extraction/batch_feature_extractor.py
index 8d089de..f03d76c 100644
--- a/classifier/feature_extraction/batch_feature_extractor.py
+++ b/classifier/feature_extraction/batch_feature_extractor.py
@@ -2,7 +2,10 @@ from os import listdir
 from os.path import isfile, join
 import multiprocessing as mp
 import pandas as pd
-from feature_extractor import extractFeatures
+if __name__ == '__main__':
+	from feature_extractor import extractFeatures
+else:
+	from .feature_extractor import extractFeatures
 
 class bcolors:
 	BLUE = '\033[94m'
diff --git a/classifier/streamClassify.py b/classifier/streamClassify.py
deleted file mode 100644
index 699257d..0000000
--- a/classifier/streamClassify.py
+++ /dev/null
@@ -1,85 +0,0 @@
-import pyaudio
-import struct
-import math
-import pandas as pd
-
-from feature_extraction.feature_extractor import extractFeatures
-from preprocessing.data_preprocessing import createSingleFeaturesArray, standardization
-from training.model_training import kFCrossValid, simpleTrain
-
-FORMAT = pyaudio.paInt16
-SHORT_NORMALIZE = (1.0/32768.0)
-CHANNELS = 1
-RATE = 22050
-INPUT_BLOCK_TIME = int(6144 / RATE)
-INPUT_FRAMES_PER_BLOCK = 6144
-
-def classify(block, clf):
-	import numpy as np
-
-	audio_data = np.fromstring(block, np.int16)
-	audio_data = audio_data.astype(int)
-
-	values = extractFeatures(audio_data, 'tmp.json', RATE)
-	audioClass = clf.predict(values)
-
-	return audioClass
-
-class micListener(object):
-	def __init__(self):
-		self.pa = pyaudio.PyAudio()
-		self.stream = self.open_mic_stream()
-
-		print('Training...')
-		dataset, target, featureKeys = createSingleFeaturesArray(
-			'feature_extraction/music_features/',
-			'feature_extraction/speech_features/')
-
-		self.clf = kFCrossValid(dataset, target, model = 'rndForest')
-		print('Training done!')
-
-	def stop(self):
-		self.stream.close()
-
-	def find_input_device(self):
-		device_index = None
-		for i in range( self.pa.get_device_count() ):
-			devinfo = self.pa.get_device_info_by_index(i)
-			print( "Device %d: %s"%(i,devinfo["name"]) )
-
-			for keyword in ["mic","input"]:
-				if keyword in devinfo["name"].lower():
-					print( "Found an input: device %d - %s"%(i,devinfo["name"]) )
-					device_index = i
-					return device_index
-
-		if device_index == None:
-			print( "No preferred input found; using default input device." )
-
-		return device_index
-
-	def open_mic_stream( self ):
-		device_index = self.find_input_device()
-
-		stream = self.pa.open(format = FORMAT, channels = CHANNELS, rate = RATE,
-			input = True, input_device_index = device_index,
-			frames_per_buffer = INPUT_FRAMES_PER_BLOCK)
-
-		return stream
-
-	def listen(self):
-		try:
-			block = self.stream.read(INPUT_FRAMES_PER_BLOCK)
-		except IOError as e:
-			# dammit.
-			print('IOError!')
-			return
-
-		audioClass = classify(block, self.clf)
-		print(audioClass)
-
-if __name__ == "__main__":
-	micStr = micListener()
-
-	for i in range(300):
-		micStr.listen()
\ No newline at end of file