Improve model handling

client.py

@@ -2,105 +2,30 @@
 # -*- coding: utf-8 -*-
 from __future__ import absolute_import, division, print_function
 
-import argparse
 import numpy as np
-import shlex
-import subprocess
 import sys
 import wave
-import json
 
 from deepspeech import Model, version
 from timeit import default_timer as timer
 
-try:
-    from shhlex import quote
-except ImportError:
-    from pipes import quote
 
-
-def convert_samplerate(audio_path, desired_sample_rate):
-    sox_cmd = 'sox {} --type raw --bits 16 --channels 1 --rate {} --encoding signed-integer --endian little --compression 0.0 --no-dither - '.format(
-        quote(audio_path), desired_sample_rate)
-    try:
-        output = subprocess.check_output(
-            shlex.split(sox_cmd), stderr=subprocess.PIPE)
-    except subprocess.CalledProcessError as e:
-        raise RuntimeError('SoX returned non-zero status: {}'.format(e.stderr))
-    except OSError as e:
-        raise OSError(e.errno, 'SoX not found, use {}hz files or install it: {}'.format(
-            desired_sample_rate, e.strerror))
-
-    return desired_sample_rate, np.frombuffer(output, np.int16)
-
-
-def metadata_to_string(metadata):
-    return ''.join(token.text for token in metadata.tokens)
-
-
-def words_from_candidate_transcript(metadata):
-    word = ""
-    word_list = []
-    word_start_time = 0
-    # Loop through each character
-    for i, token in enumerate(metadata.tokens):
-        # Append character to word if it's not a space
-        if token.text != " ":
-            if len(word) == 0:
-                # Log the start time of the new word
-                word_start_time = token.start_time
-
-            word = word + token.text
-        # Word boundary is either a space or the last character in the array
-        if token.text == " " or i == len(metadata.tokens) - 1:
-            word_duration = token.start_time - word_start_time
-
-            if word_duration < 0:
-                word_duration = 0
-
-            each_word = dict()
-            each_word["word"] = word
-            each_word["start_time "] = round(word_start_time, 4)
-            each_word["duration"] = round(word_duration, 4)
-
-            word_list.append(each_word)
-            # Reset
-            word = ""
-            word_start_time = 0
-
-    return word_list
-
-
-def metadata_json_output(metadata):
-    json_result = dict()
-    json_result["transcripts"] = [{
-        "confidence": transcript.confidence,
-        "words": words_from_candidate_transcript(transcript),
-    } for transcript in metadata.transcripts]
-    return json.dumps(json_result, indent=2)
-
-
-class VersionAction(argparse.Action):
-    def __init__(self, *args, **kwargs):
-        super(VersionAction, self).__init__(nargs=0, *args, **kwargs)
-
-    def __call__(self, *args, **kwargs):
-        print('DeepSpeech ', version())
-        exit(0)
+uk_model = Model("./uk.tflite")
+en_model = Model("./deepspeech-0.7.3-models.tflite")
 
 
 def client(audio_file, lang="uk"):
     model_load_start = timer()
     # sphinx-doc: python_ref_model_start
-    model_path = "uk.tflite"
+    model = uk_model
     if lang not in ["en", "uk"]:
         lang = "uk"
     if lang == "uk":
-        model_path = "./uk.tflite"
+        model = uk_model
     if lang == "en":
-        model_path = "./deepspeech-0.7.3-models.tflite"
-    print(lang)
-    ds = Model(model_path)
+        model = en_model
+
+    ds = model
     # sphinx-doc: python_ref_model_stop
     model_load_end = timer() - model_load_start
     print('Loaded model in {:.3}s.'.format(model_load_end), file=sys.stderr)