Spaces:
Sleeping
Sleeping
| import pickle | |
| import pandas as pd | |
| import numpy | |
| #import logging, os | |
| #logging.disable(logging.WARNING) | |
| #os.environ["TF_CPP_MIN_LOG_LEVEL"] = "3" | |
| import tensorflow as tf | |
| import tensorflow_text as tf_text | |
| from metaphone import doublemetaphone | |
| import re | |
| with open('vocab_data.pkl', 'rb') as fp: | |
| hin_vocab = pickle.load(fp) | |
| vocab_keys=[l for l in hin_vocab] | |
| #all_data_vocab_53k_mixed_batch_v2 | |
| reloaded = tf.saved_model.load("translator") | |
| def t_text(line): | |
| line=re.sub("[.!?\\-\'\"]", "",line).lower().strip() | |
| string='' | |
| for j in line.split(' '): | |
| if doublemetaphone(j)[0]+'*'+doublemetaphone(j[::-1])[0]+'*'+j[:2]+'*'+j[len(j)-1:] in vocab_keys: | |
| string=string+list(hin_vocab[doublemetaphone(j)[0]+'*'+doublemetaphone(j[::-1])[0]+'*'+j[:2]+'*'+j[len(j)-1:]])[0]+' ' | |
| else: | |
| string=string+j+' ' | |
| return string.lower().strip() | |
| def outcome(input): | |
| trans_text=t_text(input) | |
| result=reloaded.tf_translate(tf.constant([trans_text]))['text'][0].numpy().decode() | |
| return result | |
| #print(outcome("Please timer ko rokey")) |