#config.gpu_options.allow_growth=True #不全部占满显存, 按需分配
set_session(tf.Session(config=config))
datapath = ''
modelpath = 'model_speech'
if (not os.path.exists(modelpath)): # 判断保存模型的目录是否存在
os.makedirs(modelpath) # 如果不存在，就新建一个，避免之后保存模型的时候炸掉
system_type = plat.system() # 由于不同的系统的文件路径表示不一样，需要进行判断
if (system_type == 'Windows'):
datapath = 'E:\\语音数据集'
elif (system_type == 'Linux'):
datapath = 'dataset'
else:
print('*[Message] Unknown System\n')
datapath = 'dataset'
ms = ModelSpeech(datapath)
ms.LoadModel(
os.path.join(modelpath, 'm251', 'speech_model251_e_0_step_42500.model'))
ms.TestModel(datapath, str_dataset='test', data_count=128, out_report=True)
#r = ms.RecognizeSpeech_FromFile('E:\\语音数据集\\ST-CMDS-20170001_1-OS\\20170001P00241I0053.wav')
#r = ms.RecognizeSpeech_FromFile('E:\\语音数据集\\ST-CMDS-20170001_1-OS\\20170001P00020I0087.wav')
#r = ms.RecognizeSpeech_FromFile('E:\\语音数据集\\wav\\train\\A11\\A11_167.WAV')
#r = ms.RecognizeSpeech_FromFile('E:\\语音数据集\\wav\\test\\D4\\D4_750.wav')
#print('*[提示] 语音识别结果：\n',r)
if (not os.path.exists(modelpath)): # 判断保存模型的目录是否存在
os.makedirs(modelpath) # 如果不存在，就新建一个，避免之后保存模型的时候炸掉
system_type = plat.system() # 由于不同的系统的文件路径表示不一样，需要进行判断
if (system_type == 'Windows'):
datapath = 'I:\\python_speech_file'
modelpath = modelpath + '\\'
elif (system_type == 'Linux'):
datapath = 'dataset'
modelpath = modelpath + '/'
else:
print('*[Message] Unknown System\n')
datapath = 'dataset'
modelpath = modelpath + '/'
ms = ModelSpeech(datapath)
ms.LoadModel(modelpath + 'm251/speech_model251_e_0_step_79500.model')
ms.TestModel(datapath, str_dataset='dev', data_count=256, out_report=True)
#for index in range(10):
#ms.TestModel(datapath, str_dataset='test', data_count = 512, out_report = True)
#print(rate/10)
#r = ms.RecognizeSpeech_FromFile('E:\\语音数据集\\ST-CMDS-20170001_1-OS\\20170001P00241I0053.wav')
#r = ms.RecognizeSpeech_FromFile('E:\\语音数据集\\ST-CMDS-20170001_1-OS\\20170001P00020I0087.wav')
#r = ms.RecognizeSpeech_FromFile('E:\\语音数据集\\wav\\train\\A11\\A11_167.WAV')
#r = ms.RecognizeSpeech_FromFile('E:\\语音数据集\\wav\\test\\D4\\D4_750.wav')
#print('*[提示] 语音识别结果：\n',r)