Update app_utils.py

app_utils.py

@@ -1,3 +1,4 @@
+import gradio as gr
 import torch
 import time
 import numpy as np
@@ -43,57 +44,6 @@ def text_api(text:str):
     )
     return result
 
-# def get_text_score(text):
-#     string=text_api(text)
-#     part1 = str.partition(string, r"text")
-#     want1 = part1[2]
-#     label = want1[4:6]
-#     part2 = str.partition(string, r"probability")
-#     want2 = part2[2]
-#     prob = float(want2[3:-4])
-#     return label, prob
-
-
-# def classify_continuous(audio):
-#     print(type(audio))
-#     print(audio)
-#     sample_rate, signal = (audio) # 这是语音的输入
-#     signal = signal.astype(np.float32)
-#     signal /= np.max(np.abs(signal))
-#     sf.write("data/a.wav", signal, sample_rate)
-#     signal, sample_rate = torchaudio.load("data/a.wav")
-#     signal1 = torchaudio.transforms.Resample(orig_freq=sample_rate, new_freq=16000)(
-#         signal
-#     )
-#     torchaudio.save("data/out.wav", signal1, 16000, encoding="PCM_S", bits_per_sample=16)
-#     Audio = "data/out.wav"
-#     speech, sample_rate = AudioReader.read_wav_file(Audio)
-#     if signal == "none":
-#         return "none", "none", "haha"
-#     else:
-#         segments = vad.segments_offline(speech)
-#         text_results = ""
-#         for part in segments:
-#             _result = ASR_model.infer_offline(
-#                 speech[part[0] * 16 : part[1] * 16], hot_words="任意热词 空格分开"
-#             )
-#             text_results += punc.punctuate(_result)[0]
-
-#         out_prob, score, index, text_lab = classifier.classify_batch(signal1)
-#         print(type(out_prob.squeeze(0).numpy()))
-#         print(out_prob.squeeze(0).numpy())
-#         print(type(text_lab[-1]))
-#         print(text_lab[-1])
-#         return text_results, out_prob.squeeze(0).numpy(), text_lab[-1], Audio
-
-
-
-# def preprocess_image_and_predict(inp):
-#     return None, None, None
-
-# def preprocess_video_and_predict(video):    
-#     return None, None, None, None
-
 #######################################################################
 #规范函数，只管值输入输出：
 def text_score(text):