save

app.py

@@ -43,8 +43,8 @@ def runApi():
 
     audio = "audio.mp3"
 
-    audio = whisper.load_audio(audio)
-    audio = whisper.pad_or_trim(audio)
+    audioOri = whisper.load_audio(audio)
+    audio = whisper.pad_or_trim(audioOri)
     
     mel = whisper.log_mel_spectrogram(audio).to(model.device)
     
@@ -54,9 +54,9 @@ def runApi():
     result = whisper.decode(model, mel, options)
 
     # test 2
-    ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")
-    sample = ds[0]["audio"]
-    prediction = pipe(sample.copy())["text"]
+    # ds = load_dataset("hf-internal-testing/librispeech_asr_dummy", "clean", split="validation")
+    # sample = ds[0]["audio"]
+    prediction = pipe(audioOri)["text"]
     print(prediction)
 
     end_time = time.time()