Update app.py

app.py

@@ -9,13 +9,14 @@ paper_text = "[Paper]"
 model = whisper.load_model("tiny")
 print('model loaded')
 
+def round_time_resolution(time_resolution):
+    multiple = float(time_resolution) / 0.4
+    rounded_multiple = round(multiple)
+    rounded_time_resolution = rounded_multiple * 0.4
+    return rounded_time_resolution
+
 def predict(audio_path, time_resolution):
-    def round_time_resolution(time_resolution):
-        multiple = float(time_resolution) / 0.4
-        rounded_multiple = round(multiple)
-        rounded_time_resolution = rounded_multiple * 0.4
-        return rounded_time_resolution
-    # audio_tagging_time_resolution = round_time_resolution(time_resolution)
+    audio_tagging_time_resolution = round_time_resolution(time_resolution)
     # result = model.transcribe(audio_path, at_time_res=audio_tagging_time_resolution)
     # # ASR Results
     # print(result["text"])
@@ -31,7 +32,7 @@ def predict(audio_path, time_resolution):
     #     print(segment)
     #     at_output = at_output + str(segment['time']['start']) + 's-' + str(segment['time']['end']) + 's: ' + ','.join([x[0] for x in segment['audio tags']]) + '\n'
     #     print(at_output)
-    asr_output, at_output = 's', 'k'
+    asr_output, at_output = str(audio_tagging_time_resolution), 'k'
     return asr_output, at_output
 
 iface = gr.Interface(fn=predict,