Update app.py

app.py

@@ -40,8 +40,8 @@ def extract_audio(input_video_name):
     return mp3_file
 
 def transcribe(audio, max_segment_duration=2.0):  # Set your desired max duration here
-    model = WhisperModel("tiny", device="cpu", cpu_threads=12, local_files_only=True)
-    segments, info = model.transcribe(audio, vad_filter=True, vad_parameters=dict(min_silence_duration_ms=1500), word_timestamps=True, log_progress=True)
+    model = WhisperModel("tiny", device="cpu)
+    segments, info = model.transcribe(audio, vad_filter=True, vad_parameters=dict(min_silence_duration_ms=1500), word_timestamps=True)
     segments = list(segments)  # The transcription will actually run here.
     wordlevel_info = []
     for segment in segments:
@@ -225,10 +225,12 @@ def generate_translated_subtitle(language, segments, input_video_name):
         f.write(text)
     return subtitle_file
 
-def process_video(video):
+def process_video(video, progress=gr.Progress()):
 
+    progress(0, desc="Starting")
     mp3_file=extract_audio(video)
     wordlevel_info=transcribe(mp3_file)
+    progress(50, desc="transcribe")
     subtitles = create_subtitles(wordlevel_info)
     subtitle_file = generate_subtitle_file('fa', subtitles, 'video_subtitled')
     srt_string = read_srt_file(subtitle_file)
@@ -236,6 +238,7 @@ def process_video(video):
     srt = write_google(google_translate)
     #segments = pysrt.open(srt, encoding="utf-8")
     sub = generate_translated_subtitle("fa", google_translate, "video_subtitled")
+    progress(100, desc="Finish")
     return sub