Update app.py

app.py

@@ -11,11 +11,6 @@ os.system('bash ./whisper.cpp/models/download-ggml-model.sh medium')
 os.system('bash ./whisper.cpp/models/download-ggml-model.sh large')
 os.system('bash ./whisper.cpp/models/download-ggml-model.sh base.en')
 
-#os.system('./whisper.cpp/main -m whisper.cpp/models/ggml-base.en.bin -f whisper.cpp/samples/jfk.wav')
-#print("SEURAAVAKSI SMALL TESTI")
-#os.system('./whisper.cpp/main -m whisper.cpp/models/ggml-small.bin -f whisper.cpp/samples/jfk.wav')
-#print("MOI")
-
 
 import gradio as gr
 from pathlib import Path
@@ -25,11 +20,7 @@ import re
 import time
 
 from pytube import YouTube
-#from transformers import MarianMTModel, MarianTokenizer
 
-import psutil
-num_cores = psutil.cpu_count()
-os.environ["OMP_NUM_THREADS"] = f"{num_cores}"
 headers = {'Authorization': os.environ['DeepL_API_KEY']}
 
 
@@ -227,7 +218,8 @@ def speech_to_text(video_file_path, selected_source_lang, whisper_model):
     2. Watch it in the first video component
     3. Run automatic speech recognition on the video using fast Whisper models
     4. Translate the recognized transcriptions to 26 languages supported by deepL
-    5. Burn the translations to the original video and watch the video in the 2nd video component
+    5. Download generated subtitles in .vtt and .srt formats
+    6. Watch the the original video with generated subtitles
     
     Speech Recognition is based on models from OpenAI Whisper https://github.com/openai/whisper
     This space is using c++ implementation by https://github.com/ggerganov/whisper.cpp