adding app.py

app.py

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+import os
+import streamlit as st
+from moviepy.editor import VideoFileClip
+import speech_recognition as sr
+from pydub import AudioSegment
+
+def extract_audio_from_video(video_path, audio_path):
+    video = VideoFileClip(video_path)
+    video.audio.write_audiofile(audio_path, codec="pcm_s16le")
+
+def transcribe_audio(audio_path):
+    recognizer = sr.Recognizer()
+    audio = AudioSegment.from_wav(audio_path)
+
+    chunk_length_ms = 60000  # 60 seconds per chunk
+    chunks = [audio[i:i + chunk_length_ms] for i in range(0, len(audio), chunk_length_ms)]
+
+    full_text = ""
+    for i, chunk in enumerate(chunks):
+        chunk.export(f"chunk_{i}.wav", format="wav")
+        with sr.AudioFile(f"chunk_{i}.wav") as source:
+            audio_data = recognizer.record(source)
+            try:
+                text = recognizer.recognize_google(audio_data)
+                full_text += text + " "
+            except sr.UnknownValueError:
+                full_text += "[Unclear speech] "
+            except sr.RequestError as e:
+                full_text += f"[API error: {e}] "
+
+    for i in range(len(chunks)):
+        os.remove(f"chunk_{i}.wav")
+
+    return full_text
+
+st.title("Video to Text Transcription")
+st.write("Upload a video file to transcribe its audio to text.")
+
+uploaded_file = st.file_uploader("Choose a video file", type=["mp4", "mov", "avi", "mkv"])
+
+if uploaded_file is not None:
+    with open("temp_video." + uploaded_file.name.split('.')[-1], "wb") as f:
+        f.write(uploaded_file.getbuffer())
+    audio_path = "temp_audio.wav"
+
+    extract_audio_from_video("temp_video." + uploaded_file.name.split('.')[-1], audio_path)
+    st.write("Extracting and transcribing audio...")
+
+    transcribed_text = transcribe_audio(audio_path)
+    st.write("Transcription completed. Here's the text:")
+    st.text_area("Transcribed Text", transcribed_text, height=300)
+
+    with open("transcribed_text.txt", "w", encoding="utf-8") as text_file:
+        text_file.write(transcribed_text)
+    st.download_button("Download Transcribed Text", data=transcribed_text, file_name="transcribed_text.txt")
+
+    os.remove("temp_video." + uploaded_file.name.split('.')[-1])
+    os.remove(audio_path)

requirements.txt

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+certifi==2024.12.14
+charset-normalizer==3.4.1
+decorator==4.4.2
+idna==3.10
+imageio==2.36.1
+imageio-ffmpeg==0.5.1
+moviepy==1.0.3
+numpy==2.2.1
+pillow==10.4.0
+proglog==0.1.10
+pydub==0.25.1
+python-dotenv==1.0.1
+requests==2.32.3
+SpeechRecognition==3.13.0
+tqdm==4.67.1
+typing_extensions==4.12.2
+urllib3==2.3.0