Spaces:
Sleeping
Sleeping
| # import zipfile | |
| # import os | |
| # import tempfile | |
| # import whisper | |
| # # Specify the input PPTX file and output ZIP file names | |
| # file = '/Users/tushargupta/Downloads/Lecture 1_Definition and conceptualization.pptx' # Replace with your PPTX file path | |
| # file = os.path.splitext(file)[0] + '.zip' | |
| # # Create dictionary to store audio files | |
| # audio_files = {} | |
| # # Create temporary directory for extraction | |
| # temp_dir = tempfile.mkdtemp() | |
| # # Extract the zip file to temp directory | |
| # with zipfile.ZipFile(file, 'r') as zip_ref: | |
| # zip_ref.extractall(temp_dir) | |
| # # Path to media folder | |
| # media_path = os.path.join(temp_dir, 'ppt', 'media') | |
| # # Check if media folder exists | |
| # if os.path.exists(media_path): | |
| # # Create temporary directory for converted files | |
| # temp_audio_dir = tempfile.mkdtemp() | |
| # # Iterate through slide numbers | |
| # slide_num = 1 | |
| # while True: | |
| # # Check for either .mp4 or .m4a file for current slide | |
| # media_file = None | |
| # for ext in ['.mp4', '.m4a']: | |
| # filename = f'media{slide_num}{ext}' | |
| # file_path = os.path.join(media_path, filename) | |
| # if os.path.exists(file_path): | |
| # media_file = file_path | |
| # break | |
| # if not media_file: | |
| # break | |
| # # Create temporary mp3 file | |
| # temp_mp3 = os.path.join(temp_audio_dir, f'temp_{slide_num}.mp3') | |
| # try: | |
| # # Convert to mp3 using ffmpeg | |
| # os.system(f'ffmpeg -i "{media_file}" -vn -acodec libmp3lame "{temp_mp3}" -loglevel quiet') | |
| # # Store the temp mp3 file path in dictionary | |
| # audio_files[slide_num-1] = temp_mp3 | |
| # except Exception as e: | |
| # print(f"Error converting slide {slide_num}: {str(e)}") | |
| # slide_num += 1 | |
| # # Load Whisper model | |
| # model = whisper.load_model("base") | |
| # # Dictionary to store transcriptions by slide number | |
| # slide_transcripts = {} | |
| # # Transcribe each audio file | |
| # for slide_num, audio_file in audio_files.items(): | |
| # # Transcribe the audio file | |
| # result = model.transcribe(audio_file) | |
| # # Store transcription text for this slide | |
| # slide_transcripts[slide_num + 1] = result["text"] | |
| # # Display transcription per slide | |
| # print("\nTranscription by Slide:") | |
| # for slide_num, text in sorted(slide_transcripts.items()): | |
| # print(f"\nSlide {slide_num}:") | |
| # print(text) | |
| import streamlit as st | |
| import zipfile | |
| import os | |
| import tempfile | |
| import whisper | |
| from pathlib import Path | |
| def process_pptx(uploaded_file): | |
| # Create temporary file to save the uploaded file | |
| with tempfile.NamedTemporaryFile(delete=False, suffix='.pptx') as tmp_pptx: | |
| tmp_pptx.write(uploaded_file.getvalue()) | |
| pptx_path = tmp_pptx.name | |
| # Convert PPTX path to ZIP path | |
| zip_path = os.path.splitext(pptx_path)[0] + '.zip' | |
| os.rename(pptx_path, zip_path) | |
| # Create dictionary to store audio files | |
| audio_files = {} | |
| # Create temporary directory for extraction | |
| temp_dir = tempfile.mkdtemp() | |
| with st.spinner('Extracting PPTX contents...'): | |
| # Extract the zip file to temp directory | |
| with zipfile.ZipFile(zip_path, 'r') as zip_ref: | |
| zip_ref.extractall(temp_dir) | |
| # Path to media folder | |
| media_path = os.path.join(temp_dir, 'ppt', 'media') | |
| # Check if media folder exists | |
| if os.path.exists(media_path): | |
| # Create temporary directory for converted files | |
| temp_audio_dir = tempfile.mkdtemp() | |
| # Progress bar for audio conversion | |
| progress_bar = st.progress(0) | |
| status_text = st.empty() | |
| # First count total slides with audio | |
| total_slides = 0 | |
| slide_num = 1 | |
| while True: | |
| found = False | |
| for ext in ['.mp4', '.m4a']: | |
| if os.path.exists(os.path.join(media_path, f'media{slide_num}{ext}')): | |
| total_slides += 1 | |
| found = True | |
| break | |
| if not found: | |
| break | |
| slide_num += 1 | |
| # Process audio files | |
| slide_num = 1 | |
| processed_slides = 0 | |
| while True: | |
| # Check for either .mp4 or .m4a file for current slide | |
| media_file = None | |
| for ext in ['.mp4', '.m4a']: | |
| filename = f'media{slide_num}{ext}' | |
| file_path = os.path.join(media_path, filename) | |
| if os.path.exists(file_path): | |
| media_file = file_path | |
| break | |
| if not media_file: | |
| break | |
| # Create temporary mp3 file | |
| temp_mp3 = os.path.join(temp_audio_dir, f'temp_{slide_num}.mp3') | |
| try: | |
| status_text.text(f'Converting audio from slide {slide_num}...') | |
| # Convert to mp3 using ffmpeg | |
| os.system(f'ffmpeg -i "{media_file}" -vn -acodec libmp3lame "{temp_mp3}" -loglevel quiet') | |
| # Store the temp mp3 file path in dictionary | |
| audio_files[slide_num-1] = temp_mp3 | |
| processed_slides += 1 | |
| progress_bar.progress(processed_slides / total_slides) | |
| except Exception as e: | |
| st.error(f"Error converting slide {slide_num}: {str(e)}") | |
| slide_num += 1 | |
| progress_bar.empty() | |
| status_text.empty() | |
| # Load Whisper model | |
| with st.spinner('Loading Whisper model...'): | |
| model = whisper.load_model("base") | |
| # Dictionary to store transcriptions by slide number | |
| slide_transcripts = {} | |
| # Progress bar for transcription | |
| progress_bar = st.progress(0) | |
| status_text = st.empty() | |
| # Transcribe each audio file | |
| for idx, (slide_num, audio_file) in enumerate(audio_files.items()): | |
| status_text.text(f'Transcribing slide {slide_num + 1}...') | |
| # Transcribe the audio file | |
| result = model.transcribe(audio_file) | |
| # Store transcription text for this slide | |
| slide_transcripts[slide_num + 1] = result["text"] | |
| progress_bar.progress((idx + 1) / len(audio_files)) | |
| progress_bar.empty() | |
| status_text.empty() | |
| # Clean up temporary files | |
| os.unlink(zip_path) | |
| return slide_transcripts | |
| return None | |
| def main(): | |
| st.title('Audio2Text') | |
| st.write('Upload a PowerPoint file (PPTX) to transcribe its audio content') | |
| # File uploader | |
| uploaded_file = st.file_uploader("Choose a PPTX file", type="pptx") | |
| if uploaded_file is not None: | |
| # Check file size (2GB limit) | |
| if uploaded_file.size > 2 * 1024 * 1024 * 1024: | |
| st.error("File size exceeds 2GB limit") | |
| return | |
| st.write("Processing... This may take a while depending on the number and length of audio clips.") | |
| # Process the file | |
| transcripts = process_pptx(uploaded_file) | |
| if transcripts: | |
| st.subheader("Transcription Results") | |
| for slide_num, text in sorted(transcripts.items()): | |
| st.markdown(f"**Slide {slide_num}**") | |
| st.write(text) | |
| st.markdown("---") | |
| else: | |
| st.warning("No audio content found in the PowerPoint file.") | |
| if __name__ == "__main__": | |
| main() |