# Example usage video_file = "MM - Samuel Decker & Lucas Mancinni.mp4" print(generate_transcript(video_file)) This example focuses on Google Cloud services for transcript generation. You would need to adapt it based on your tech stack and requirements. Implementing the full feature set described would require significant development, including front-end UI, back-end API, and possibly machine learning model training for summary generation.
audio = speech.RecognitionAudio(uri=f"gs://{bucket_name}/{video_file}") MM - Samuel Decker & Lucas Mancinni.mp4
def generate_transcript(video_file): # Create client instances speech_client = speech.SpeechClient() storage_client = storage.Client() # Example usage video_file = "MM - Samuel
# Upload video to Google Cloud Storage bucket_name = "your-bucket-name" video_path = "path/to/your/video.mp4" video_blob = storage_client.bucket(bucket_name).blob(video_file) video_blob.upload_from_filename(video_path) including front-end UI
from google.cloud import speech from google.cloud import storage import io