app.py

from flask import Flask, request, render_template, send_file, jsonify
import os
import threading
from moviepy.editor import VideoFileClip, AudioFileClip
import librosa
import soundfile as sf
import noisereduce as nr
from scipy.io import wavfile
import numpy as np

app = Flask(__name__)
app.config['UPLOAD_FOLDER'] = 'uploads'
app.config['PROCESSED_FOLDER'] = 'processed'

progress_data = {}
processing_lock = threading.Lock()

# Ensure upload and processed folders exist
os.makedirs(app.config['UPLOAD_FOLDER'], exist_ok=True)
os.makedirs(app.config['PROCESSED_FOLDER'], exist_ok=True)

@app.route('/')
def index():
    return render_template('index.html')

@app.route('/upload', methods=['POST'])
def upload():
    if 'video' not in request.files:
        return jsonify({"error": "No file uploaded"}), 400

    file = request.files['video']
    if file.filename == '':
        return jsonify({"error": "No file selected"}), 400

    # Save the uploaded file
    file_path = os.path.join(app.config['UPLOAD_FOLDER'], file.filename)
    file.save(file_path)

    # Process the video
    output_path = os.path.join(app.config['PROCESSED_FOLDER'], f"cleaned_{file.filename}")
    
    try:
        process_video(file_path, output_path)
    except Exception as e:
        return jsonify({"error": f"Processing failed: {str(e)}"}), 500

    return jsonify({"message": "Video processed successfully", "file": f"cleaned_{file.filename}"})

@app.route('/download/<filename>')
def download(filename):
    return send_file(os.path.join(app.config['PROCESSED_FOLDER'], filename), as_attachment=True)

def process_video(input_path, output_path):
    try:
        # Load the video safely
        video = VideoFileClip(input_path, fps_source="fps")
        audio = video.audio

        # Extract audio
        temp_audio = "temp_audio.wav"
        audio.write_audiofile(temp_audio, fps=44100)

        # Load the audio file for noise reduction
        rate, data = wavfile.read(temp_audio)

        # Convert data to float32 for noise reduction
        if data.dtype != np.float32:
            data = data.astype(np.float32) / np.iinfo(data.dtype).max

        # Perform noise reduction
        reduced_noise = nr.reduce_noise(y=data, sr=rate)

        # Save the cleaned audio
        cleaned_audio_path = "cleaned_audio.wav"
        wavfile.write(cleaned_audio_path, rate, (reduced_noise * np.iinfo(np.int16).max).astype(np.int16))

        # Merge the cleaned audio with the video
        cleaned_audio = AudioFileClip(cleaned_audio_path)
        final_video = video.set_audio(cleaned_audio)

        # Write output
        final_video.write_videofile(output_path, codec='libx264', audio_codec='aac')

    finally:
        # Clean up temporary files
        if os.path.exists(temp_audio):
            os.remove(temp_audio)
        if os.path.exists(cleaned_audio_path):
            os.remove(cleaned_audio_path)

if __name__ == '__main__':
    app.run(debug=True)