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How to create a Python application that converts video to text using IBM Watson Speech to Text service. The guide will cover obtaining the necessary credentials from IBM Cloud, setting up the Python environment, and running the application.

• Python installed on your machine
• IBM Cloud account (sign up at https://cloud.ibm.com/registration)

1. Log in to your IBM Cloud account.
2. Go to the IBM Cloud Catalog (https://cloud.ibm.com/catalog).
3. Search for "Speech to Text" in the catalog.
4. Click on the "Speech to Text" service and select a pricing plan that suits your needs.
5. Give a unique name to your Speech to Text instance, and click on "Create" to provision the service.
6. Once the service is created, navigate to the service dashboard.

1. In the Speech to Text service dashboard, click on "Service credentials" in the left-hand menu.
2. Click on "New credential" to create a new set of credentials.
3. Give a unique name to the credentials and click on "Add".

1. Open a terminal or command prompt.
2. Create a new directory for your project and navigate to it.
3. Create a new Python virtual environment by running the following command:

   python -m venv env
   

4. Activate the virtual environment:
   • On Windows:

     env\Scripts\activate
     

   • On macOS/Linux:

     source env/bin/activate
     

5. Install the required Python packages:

   pip install flask ibm-watson python-dotenv moviepy
   

1. Create a new file named app.py in your project directory.

2. Open app.py in a text editor and add the following code:

    from flask import Flask, request, jsonify, render_template
    from ibm_watson import SpeechToTextV1
    from ibm_cloud_sdk_core.authenticators import IAMAuthenticator
    import os
    from dotenv import load_dotenv
    import mimetypes
    from moviepy.editor import VideoFileClip
    from werkzeug.utils import secure_filename
   
    load_dotenv()
   
    authenticator = IAMAuthenticator(os.getenv("API_KEY"))
    speech_to_text = SpeechToTextV1(authenticator=authenticator)
    speech_to_text.set_service_url(os.getenv("SERVICE_URL"))
   
    app = Flask(__name__)
   
    # Create the "uploads" directory if it doesn't exist
    current_directory = os.getcwd()
    uploads_directory = os.path.join(current_directory, 'uploads')
    if not os.path.exists(uploads_directory):
        os.makedirs(uploads_directory)
   
   
    @app.route('/')
    def index():
        return render_template('index.html')
   
   
    @app.route('/convert', methods=['POST'])
    def convert_video_to_text():
        if 'file' not in request.files:
            return jsonify({'error': 'No file provided'}), 400
   
        video_file = request.files['file']
        file_name = video_file.filename
        content_type, _ = mimetypes.guess_type(file_name)
   
        if content_type not in ['video/mp4', 'video/quicktime']:
            return jsonify({'error': 'Invalid file format. Only MP4 and MOV videos are supported.'}), 400
   
        # Save the file
        file_path = os.path.join('uploads', secure_filename(file_name))
        video_file.save(file_path)
        print(f"File saved at: {file_path}")
        audio_path = 'audio.mp3'
   
        try:
            video = VideoFileClip(file_path)
            audio = video.audio
            audio.write_audiofile(audio_path, codec='libmp3lame')
            
            # Close the opened files
            audio.close()
            video.close()
        except Exception as e:
            return jsonify({'error': str(e)}), 500
   
        with open(audio_path, 'rb') as audio_file:
            response = speech_to_text.recognize(audio=audio_file,
                                                content_type='audio/mp3',
                                                speaker_labels=True,
                                                inactivity_timeout=-1).get_result()
   
        transcripts = [result['alternatives'][0]['transcript'] for result in response['results']]
        transcript = " ".join(x for x in transcripts)
   
        # Close the opened files
        audio_file.close()
   
        os.remove(file_path)
        os.remove(audio_path)
   
        return jsonify({'transcript': transcript})
   
   
    if __name__ == '__main__':
        app.run(debug=True, use_reloader=False)   

1. Create a new directory named templates in your project directory.

2. Inside the templates directory, create a new file named index.html.

3. Open index.html in a text editor and add the following code:

    <!doctype html>
    <html lang="en">
    <head>
        <meta charset="utf-8">
        <meta name="viewport" content="width=device-width, initial-scale=1, shrink-to-fit=no">
        <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0/css/bootstrap.min.css" integrity="sha384-Gn5384xqQ1aoWXA+058RXPxPg6fy4IWvTNh0E263XmFcJlSAwiGgFAW/dAiS6JXm" crossorigin="anonymous">
        <title>Audio to Text Converter</title>
        <style>
            .transcript-container {
                border: 1px solid #ccc;
                padding: 10px;
                margin-top: 20px;
            }
            
            .spinner {
                display: none;
                margin: 20px auto;
                width: 50px;
                height: 50px;
                border: 5px solid #f3f3f3;
                border-top: 5px solid #007bff;
                border-radius: 50%;
                animation: spin 1s linear infinite;
            }
            
            @keyframes spin {
                0% { transform: rotate(0deg); }
                100% { transform: rotate(360deg); }
            }
        </style>
    </head>
    <body>
        <div class="container">
        <h1 class="my-3">Video to Text Converter</h1>
        <form id="convert-form" enctype="multipart/form-data">
            <div class="form-group">
            <label for="file">Choose an audio file:</label>
            <input type="file" name="file" id="file" class="form-control">
            </div>
            <button type="submit" id="convert-btn" class="btn btn-primary">Convert</button>
        </form>
        
        <div class="spinner"></div>
        
        <div class="transcript-container">
            <h3>Transcript:</h3>
            <p id="transcript"></p>
        </div>
        </div>
        <script src="https://code.jquery.com/jquery-3.2.1.slim.min.js" integrity="sha384-KJ3o2DKtIkvYIK3UENzmM7KCkRr/rE9/Qpg6aAZGJwFDMVNA/GpGFF93hXpG5KkN" crossorigin="anonymous"></script>
        <script src="https://cdnjs.cloudflare.com/ajax/libs/popper.js/1.12.9/umd/popper.min.js" integrity="sha384-ApNbgh9B+Y1QKtv3Rn7W3mgPxhU9K/ScQsAP7hUibX39j7fakFPskvXusvfa0b4Q" crossorigin="anonymous"></script>
        <script src="https://maxcdn.bootstrapcdn.com/bootstrap/4.0.0/js/bootstrap.min.js" integrity="sha384-JZR6Spejh4U02d8jOt6vLEHfe/JQGiRRSQQxSfFWpi1MquVdAyjUar5+76PVCmYl" crossorigin="anonymous"></script>
        <script>
            document.addEventListener('DOMContentLoaded', () => {
                const form = document.getElementById('convert-form');
                const convertBtn = document.getElementById('convert-btn');
                const transcript = document.getElementById('transcript');
                const spinner = document.querySelector('.spinner');
                
                form.addEventListener('submit', async (e) => {
                    e.preventDefault();
                    const formData = new FormData(form);
                    
                    convertBtn.disabled = true;
                    spinner.style.display = 'block';
   
                    try {
                        const response = await fetch('/convert', {
                            method: 'POST',
                            body: formData
                        });
   
                        const data = await response.json();
                        
                        transcript.innerText = data.transcript;
                        convertBtn.disabled = false;
                        spinner.style.display = 'none';
                    } catch (error) {
                        console.error(error);
                        convertBtn.disabled = false;
                        spinner.style.display = 'none';
                    }
                });
            });
        </script>
    </body>
    </html>

1. Create a new file named .env in your project directory.

2. Open .env in a text editor and add the following lines:

   API_KEY=<your-api-key>
   SERVICE_URL=<your-service-url>
   

   Replace <your-api-key> with the API key obtained from the Speech to Text service credentials, and <your-service-url> with the URL of your Speech to Text service instance.

1. Make sure you are in the project directory and the virtual environment is activated.
2. Run the following command to start the Flask application:

   python app.py
   

3. Open a web browser and go to http://localhost:5000 to access the application.
4. Choose a video file (in MP4 format) and click the "Convert" button.
5. The application will convert the video to text using the IBM Watson Speech to Text service and display the transcript on the page.

That's it! You have successfully created a Python application that converts video to text using IBM Watson Speech to Text service. Feel free to customize the application and add more features as per your requirements.