Audio Visualizer with Image Transition

This code is an audio visualizer that displays images based on the volume level of the audio input. It uses OpenCV (cv2) for image processing, PyAudio for audio input/output, and NumPy for numerical operations.

Prerequisites

• Python 3.x
• OpenCV (cv2) library
• NumPy library
• PyAudio library

How to Run the Code

1. Make sure you have the necessary images:

   • "caramellotus_BLK.png"
   • "caramellotus.png"
   • "prize.jpeg"

2. Install the required libraries:

pip install opencv-python pip install numpy pip install pyaudio

3. Run the code:

python audio_visualizer.py

Code Explanation

1. Image Loading and Resizing:

• The code loads three images: "caramellotus_BLK.png," "caramellotus.png," and "prize.jpeg" using the cv2.imread() function.
• The desired size for the images is specified as (4128, 2752).
• Each image is resized to the desired size using cv2.resize().

2. PyAudio Initialization:

• PyAudio is initialized using pyaudio.PyAudio().

3. Variable Initialization:

• avg_volume represents the running average of volume levels.
• alpha is a weight used to calculate the running average.
• img2_revealed is a flag indicating whether img2 is fully revealed.
• img3_timer is a timer used to display img3.

4. Audio Input Initialization:

• The microphone is opened for audio input using p.open().
• The sample rate is set to 44100, and the chunk size is set to 4096.

5. Main Loop:

• The main loop continues until the program is terminated.
• Inside the loop, a chunk of audio data is read from the microphone using stream.read().
• The volume level of the audio data is calculated using audioop.rms().
• The volume level is normalized to a percentage of the maximum volume level.
• The current volume level is added to the running average using the avg_volume formula.
• The number of rows to reveal based on the running average is calculated.
• A copy of img1 is created as new_image.
• If img2 is not fully revealed, rows of img2 are revealed based on the volume level.
• If all rows of img2 are revealed, the img3_timer is started, and img2_revealed is set to True.
• If img2 is fully revealed, img3 is displayed for a certain duration.
• The current image (new_image) is displayed using cv2.imshow().
• The running average of volume levels is decreased by a constant value in each iteration.
• The program checks for key presses, and if the user presses 'q', the program is terminated.

6. Cleanup:

• The audio input stream is stopped and closed using stream.stop_stream() and stream.close().
• PyAudio is terminated using p.terminate().
• All OpenCV windows are destroyed using cv2.destroyAllWindows().

Feel free to customize the code and images according to your preferences. Enjoy the audio visualizer!

Cleanup

To stop the program, press 'q' on the keyboard. The program will clean up the resources and close the application window.

If you encounter any issues or have any questions, please feel free to reach out.