py pitch detect

import pyaudio
import numpy as np
import librosa

# Function to capture audio
def capture_audio(duration=3, sample_rate=22050):
    p = pyaudio.PyAudio()
    stream = p.open(format=pyaudio.paFloat32,
                    channels=1,
                    rate=sample_rate,
                    input=True,
                    frames_per_buffer=1024)

    print("Recording...")
    frames = []
    for _ in range(0, int(sample_rate / 1024 * duration)):
        data = stream.read(1024)
        frames.append(np.frombuffer(data, dtype=np.float32))

    print("Finished recording.")
    stream.stop_stream()
    stream.close()
    p.terminate()

    audio_data = np.hstack(frames)
    return audio_data, sample_rate

# Function to detect pitch
def detect_pitch(audio_data, sample_rate):
    pitches, magnitudes = librosa.core.piptrack(y=audio_data, sr=sample_rate)
    pitch = []
    for t in range(pitches.shape[1]):
        index = magnitudes[:, t].argmax()
        pitch.append(pitches[index, t])
    pitch = np.array(pitch)
    pitch = pitch[pitch > 0]  # Remove zero values
    return pitch

# Function to determine if the note is high or low
def classify_pitch(pitch):
    average_pitch = np.mean(pitch)
    if average_pitch > 300:  # Threshold for high note (in Hz)
        return "High Note"
    else:
        return "Low Note"

# Main function
def main():
    audio_data, sample_rate = capture_audio()
    pitch = detect_pitch(audio_data, sample_rate)
    note_classification = classify_pitch(pitch)
    print(f"The detected note is a {note_classification}.")

if __name__ == "__main__":
    main()