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Enhancing Audio Visualization with Advanced Features and Effects #169

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Enhancing Audio Visualization with Advanced Features and Effects #169

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6ca7ba0
Enhancing Audio Visualization with Advanced Features and Effects
arjundontflex Jul 15, 2024
d525157
Merge branch 'main' into main
dinxsh Jul 19, 2024
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182 changes: 119 additions & 63 deletions Real-Time VU Meter.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,44 +4,41 @@
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg
import matplotlib.pyplot as plt
import soundfile as sf
import scipy.fftpack
import librosa.display
import requests
import io
from pydub import AudioSegment
import soundfile as sf
from scipy.signal import convolve

_VARS = {"window": False, "stream": False, "audioData": np.array([]), "audioBuffer": np.array([])}
# Constants and Variables
CHUNK = 1024
RATE = 44100
INTERVAL = 1
TIMEOUT = 10
NOISE_FLOOR = 1e-6
_VARS = {"window": False, "stream": False, "audioData": np.array([]), "audioBuffer": np.array([]), "mode": "VU", "channels": 1}

AppFont = "Helvetica"
sg.theme("DarkBlue3")

# Layout
layout = [
[
sg.Graph(
canvas_size=(600, 300),
graph_bottom_left=(-2, -2),
graph_top_right=(102, 102),
background_color="#809AB6",
key="graph_vu_meter",
tooltip="VU Meter"
)
],
[sg.Text("Progress:", text_color='white', font=('Helvetica', 15, 'bold')), sg.ProgressBar(100, orientation="h", size=(20, 20), key="-PROG-")],
[
sg.Button("Listen", font=AppFont, tooltip="Start listening"),
sg.Button("Pause", font=AppFont, disabled=True, tooltip="Pause listening"),
sg.Button("Resume", font=AppFont, disabled=True, tooltip="Resume listening"),
sg.Button("Stop", font=AppFont, disabled=True, tooltip="Stop listening"),
sg.Button("Save", font=AppFont, disabled=True, tooltip="Save the plot"),
sg.Button("Exit", font=AppFont, tooltip="Exit the application"),
],
[sg.Graph(canvas_size=(600, 300), graph_bottom_left=(-2, -2), graph_top_right=(102, 102), background_color="#809AB6", key="graph_audio", tooltip="Audio Visualization")],
[sg.Text("Progress:", text_color='white', font=('Helvetica', 15, 'bold')), sg.ProgressBar(100, orientation="h", size=(20, 20), key="-PROG-")],
[sg.Button("Listen", font=AppFont, tooltip="Start listening"), sg.Button("Pause", font=AppFont, disabled=True, tooltip="Pause listening"), sg.Button("Resume", font=AppFont, disabled=True, tooltip="Resume listening"), sg.Button("Stop", font=AppFont, disabled=True, tooltip="Stop listening"), sg.Button("Save", font=AppFont, disabled=True, tooltip="Save the plot"), sg.Button("Exit", font=AppFont, tooltip="Exit the application")],
[sg.Combo(["VU", "Waveform", "Spectrum", "Spectrogram"], default_value="VU", key="view_mode", tooltip="Select visualization mode"), sg.Checkbox("Echo", key="echo"), sg.Checkbox("Reverb", key="reverb"), sg.Checkbox("Stereo", key="stereo")],
[sg.Text("Stream URL:", size=(10, 1)), sg.InputText(key="stream_url", size=(40, 1)), sg.Button("Stream", font=AppFont, tooltip="Stream audio from URL")]
]

_VARS["window"] = sg.Window("Mic to VU Meter", layout, finalize=True)
graph_vu_meter = _VARS["window"]["graph_vu_meter"]
_VARS["window"] = sg.Window("Audio Visualizer", layout, finalize=True)
graph_audio = _VARS["window"]["graph_audio"]

CHUNK = 1024
RATE = 44100
INTERVAL = 1
TIMEOUT = 10
NOISE_FLOOR = 1e-6
# PyAudio Instance
pAud = pyaudio.PyAudio()

# Helper Functions
def draw_figure(canvas, figure):
figure_canvas_agg = FigureCanvasTkAgg(figure, canvas)
figure_canvas_agg.draw()
Expand All @@ -55,6 +52,8 @@ def stop():
_VARS["window"]["-PROG-"].update(0)
_VARS["window"]["Stop"].Update(disabled=True)
_VARS["window"]["Listen"].Update(disabled=False)
_VARS["window"]["Pause"].Update(disabled=True)
_VARS["window"]["Resume"].Update(disabled=True)

def pause():
if _VARS["stream"].is_active():
Expand All @@ -71,45 +70,111 @@ def resume():
def save():
folder = sg.popup_get_folder('Please select a directory to save the files')
if folder:
fig_vu_meter.savefig(f'{folder}/vu_meter.png')
sg.popup('Success', f'Image saved as {folder}/vu_meter.png')
fig_audio.savefig(f'{folder}/audio_visualization.png')
sg.popup('Success', f'Image saved as {folder}/audio_visualization.png')
sf.write(f'{folder}/output.wav', _VARS["audioBuffer"], RATE)
sg.popup('Success', f'Audio saved as {folder}/output.wav')

def callback(in_data, frame_count, time_info, status):
_VARS["audioData"] = np.frombuffer(in_data, dtype=np.int16)
_VARS["audioBuffer"] = np.append(_VARS["audioBuffer"], _VARS["audioData"])
audio_data = np.frombuffer(in_data, dtype=np.int16)
if _VARS["channels"] == 2:
audio_data = audio_data.reshape(-1, 2)
if _VARS["audioBuffer"].size == 0:
_VARS["audioBuffer"] = audio_data
else:
_VARS["audioBuffer"] = np.vstack((_VARS["audioBuffer"], audio_data))
_VARS["audioData"] = audio_data
return (in_data, pyaudio.paContinue)

def listen():
_VARS["window"]["Stop"].Update(disabled=False)
_VARS["window"]["Listen"].Update(disabled=True)
_VARS["stream"] = pAud.open(
format=pyaudio.paInt16,
channels=1,
rate=RATE,
input=True,
frames_per_buffer=CHUNK,
stream_callback=callback,
)
_VARS["window"]["Pause"].Update(disabled=False)
_VARS["window"]["Save"].Update(disabled=False)
_VARS["channels"] = 2 if _VARS["window"]["stereo"].get() else 1
_VARS["stream"] = pAud.open(format=pyaudio.paInt16, channels=_VARS["channels"], rate=RATE, input=True, frames_per_buffer=CHUNK, stream_callback=callback)
_VARS["stream"].start_stream()

fig_vu_meter, ax_vu_meter = plt.subplots()
fig_vu_meter_agg = draw_figure(graph_vu_meter.TKCanvas, fig_vu_meter)
def apply_effects(data):
if _VARS["window"]["echo"].get():
data = np.concatenate([data, data])
if _VARS["window"]["reverb"].get():
reverb_kernel = np.random.normal(size=5000)
data = convolve(data, reverb_kernel, mode='full')[:len(data)]
return data

def update_vu():
rms = np.sqrt(np.mean(np.square(_VARS["audioData"])))
vu_level = 20 * np.log10(max(rms, NOISE_FLOOR)) + 3
normalized_vu_level = max(vu_level, 0)
_VARS["window"]["-PROG-"].update(normalized_vu_level)
ax_audio.clear()
ax_audio.barh(['VU Meter'], [normalized_vu_level], color='green')
ax_audio.set_xlim(0, 80)
ax_audio.set_xlabel("Level (dB)")
ax_audio.grid(True)
fig_audio_agg.draw()

def update_waveform():
ax_audio.clear()
ax_audio.plot(_VARS["audioData"])
ax_audio.set_xlabel("Samples")
ax_audio.set_ylabel("Amplitude")
fig_audio_agg.draw()

def update_spectrum():
N = len(_VARS["audioData"])
T = 1.0 / RATE
yf = scipy.fftpack.fft(_VARS["audioData"])
xf = np.linspace(0.0, 1.0/(2.0*T), N//2)
ax_audio.clear()
ax_audio.plot(xf, 2.0/N * np.abs(yf[:N//2]))
ax_audio.set_xlabel('Frequency (Hz)')
ax_audio.set_ylabel('Amplitude')
ax_audio.grid(True)
fig_audio_agg.draw()

def update_spectrogram():
ax_audio.clear()
ax_audio.specgram(_VARS["audioData"], Fs=RATE)
ax_audio.set_xlabel('Time (s)')
ax_audio.set_ylabel('Frequency (Hz)')
fig_audio_agg.draw()

def switch_view():
mode = _VARS["window"]["view_mode"].get()
if mode == "VU":
update_vu()
elif mode == "Waveform":
update_waveform()
elif mode == "Spectrum":
update_spectrum()
elif mode == "Spectrogram":
update_spectrogram()

def stream_audio(url):
response = requests.get(url)
audio = AudioSegment.from_file(io.BytesIO(response.content))
data = np.array(audio.get_array_of_samples())
_VARS["audioBuffer"] = data
_VARS["audioData"] = data
while True:
switch_view()
if _VARS["window"].read(timeout=TIMEOUT)[0] == "Exit":
break

# Main Loop
fig_audio, ax_audio = plt.subplots()
fig_audio_agg = draw_figure(graph_audio.TKCanvas, fig_audio)

while True:
event, values = _VARS["window"].read(timeout=TIMEOUT)
if event == "Exit":
stop()
pAud.terminate()
break
if event == sg.WIN_CLOSED:
if event == "Exit" or event == sg.WIN_CLOSED:
stop()
pAud.terminate()
break
if event == "Listen":
listen()
_VARS["window"]["Save"].Update(disabled=False)
if event == "Pause":
pause()
if event == "Resume":
Expand All @@ -118,19 +183,10 @@ def listen():
stop()
if event == "Save":
save()

elif _VARS["audioData"].size != 0:
rms = np.sqrt(np.mean(np.square(_VARS["audioData"])))
vu_level = 20 * np.log10(max(rms, NOISE_FLOOR)) + 3

normalized_vu_level = max(vu_level, 0)

_VARS["window"]["-PROG-"].update(normalized_vu_level)

ax_vu_meter.clear()
ax_vu_meter.barh(['VU Meter'], [normalized_vu_level], color='green')
ax_vu_meter.set_xlim(0, 80)
ax_vu_meter.set_xlabel("Level (dB)")
ax_vu_meter.grid(True)

fig_vu_meter_agg.draw()
if event == "Stream":
stream_audio(values["stream_url"])
if event == "view_mode":
switch_view()
if _VARS["audioData"].size != 0:
_VARS["audioData"] = apply_effects(_VARS["audioData"])
switch_view()