Gurkengewuerz
/
audio-reactive-led-strip
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

Added a slider for contrast adjustment 

Added a slider and variables for adjusting the contrast of the
visualization.
This commit is contained in:
Scott Lawson 2017-01-03 19:16:45 -08:00
parent e3ebe167e8
commit 47aa7bfcdd
3 changed files with 67 additions and 8 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
python/config.py
View File

@ -67,7 +67,7 @@ MIN_FREQUENCY = 200
MAX_FREQUENCY = 12000
"""Frequencies above this value will be removed during audio processing"""
N_FFT_BINS = 15
N_FFT_BINS = 9
"""Number of frequency bins to use when transforming audio to frequency domain
Fast Fourier transforms are used to transform time-domain audio data to the

8
python/image.py Normal file
View File

@ -0,0 +1,8 @@
import numpy as np
from skimage.exposure import rescale_intensity, equalize_hist, adjust_sigmoid, equalize_adapthist
def contrast(x, gain=100.0):
return adjust_sigmoid(x, gain=gain/10.0)
def equalize(x):
return equalize_hist(x)

65
python/visualization.py
View File

@ -7,6 +7,7 @@ import config
import microphone
import dsp
import led
import image
if config.USE_GUI:
import gui
@ -75,7 +76,7 @@ g_filt = dsp.ExpFilter(np.tile(0.01, config.N_PIXELS // 2),
b_filt = dsp.ExpFilter(np.tile(0.01, config.N_PIXELS // 2),
alpha_decay=0.25, alpha_rise=0.99)
p_filt = dsp.ExpFilter(np.tile(1, (3, config.N_PIXELS // 2)),
alpha_decay=0.2, alpha_rise=0.99)
alpha_decay=0.1, alpha_rise=0.99)
p = np.tile(1.0, (3, config.N_PIXELS // 2))
gain = dsp.ExpFilter(np.tile(0.01, config.N_FFT_BINS),
alpha_decay=0.001, alpha_rise=0.99)
@ -84,21 +85,32 @@ gain = dsp.ExpFilter(np.tile(0.01, config.N_FFT_BINS),
def visualize_scroll(y):
"""Effect that originates in the center and scrolls outwards"""
global p
y = np.copy(y)**1.0
# y = np.copy(y)**1.5
# Scaling adjustment
y = np.copy(y)**(g_contrast / 50.0)
gain.update(y)
y /= gain.value
# Constrast adjustment
y = image.contrast(y, gain=r_contrast)
y *= 255.0
# r = int(np.mean(y[:len(y) // 3]))
# g = int(np.mean(y[len(y) // 3: 2 * len(y) // 3]))
# b = int(np.mean(y[2 * len(y) // 3:]))
r = int(max(y[:len(y) // 3]))
g = int(max(y[len(y) // 3: 2 * len(y) // 3]))
b = int(max(y[2 * len(y) // 3:]))
# Scrolling effect window
p = np.roll(p, 1, axis=1)
p *= 0.98
# p = gaussian_filter1d(p, sigma=0.2)
p = gaussian_filter1d(p, sigma=0.2)
# Create new color originating at the center
p[0, 0] = r
p[1, 0] = g
p[2, 0] = b
# # Contrast adjustment
# p[0, :] = image.contrast(p[0, :] / 255.0, gain=r_contrast) * 255.0
# p[1, :] = image.contrast(p[1, :] / 255.0, gain=g_contrast) * 255.0
# p[2, :] = image.contrast(p[2, :] / 255.0, gain=b_contrast) * 255.0
# Update the LED strip
led.pixels = np.concatenate((p[:, ::-1], p), axis=1)
led.update()
@ -135,6 +147,10 @@ def visualize_energy(y):
p[0, :] = gaussian_filter1d(p[0, :], sigma=4.0)
p[1, :] = gaussian_filter1d(p[1, :], sigma=4.0)
p[2, :] = gaussian_filter1d(p[2, :], sigma=4.0)
# Contrast adjustment
p[0, :] = image.contrast(p[0, :] / 255.0, gain=r_contrast) * 255.0
p[1, :] = image.contrast(p[1, :] / 255.0, gain=g_contrast) * 255.0
p[2, :] = image.contrast(p[2, :] / 255.0, gain=b_contrast) * 255.0
# Set the new pixel value
led.pixels = np.concatenate((p[:, ::-1], p), axis=1)
led.update()
@ -149,9 +165,13 @@ def visualize_spectrum(y):
"""Effect that maps the Mel filterbank frequencies onto the LED strip"""
y = np.copy(interpolate(y, config.N_PIXELS // 2))
# Blur the color channels with different strengths
r = gaussian_filter1d(y, sigma=1., order=0)
g = gaussian_filter1d(y, sigma=1., order=0)
b = gaussian_filter1d(y, sigma=1., order=0)
r = gaussian_filter1d(y, sigma=1.0, order=0)
g = gaussian_filter1d(y, sigma=1.0, order=0)
b = gaussian_filter1d(y, sigma=1.0, order=0)
# Contrast adjustment
r = image.contrast(r, gain=r_contrast)
g = image.contrast(g, gain=g_contrast)
b = image.contrast(b, gain=b_contrast)
# Update temporal filters
r_filt.update(r)
g_filt.update(g)
@ -226,6 +246,11 @@ def microphone_update(stream):
if config.DISPLAY_FPS:
print('FPS {:.0f} / {:.0f}'.format(frames_per_second(), config.FPS))
# Contrast adjustment values
# Adjusting these values will change the visualization
r_contrast = 190
g_contrast = 143
b_contrast = 200
# Number of audio samples to read every time frame
samples_per_frame = int(config.MIC_RATE / config.FPS)
@ -239,6 +264,7 @@ visualization_effect = visualize_energy
if __name__ == '__main__':
if config.USE_GUI:
import pyqtgraph as pg
from pyqtgraph.Qt import QtGui, QtCore
# Create GUI plot for visualizing LED strip output
GUI = gui.GUI(width=800, height=400, title='Audio Visualization')
GUI.add_plot('Color Channels')
@ -259,13 +285,38 @@ if __name__ == '__main__':
'Energy effect': visualize_energy
}
effect_combobox = pg.ComboBox(items=effect_list)
# ComboBox event handler
def effect_change():
global visualization_effect
visualization_effect = effect_combobox.value()
effect_combobox.setValue(visualization_effect)
effect_combobox.currentIndexChanged.connect(effect_change)
GUI.layout.addWidget(effect_combobox)
# Contrast
r_slider = QtGui.QSlider(QtCore.Qt.Horizontal)
g_slider = QtGui.QSlider(QtCore.Qt.Horizontal)
b_slider = QtGui.QSlider(QtCore.Qt.Horizontal)
r_slider.setRange(0, 200)
g_slider.setRange(0, 200)
b_slider.setRange(0, 200)
# Slider event handler
def adjust_contrast():
global r_contrast, g_contrast, b_contrast
r_contrast = r_slider.value()
g_contrast = g_slider.value()
b_contrast = b_slider.value()
print(r_contrast, g_contrast, b_contrast)
r_slider.valueChanged.connect(adjust_contrast)
g_slider.valueChanged.connect(adjust_contrast)
b_slider.valueChanged.connect(adjust_contrast)
# Set initial contrast
r_slider.setValue(100)
g_slider.setValue(100)
b_slider.setValue(100)
adjust_contrast()
GUI.layout.addWidget(r_slider)
GUI.layout.addWidget(g_slider)
GUI.layout.addWidget(b_slider)
# Initialize LEDs
led.update()
# Start listening to live audio stream