Improved GUI, fixed bugs, better visualizations
* Resolved an issue with the ESP8266 where gamma correction would be performed twice. Changed GAMMA_CORRECTION to SOFTWARE_GAMMA_CORRECTION to make a distinction between software and firmware gamma correction. The ESP8266 does firmware gamma correction and dithering, while the Raspberry Pi uses slightly more inferior software gamma correction. Changed the software gamma table to match the gamma table used in the ESP8266 firmware. * Improved the spectrum visualization by using one of the color channels to visualize the absolute value of the temporal derivative of the spectrum. Also added a feature to reject the "common mode" spectral components, which is analogous to the spectral DC component. * Signficantly improved the GUI and added a frequency adjustment slider. Adjusting the frequency range has a big impact on the visualization output. Recommend using a high frequency range (something like 4 kHz - 10 kHz) when running the scrol visualization.
This commit is contained in:
Scott Lawson
parent
82c52bdc54
commit
0e73fd1348
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@ -3,21 +3,11 @@
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#ifndef __WS2812_H__
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#define __WS2812_H__
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// Gamma Correction
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// Uses a nonlinear lookup table to correct for human perception of light.
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// When gamma correction is used, a brightness value of 2X should appear twice
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// as bright as a value of X.
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// 1 = Enable gamma correction
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// 0 = Disable gamma correction
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// Note: There seems to be a bug and you can't actually disable this
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#define WS2812_GAMMA_CORRECTION (0)
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// Temporal Dithering
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// Dithering preserves color and light when brightness is low.
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// Sometimes this can cause undesirable flickering.
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// 1 = Disable temporal dithering
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// 2, 6, 8 = Enable temporal dithering (larger values = more dithering)
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#define WS2812_DITHER_NUM (4)
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#define WS2812_USE_INTERRUPT (0) // not supported yet
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@ -3,7 +3,7 @@ from __future__ import print_function
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from __future__ import division
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import os
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DEVICE = 'pi'
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DEVICE = 'esp8266'
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"""Device used to control LED strip. Must be 'pi' or 'esp8266'"""
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if DEVICE == 'esp8266':
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@ -11,6 +11,8 @@ if DEVICE == 'esp8266':
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"""IP address of the ESP8266. Must match IP in ws2812_controller.ino"""
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UDP_PORT = 7777
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"""Port number used for socket communication between Python and ESP8266"""
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SOFTWARE_GAMMA_CORRECTION = False
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"""Set to False because the firmware handles gamma correction + dither"""
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if DEVICE == 'pi':
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LED_PIN = 18
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@ -23,11 +25,13 @@ if DEVICE == 'pi':
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"""Brightness of LED strip between 0 and 255"""
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LED_INVERT = True
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"""Set True if using an inverting logic level converter"""
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SOFTWARE_GAMMA_CORRECTION = True
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"""Set to True because Raspberry Pi doesn't use hardware dithering"""
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USE_GUI = False
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USE_GUI = True
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"""Whether or not to display a PyQtGraph GUI plot of visualization"""
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DISPLAY_FPS = False
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DISPLAY_FPS = True
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"""Whether to display the FPS when running (can reduce performance)"""
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N_PIXELS = 60
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@ -36,9 +40,6 @@ N_PIXELS = 60
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GAMMA_TABLE_PATH = os.path.join(os.path.dirname(__file__), 'gamma_table.npy')
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"""Location of the gamma correction table"""
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GAMMA_CORRECTION = True
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"""Whether to correct LED brightness for nonlinear brightness perception"""
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MIC_RATE = 44100
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"""Sampling frequency of the microphone in Hz"""
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@ -67,7 +68,7 @@ MIN_FREQUENCY = 200
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MAX_FREQUENCY = 12000
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"""Frequencies above this value will be removed during audio processing"""
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N_FFT_BINS = 9
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N_FFT_BINS = 24
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"""Number of frequency bins to use when transforming audio to frequency domain
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Fast Fourier transforms are used to transform time-domain audio data to the
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@ -77,7 +78,7 @@ frequency bins to use.
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A small number of bins reduces the frequency resolution of the visualization
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but improves amplitude resolution. The opposite is true when using a large
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number of bins.
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number of bins. More bins is not always better!
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There is no point using more bins than there are pixels on the LED strip.
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"""
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@ -39,20 +39,15 @@ def fft(data, window=None):
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return xs, ys
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samples = int(config.MIC_RATE * config.N_ROLLING_HISTORY / (2.0 * config.FPS))
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mel_y, (_, mel_x) = melbank.compute_melmat(num_mel_bands=config.N_FFT_BINS,
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freq_min=config.MIN_FREQUENCY,
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freq_max=config.MAX_FREQUENCY,
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num_fft_bands=samples,
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sample_rate=config.MIC_RATE)
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def create_mel_bank(n_history):
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def create_mel_bank():
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global samples, mel_y, mel_x
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config.N_ROLLING_HISTORY = n_history
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samples = int(config.MIC_RATE * config.N_ROLLING_HISTORY / (2.0 * config.FPS))
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mel_y, (_, mel_x) = melbank.compute_melmat(num_mel_bands=config.N_FFT_BINS,
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freq_min=config.MIN_FREQUENCY,
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freq_max=config.MAX_FREQUENCY,
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num_fft_bands=samples,
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sample_rate=config.MIC_RATE)
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samples = None
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mel_y = None
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mel_x = None
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create_mel_bank()
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Binary file not shown.
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@ -1,8 +0,0 @@
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import numpy as np
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from skimage.exposure import rescale_intensity, equalize_hist, adjust_sigmoid, equalize_adapthist
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def contrast(x, gain=100.0):
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return adjust_sigmoid(x, gain=gain/10.0)
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def equalize(x):
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return equalize_hist(x)
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@ -46,7 +46,7 @@ def _update_esp8266():
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# Truncate values and cast to integer
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pixels = np.clip(pixels, 0, 255).astype(int)
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# Optionally apply gamma correctio
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p = _gamma[pixels] if config.GAMMA_CORRECTION else np.copy(pixels)
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p = _gamma[pixels] if config.SOFTWARE_GAMMA_CORRECTION else np.copy(pixels)
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# Send UDP packets when using ESP8266
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m = []
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for i in range(config.N_PIXELS):
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@ -72,7 +72,7 @@ def _update_pi():
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# Truncate values and cast to integer
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pixels = np.clip(pixels, 0, 255).astype(long)
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# Optional gamma correction
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p = _gamma[pixels] if config.GAMMA_CORRECTION else np.copy(pixels)
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p = _gamma[pixels] if config.SOFTWARE_GAMMA_CORRECTION else np.copy(pixels)
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# Encode 24-bit LED values in 32 bit integers
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r = np.left_shift(p[0][:].astype(int), 8)
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g = np.left_shift(p[1][:].astype(int), 16)
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@ -7,9 +7,6 @@ import config
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import microphone
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import dsp
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import led
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import image
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if config.USE_GUI:
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import gui
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_time_prev = time.time() * 1000.0
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"""The previous time that the frames_per_second() function was called"""
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@ -70,11 +67,13 @@ def interpolate(y, new_length):
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r_filt = dsp.ExpFilter(np.tile(0.01, config.N_PIXELS // 2),
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alpha_decay=0.04, alpha_rise=0.4)
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alpha_decay=0.2, alpha_rise=0.99)
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g_filt = dsp.ExpFilter(np.tile(0.01, config.N_PIXELS // 2),
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alpha_decay=0.15, alpha_rise=0.99)
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alpha_decay=0.05, alpha_rise=0.3)
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b_filt = dsp.ExpFilter(np.tile(0.01, config.N_PIXELS // 2),
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alpha_decay=0.25, alpha_rise=0.99)
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alpha_decay=0.1, alpha_rise=0.5)
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common_mode = dsp.ExpFilter(np.tile(0.01, config.N_PIXELS // 2),
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alpha_decay=0.99, alpha_rise=0.01)
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p_filt = dsp.ExpFilter(np.tile(1, (3, config.N_PIXELS // 2)),
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alpha_decay=0.1, alpha_rise=0.99)
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p = np.tile(1.0, (3, config.N_PIXELS // 2))
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@ -85,17 +84,10 @@ gain = dsp.ExpFilter(np.tile(0.01, config.N_FFT_BINS),
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def visualize_scroll(y):
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"""Effect that originates in the center and scrolls outwards"""
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global p
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# y = np.copy(y)**1.5
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# Scaling adjustment
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y = np.copy(y)**(g_contrast / 50.0)
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y = np.copy(y)**2.0
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gain.update(y)
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y /= gain.value
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# Constrast adjustment
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y = image.contrast(y, gain=r_contrast)
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y *= 255.0
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# r = int(np.mean(y[:len(y) // 3]))
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# g = int(np.mean(y[len(y) // 3: 2 * len(y) // 3]))
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# b = int(np.mean(y[2 * len(y) // 3:]))
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r = int(max(y[:len(y) // 3]))
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g = int(max(y[len(y) // 3: 2 * len(y) // 3]))
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b = int(max(y[2 * len(y) // 3:]))
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@ -107,24 +99,14 @@ def visualize_scroll(y):
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p[0, 0] = r
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p[1, 0] = g
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p[2, 0] = b
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# # Contrast adjustment
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# p[0, :] = image.contrast(p[0, :] / 255.0, gain=r_contrast) * 255.0
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# p[1, :] = image.contrast(p[1, :] / 255.0, gain=g_contrast) * 255.0
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# p[2, :] = image.contrast(p[2, :] / 255.0, gain=b_contrast) * 255.0
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# Update the LED strip
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led.pixels = np.concatenate((p[:, ::-1], p), axis=1)
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led.update()
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if config.USE_GUI:
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# Update the GUI plots
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GUI.curve[0][0].setData(y=np.concatenate((p[0, :][::-1], p[0, :])))
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GUI.curve[0][1].setData(y=np.concatenate((p[1, :][::-1], p[1, :])))
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GUI.curve[0][2].setData(y=np.concatenate((p[2, :][::-1], p[2, :])))
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return np.concatenate((p[:, ::-1], p), axis=1)
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def visualize_energy(y):
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"""Effect that expands from the center with increasing sound energy"""
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global p
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y = np.copy(y)**2.0
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y = np.copy(y)
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gain.update(y)
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y /= gain.value
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# Scale by the width of the LED strip
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@ -147,53 +129,39 @@ def visualize_energy(y):
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p[0, :] = gaussian_filter1d(p[0, :], sigma=4.0)
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p[1, :] = gaussian_filter1d(p[1, :], sigma=4.0)
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p[2, :] = gaussian_filter1d(p[2, :], sigma=4.0)
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# Contrast adjustment
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p[0, :] = image.contrast(p[0, :] / 255.0, gain=r_contrast) * 255.0
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p[1, :] = image.contrast(p[1, :] / 255.0, gain=g_contrast) * 255.0
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p[2, :] = image.contrast(p[2, :] / 255.0, gain=b_contrast) * 255.0
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# Set the new pixel value
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led.pixels = np.concatenate((p[:, ::-1], p), axis=1)
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led.update()
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if config.USE_GUI:
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# Update the GUI plots
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GUI.curve[0][0].setData(y=np.concatenate((p[0, :][::-1], p[0, :])))
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GUI.curve[0][1].setData(y=np.concatenate((p[1, :][::-1], p[1, :])))
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GUI.curve[0][2].setData(y=np.concatenate((p[2, :][::-1], p[2, :])))
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return np.concatenate((p[:, ::-1], p), axis=1)
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prev_spectrum = np.tile(0.01, config.N_PIXELS // 2)
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def visualize_spectrum(y):
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"""Effect that maps the Mel filterbank frequencies onto the LED strip"""
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global prev_spectrum
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y = np.copy(interpolate(y, config.N_PIXELS // 2))
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# Blur the color channels with different strengths
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r = gaussian_filter1d(y, sigma=1.0, order=0)
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g = gaussian_filter1d(y, sigma=1.0, order=0)
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b = gaussian_filter1d(y, sigma=1.0, order=0)
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# Contrast adjustment
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r = image.contrast(r, gain=r_contrast)
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g = image.contrast(g, gain=g_contrast)
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b = image.contrast(b, gain=b_contrast)
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common_mode.update(gaussian_filter1d(y, sigma=2.0))
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diff = y - prev_spectrum
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prev_spectrum = np.copy(y)
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r = gaussian_filter1d(y, sigma=0.5) - common_mode.value
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# g = gaussian_filter1d(y, sigma=0.5) - common_mode.value
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b = gaussian_filter1d(y, sigma=0.0) - common_mode.value
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# Update temporal filters
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r_filt.update(r)
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g_filt.update(g)
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b_filt.update(b)
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# Pixel values
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pixel_r = np.concatenate((r_filt.value[::-1], r_filt.value)) * 255.0
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pixel_g = np.concatenate((g_filt.value[::-1], g_filt.value)) * 255.0
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pixel_b = np.concatenate((b_filt.value[::-1], b_filt.value)) * 255.0
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# Update the LED strip values
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led.pixels[0, :] = pixel_r
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led.pixels[1, :] = pixel_g
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led.pixels[2, :] = pixel_b
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led.update()
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if config.USE_GUI:
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# Update the GUI plots
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GUI.curve[0][0].setData(y=pixel_r)
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GUI.curve[0][1].setData(y=pixel_g)
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GUI.curve[0][2].setData(y=pixel_b)
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r = r_filt.update(r)
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# g = g_filt.update(g)
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g = np.abs(diff)
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b = b_filt.update(b)
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# Mirror the color channels for symmetric output
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pixel_r = np.concatenate((r[::-1], r))
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pixel_g = np.concatenate((g[::-1], g))
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pixel_b = np.concatenate((b[::-1], b))
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output = np.array([pixel_r, pixel_g, pixel_b]) * 255.0
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return output
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fft_plot_filter = dsp.ExpFilter(np.tile(1e-1, config.N_FFT_BINS),
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alpha_decay=0.5, alpha_rise=0.99)
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mel_gain = dsp.ExpFilter(np.tile(1e-1, config.N_FFT_BINS),
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alpha_decay=0.01, alpha_rise=0.99)
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mel_smoothing = dsp.ExpFilter(np.tile(1e-1, config.N_FFT_BINS),
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alpha_decay=0.5, alpha_rise=0.99)
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volume = dsp.ExpFilter(config.MIN_VOLUME_THRESHOLD,
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alpha_decay=0.02, alpha_rise=0.02)
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@ -231,26 +199,31 @@ def microphone_update(stream):
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YS = YS[:len(YS) // 2]
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XS = XS[:len(XS) // 2]
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# Construct a Mel filterbank from the FFT data
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YS = np.atleast_2d(np.abs(YS)).T * dsp.mel_y.T
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mel = np.atleast_2d(np.abs(YS)).T * dsp.mel_y.T
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# Scale data to values more suitable for visualization
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YS = np.sum(YS, axis=0)**2.0
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mel = YS**0.5
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mel = gaussian_filter1d(mel, sigma=1.0)
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# Normalize the Mel filterbank to make it volume independent
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mel_gain.update(np.max(mel))
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mel = np.mean(mel, axis=0)
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mel = mel**2.0
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# Gain normalization
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mel_gain.update(np.max(gaussian_filter1d(mel, sigma=1.0)))
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mel = mel / mel_gain.value
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# Visualize the filterbank output
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visualization_effect(mel)
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mel = mel_smoothing.update(mel)
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# Map filterbank output onto LED strip
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output = visualization_effect(mel)
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led.pixels = output
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led.update()
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# Plot filterbank output
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x = np.linspace(config.MIN_FREQUENCY, config.MAX_FREQUENCY, len(mel))
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mel_curve.setData(x=x, y=fft_plot_filter.update(mel))
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# Plot the color channels
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r_curve.setData(y=led.pixels[0])
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g_curve.setData(y=led.pixels[1])
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b_curve.setData(y=led.pixels[2])
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if config.USE_GUI:
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GUI.app.processEvents()
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app.processEvents()
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if config.DISPLAY_FPS:
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print('FPS {:.0f} / {:.0f}'.format(frames_per_second(), config.FPS))
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# Contrast adjustment values
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# Adjusting these values will change the visualization
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r_contrast = 190
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g_contrast = 143
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b_contrast = 200
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# Number of audio samples to read every time frame
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samples_per_frame = int(config.MIC_RATE / config.FPS)
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@ -258,65 +231,108 @@ samples_per_frame = int(config.MIC_RATE / config.FPS)
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# Array containing the rolling audio sample window
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y_roll = np.random.rand(config.N_ROLLING_HISTORY, samples_per_frame) / 1e16
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visualization_effect = visualize_energy
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visualization_effect = visualize_spectrum
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"""Visualization effect to display on the LED strip"""
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if __name__ == '__main__':
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if config.USE_GUI:
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import pyqtgraph as pg
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from pyqtgraph.Qt import QtGui, QtCore
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# Create GUI plot for visualizing LED strip output
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GUI = gui.GUI(width=800, height=400, title='Audio Visualization')
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GUI.add_plot('Color Channels')
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r_pen = pg.mkPen((255, 30, 30, 200), width=6)
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g_pen = pg.mkPen((30, 255, 30, 200), width=6)
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b_pen = pg.mkPen((30, 30, 255, 200), width=6)
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GUI.add_curve(plot_index=0, pen=r_pen)
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GUI.add_curve(plot_index=0, pen=g_pen)
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GUI.add_curve(plot_index=0, pen=b_pen)
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GUI.plot[0].setRange(xRange=(0, config.N_PIXELS), yRange=(-5, 275))
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GUI.curve[0][0].setData(x=range(config.N_PIXELS))
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GUI.curve[0][1].setData(x=range(config.N_PIXELS))
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GUI.curve[0][2].setData(x=range(config.N_PIXELS))
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# Add ComboBox for effect selection
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effect_list = {
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'Scroll effect': visualize_scroll,
|
||||
'Spectrum effect': visualize_spectrum,
|
||||
'Energy effect': visualize_energy
|
||||
}
|
||||
effect_combobox = pg.ComboBox(items=effect_list)
|
||||
# ComboBox event handler
|
||||
def effect_change():
|
||||
# Create GUI window
|
||||
app = QtGui.QApplication([])
|
||||
view = pg.GraphicsView()
|
||||
layout = pg.GraphicsLayout(border=(100,100,100))
|
||||
view.setCentralItem(layout)
|
||||
view.show()
|
||||
view.setWindowTitle('Visualization')
|
||||
view.resize(800,600)
|
||||
# Mel filterbank plot
|
||||
fft_plot = layout.addPlot(title='Filterbank Output', colspan=3)
|
||||
fft_plot.setRange(yRange=[-0.1, 1.2])
|
||||
fft_plot.disableAutoRange(axis=pg.ViewBox.YAxis)
|
||||
x_data = np.array(range(1, config.N_FFT_BINS + 1))
|
||||
mel_curve = pg.PlotCurveItem()
|
||||
mel_curve.setData(x=x_data, y=x_data*0)
|
||||
fft_plot.addItem(mel_curve)
|
||||
# Visualization plot
|
||||
layout.nextRow()
|
||||
led_plot = layout.addPlot(title='Visualization Output', colspan=3)
|
||||
led_plot.setRange(yRange=[-5, 260])
|
||||
led_plot.disableAutoRange(axis=pg.ViewBox.YAxis)
|
||||
# Pen for each of the color channel curves
|
||||
r_pen = pg.mkPen((255, 30, 30, 200), width=4)
|
||||
g_pen = pg.mkPen((30, 255, 30, 200), width=4)
|
||||
b_pen = pg.mkPen((30, 30, 255, 200), width=4)
|
||||
# Color channel curves
|
||||
r_curve = pg.PlotCurveItem(pen=r_pen)
|
||||
g_curve = pg.PlotCurveItem(pen=g_pen)
|
||||
b_curve = pg.PlotCurveItem(pen=b_pen)
|
||||
# Define x data
|
||||
x_data = np.array(range(1, config.N_PIXELS + 1))
|
||||
r_curve.setData(x=x_data, y=x_data*0)
|
||||
g_curve.setData(x=x_data, y=x_data*0)
|
||||
b_curve.setData(x=x_data, y=x_data*0)
|
||||
# Add curves to plot
|
||||
led_plot.addItem(r_curve)
|
||||
led_plot.addItem(g_curve)
|
||||
led_plot.addItem(b_curve)
|
||||
# Frequency range label
|
||||
freq_label = pg.LabelItem('')
|
||||
# Frequency slider
|
||||
def freq_slider_change(tick):
|
||||
minf = freq_slider.tickValue(0)**2.0 * (config.MIC_RATE / 2.0)
|
||||
maxf = freq_slider.tickValue(1)**2.0 * (config.MIC_RATE / 2.0)
|
||||
t = 'Frequency range: {:.0f} - {:.0f} Hz'.format(minf, maxf)
|
||||
freq_label.setText(t)
|
||||
config.MIN_FREQUENCY = minf
|
||||
config.MAX_FREQUENCY = maxf
|
||||
dsp.create_mel_bank()
|
||||
freq_slider = pg.TickSliderItem(orientation='bottom', allowAdd=False)
|
||||
freq_slider.addTick((config.MIN_FREQUENCY / (config.MIC_RATE / 2.0))**0.5)
|
||||
freq_slider.addTick((config.MAX_FREQUENCY / (config.MIC_RATE / 2.0))**0.5)
|
||||
freq_slider.tickMoveFinished = freq_slider_change
|
||||
freq_label.setText('Frequency range: {} - {} Hz'.format(
|
||||
config.MIN_FREQUENCY,
|
||||
config.MAX_FREQUENCY))
|
||||
# Effect selection
|
||||
active_color = '#16dbeb'
|
||||
inactive_color = '#FFFFFF'
|
||||
def energy_click(x):
|
||||
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)
|
||||
visualization_effect = visualize_energy
|
||||
energy_label.setText('Energy', color=active_color)
|
||||
scroll_label.setText('Scroll', color=inactive_color)
|
||||
spectrum_label.setText('Spectrum', color=inactive_color)
|
||||
def scroll_click(x):
|
||||
global visualization_effect
|
||||
visualization_effect = visualize_scroll
|
||||
energy_label.setText('Energy', color=inactive_color)
|
||||
scroll_label.setText('Scroll', color=active_color)
|
||||
spectrum_label.setText('Spectrum', color=inactive_color)
|
||||
def spectrum_click(x):
|
||||
global visualization_effect
|
||||
visualization_effect = visualize_spectrum
|
||||
energy_label.setText('Energy', color=inactive_color)
|
||||
scroll_label.setText('Scroll', color=inactive_color)
|
||||
spectrum_label.setText('Spectrum', color=active_color)
|
||||
# Create effect "buttons" (labels with click event)
|
||||
energy_label = pg.LabelItem('Energy')
|
||||
scroll_label = pg.LabelItem('Scroll')
|
||||
spectrum_label = pg.LabelItem('Spectrum')
|
||||
energy_label.mousePressEvent = energy_click
|
||||
scroll_label.mousePressEvent = scroll_click
|
||||
spectrum_label.mousePressEvent = spectrum_click
|
||||
energy_click(0)
|
||||
# Layout
|
||||
layout.nextRow()
|
||||
layout.addItem(freq_label, colspan=3)
|
||||
layout.nextRow()
|
||||
layout.addItem(freq_slider, colspan=3)
|
||||
layout.nextRow()
|
||||
layout.addItem(energy_label)
|
||||
layout.addItem(scroll_label)
|
||||
layout.addItem(spectrum_label)
|
||||
# Initialize LEDs
|
||||
led.update()
|
||||
# Start listening to live audio stream
|
||||
|
|
|
|||
Loading…
Reference in New Issue