import collections
import time
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.animation
plt.ion()
import dvs
filename = 'dvs-ball-1ms.npz'
events = dvs.load(filename, dt_round=True)
dvs.flow(events, debug=True)
assert False
def imshow(image, ax=None):
ax = plt.gca() if ax is None else ax
# ax.imshow(image, vmin=-1, vmax=1, cmap='gray', interpolation=None)
ax.imshow(image, cmap='gray', interpolation=None)
def gaussian(x, mean=0, std=1, normalize=True):
y = np.exp(-(0.5 / std**2) * (x - mean)**2)
y /= y.sum()
return y
# def convolve_fft(x, y, axis=-1):
# X = np.fft.fft(x, axis=axis)
# Y
DEBUG = True
""" Record DVS data using the V-REP simulator. Since simulation times are not fast with the kind of time-step we want for DVS events, we use this file to simulate and record the events, so that they can be processed in another file. Using 'dvs-epuck.ttt' """ import numpy as np import matplotlib.pyplot as plt import dvs stereo = False filename = 'dvs.npz' # filename = 'dvs-epuck-stereo.npz' # filename = 'dvs-ball-1ms.npz' dvs.record(filename, stereo=stereo) # re-load events, since this scales the time events = dvs.load(filename) # plt.figure(1) # axs = [plt.subplot(1, 2, i+1) for i in range(2)] if stereo else plt.gca() # ani = dvs.show(events, axs=axs, stereo=stereo) # plt.show()
vmin=-1,
vmax=1,
cmap='gray',
interpolation='none')
ax.set_xticks([])
ax.set_yticks([])
return plt_img
rng = np.random.RandomState(3)
dt = 0.001
# --- load and filter DVS spikes
filename = 'dvs.npz'
# filename = 'dvs-ball-1ms.npz'
events = dvs.load(filename, dt_round=False)
t0 = 0.1
spikes = dvs.make_video(events, t0=t0, dt_frame=dt, tau=0)
video = dvs.make_video(events, t0=t0, dt_frame=dt, tau=0.005)
if 0:
plt.ion()
plt.figure(1)
ax = plt.gca()
img = show_image(ax, video[0])
ax.invert_yaxis()
for frame in video:
img.set_data(frame)
plt.draw()
""" Record DVS data using the V-REP simulator. Since simulation times are not fast with the kind of time-step we want for DVS events, we use this file to simulate and record the events, so that they can be processed in another file. Using 'dvs-epuck.ttt' """ import numpy as np import matplotlib.pyplot as plt import dvs stereo = False filename = 'dvs.npz' # filename = 'dvs-epuck-stereo.npz' # filename = 'dvs-ball-1ms.npz' dvs.record(filename, stereo=stereo) # re-load events, since this scales the time events = dvs.load(filename) # plt.figure(1) # axs = [plt.subplot(1, 2, i+1) for i in range(2)] if stereo else plt.gca() # ani = dvs.show(events, axs=axs, stereo=stereo) # plt.show()
import numpy as np import matplotlib.pyplot as plt plt.ion() import dvs filename = 'dvs-epuck-stereo-2.npz' events0, events1 = dvs.load(filename, dt_round=True) dvs.stereo(events0, events1, debug=True)
import numpy as np import matplotlib.pyplot as plt plt.ion() import dvs filename = 'dvs-epuck-stereo-2.npz' events0, events1 = dvs.load(filename, dt_round=True) dvs.stereo(events0, events1, debug=True)
