def main():
#Path to .aedat file
path = 'DVS_1.aedat'
#loading the values of the file
#t is the time vector
# x and y is the coordinates of the events
# p is the polarity of the event (eg.: 1 or -1)
t, x, y, p = aedatUtils.loadaerdat(path)
#time window of the frame (merging events)
tI=50000 #50 ms
totalImages = []
#get the t,p,x and y vectors and return a vector of frames agrouped in time intervals of tI
totalImages = aedatUtils.getFramesTimeBased(t,p,x,y,tI)
#config for plotting the frames
fig,axarr = plt.subplots(1)
handle = None
imageVector = []
for f in totalImages:
f = f.astype(np.uint8)
imagem = copy.deepcopy(f)
if handle is None:
handle = plt.imshow(np.dstack([f,f,f]))
else:
handle.set_data(np.dstack([f,f,f]))
plt.pause(tI/1000000)
plt.draw()
def main2():
path = 'DVS_2.aedat'
video = cv2.VideoCapture('video_2.mp4')
write_obj = cv2.VideoWriter('vid//test_video_2.mkv',
cv2.VideoWriter_fourcc(*'XVID'), 20,
(128, 128))
t, x, y, p = aedatUtils.loadaerdat(path)
tI = 35000
# tI = 28507.165275992 #for video 2
totalImages = []
totalImages = aedatUtils.getFramesTimeBased(t, p, x, y, tI)
handle = None
imageVector = []
print('-----------------------------------------')
print(len(totalImages))
print(video.get(cv2.CAP_PROP_FRAME_COUNT))
# j = np.zeros((128, 128, 3), dtype=np.uint8)
# l = video.read()[1]
# k = cv2.resize(cv2.cvtColor(l, cv2.COLOR_BGR2GRAY), (128, 128))
# for temp1 in range(len(totalImages[0])):
# for temp2 in range(len(totalImages[0][0])):
# if totalImages[0][temp1][temp2] == 0:
# j[temp1][temp2] = [k[temp1][temp2], 255, 0]
# elif totalImages[0][temp1][temp2] == 255:
# j[temp1][temp2] = [k[temp1][temp2], 0, 255]
# else:
# j[temp1][temp2] = cv2.resize(l, (128, 128))[temp1][temp2]
# print(j.shape, j.dtype, j.max(), j.min())
# print(j)
# print(k.shape, k.dtype, k.max(), k.min())
# print(k)
print('-----------------------------------------')
for f in totalImages:
ret, frame = video.read()
if ret:
# l = cv2.flip(cv2.rotate(cv2.resize(frame, (128, 128)), cv2.ROTATE_90_CLOCKWISE), 1)
mat_1 = np.array(([1, 0, 20], [0, 1, 28]), dtype=np.float32)
l = cv2.warpAffine((cv2.flip(
cv2.rotate(cv2.resize(frame, (128, 128)),
cv2.ROTATE_90_COUNTERCLOCKWISE), 0)), mat_1,
(128, 128))
j = np.zeros((128, 128, 3), dtype=np.uint8)
k = cv2.cvtColor(l, cv2.COLOR_BGR2GRAY)
for temp1 in range(len(f)):
for temp2 in range(len(f[0])):
if f[temp1][temp2] == 0:
j[temp1][temp2] = [k[temp1][temp2], 255, 0]
elif f[temp1][temp2] == 255:
j[temp1][temp2] = [k[temp1][temp2], 0, 255]
else:
j[temp1][temp2] = l[temp1][temp2]
j = cv2.fastNlMeansDenoisingColored(j, None, 10, 10, 7, 15)
cv2.imshow('Output', j)
write_obj.write(j)
if cv2.waitKey(1) & 0xff == 27:
break
# f = f.astype(np.uint8)
# imagem = copy.deepcopy(f)
# if handle is None:
# plt.subplot(121)
# plt.imshow(np.dstack([f, f, f]))
# plt.subplot(122)
# plt.imshow(cv2.flip(cv2.rotate(video.read()[1], cv2.ROTATE_90_CLOCKWISE), 1)) # for 1
# else:
# handle.set_data(np.dstack([f, f, f]))
#
# plt.pause(tI / 1000000)
# plt.draw()
write_obj.release()
cv2.destroyAllWindows()