def video2dataset(video_id,
imin = 0, imax = 0,
jmin = 0, jmax = 0,
tmin = 0, tmax = 1000,
):
"""
Given a video_id, we create a Dataset contained a limited field of view
Grid and time axis are also defined
"""
db = labdb.LabDB()
# for a first go, just include everything
# get the window length and window height
sql = """SELECT length FROM video WHERE video_id = %d """ % video_id
rows = db.execute(sql)
win_l = rows[0][0]*1.0
sql = """SELECT height FROM video WHERE video_id = %d """ % video_id
rows = db.execute(sql)
win_h = rows[0][0]*1.0
print "length", win_l, "\nheight", win_h
nx = 1292
nz = 964
x = np.arange(0, win_l, win_l/nx, dtype=np.float32)
z = np.arange(0, win_h, win_h/nz, dtype=np.float32)
path2time = "/Volumes/HD3/video_data/%d/time.txt" % video_id
t = np.loadtxt(path2time)
dt = np.mean(np.diff(t[:,1]))
print "dt = " ,dt
#get the number of frames
sql = """SELECT num_frames FROM video WHERE video_id = %d""" % video_id
rows = db.execute(sql)
num_frames = rows[0][0]
# uniform grid
t = np.arange(0, num_frames*dt, dt, dtype=np.float32)
# select a window
# xmin, xmax -> imin, imax
# zmin, zmax -> jmin, jmax
# tmin, tmax -> nmin, nmax
# determine indices, grid defined only on range that is included
# create nc file to hold output
d = Dataset('video', 'w')
d.defineGrid(x, z, t)
# video are images of intensity
I = d.addVariable('I', np.uint8)
# Set path to the images
path = "/Volumes/HD3/video_data/%d/frame%05d.png"
widgets = [progressbar.Percentage(), ' ', progressbar.Bar(), ' ', progressbar.ETA()]
pbar = progressbar.ProgressBar(widgets=widgets, maxval=num_frames).start()
for n in range(num_frames):
pbar.update(n)
t_star = t[n]
if t_star < tmin or t_star > tmax:
continue
filename = path % (video_id, n)
if not os.path.exists(filename):
break
im = Image.open(filename)
# TODO: need to determine these from xmin, zmin, ...
box = (50, 50, 200, 300)
region = np.array(im.crop(box))
I[:, :, n] = region
pbar.finish()
return d.nc_id
