def test_subtract(self):
"""Expectation: subtract one number from another using C++ lambda function"""
with self.subTest("Testing subtract() using ints"):
computed = utils.subtract(self.i3, self.i4)
self.assertIsInstance(computed, int)
self.assertEqual(computed, int(3 - 4))
with self.subTest("Testing subtract() using floats"):
computed = utils.subtract(self.f3, self.f4)
self.assertIsInstance(computed, float)
self.assertEqual(computed, self.f3 - self.f4)
def length(frames, amount_used=.1):
"""
Feature based on the average distance each finger moves in the gesture
"""
num_frames = len(frames)
num_used = int(amount_used * num_frames)
firsts = [[] for i in range(num_used)]
lasts = [[] for i in range(num_used)]
for f, first in zip(frames[0:num_used], firsts):
positions = get_positions(f)
for position in positions:
first.append(position)
for f, last in zip(frames[-num_used:], lasts):
positions = get_positions(f)
for position in positions:
last.append(position)
lengths = [
utils.norm(
utils.subtract(utils.average_position(first),
utils.average_position(last)))
for first, last in zip(firsts, lasts)
]
return lengths
def palm_position_histogram(frames, bins=8, range=(-1., 1.)):
"""
Feature based on a 3d histogram of the normalized positions of each palm
"""
length = range[1] - range[0]
bin_size = length / bins
def hround(v):
return min(bins - 1, int((v - range[0]) / bin_size))
l = list_3d(bins)
positions = []
for frame in frames:
for hand in frame.hands():
palm = hand.palm()
if palm:
p = palm.position
positions.append(p)
average_p = utils.ave_v(positions)
for index, position in enumerate(positions):
positions[index] = utils.subtract(position, average_p)
v = positions[index]
x = v.x / utils.norm(v)
y = v.y / utils.norm(v)
z = v.z / utils.norm(v)
l[hround(x)][hround(y)][hround(z)] += 1
return l
def palm_position_histogram(frames,bins = 8,range=(-1.,1.)):
"""
Feature based on a 3d histogram of the normalized positions of each palm
"""
length = range[1]-range[0]
bin_size = length/bins
def hround(v):
return min(bins-1,int((v-range[0])/bin_size))
l = list_3d(bins)
positions = []
for frame in frames:
for hand in frame.hands():
palm = hand.palm()
if palm:
p = palm.position
positions.append(p)
average_p = utils.ave_v(positions)
for index,position in enumerate(positions):
positions[index] = utils.subtract(position,average_p)
v = positions[index]
x = v.x/utils.norm(v)
y = v.y/utils.norm(v)
z = v.z/utils.norm(v)
l[hround(x)][hround(y)][hround(z)] += 1
return l
def length(frames,amount_used=.1):
"""
Returns the average distance each finger moves in the gesture
"""
num_frames = len(frames)
num_used = int(amount_used*num_frames)
firsts = [[] for i in range(num_used)]
lasts = [[] for i in range(num_used)]
for f,first in zip(frames[0:num_used],firsts):
positions = get_positions(f)
for position in positions:
first.append(position)
for f,last in zip(frames[-num_used:],lasts):
positions = get_positions(f)
for position in positions:
last.append(position)
lengths = [utils.norm(utils.subtract(utils.average_position(first),utils.average_position(last))) for first,last in zip(firsts,lasts)]
return lengths
def position_histogram(frames,bins = 4,range=(-1.,1.)):
length = range[1]-range[0]
bin_size = length/bins
def hround(v):
return min(bins-1,int((v-range[0])/bin_size))
l = list_3d(bins)
positions = []
for frame in frames:
for hand in frame.hands():
for finger in hand.fingers():
p = finger.tip().position
positions.append(p)
average_p = utils.ave_v(positions)
for index,position in enumerate(positions):
positions[index] = utils.subtract(position,average_p)
v = positions[index]
x = v.x/utils.norm(v)
y = v.y/utils.norm(v)
z = v.z/utils.norm(v)
l[hround(x)][hround(y)][hround(z)] += 1
return l
def position_histogram(frames, bins=8, range=(-1., 1.)):
length = range[1] - range[0]
bin_size = length / bins
def hround(v):
return min(bins - 1, int((v - range[0]) / bin_size))
l = list_3d(bins)
positions = []
for frame in frames:
for hand in frame.hands():
for finger in hand.fingers():
p = finger.tip().position
positions.append(p)
average_p = utils.ave_v(positions)
for index, position in enumerate(positions):
positions[index] = utils.subtract(position, average_p)
v = positions[index]
x = v.x / utils.norm(v)
y = v.y / utils.norm(v)
z = v.z / utils.norm(v)
l[hround(x)][hround(y)][hround(z)] += 1
return l
def test_subtraction(self):
assert 2 == utils.subtract(4, 2)
