def map_image(image,func):
x,y = image.size
a = kd_array.gen_array((x,y), init_elem = apply(func, [image.getpixel((0,0))]))
for i in range(x):
for j in range(y):
a[i,j] = apply(func, [image.getpixel((i,j))])
return a
def column_avg(image,band='red'):
x,y = image.size
func = eval("get_"+band)
a = kd_array.gen_array([x], init_elem = 0.0)
for i in range(x):
sum_band = 0
for j in range(y):
sum_band += func(image,i,j)
a[i] = float(sum_band)/float(y)
return a
def columns_max_spikes_red(image, band='red'):
x,y = image.size
func = eval("get_red")
green = eval("get_green")
blue = eval("get_blue")
a = kd_array.gen_array([x], init_elem = 0.0)
for i in range(x):
maximum = 0
for j in range(y):
if maximum < (func(image, i, j) - green(image,i,j) - blue(image,i,j)):
maximum = func(image, i, j)
a[i] = maximum
return a
def column_avg(image,band='red',y_scope_to=1,y_scope_from=0):
"""
Extended with scope settings for Y-axis.
"""
x,y = image.size
func = eval("get_"+band)
a = kd_array.gen_array([x], init_elem = 0.0)
for i in range(x):
sum_band = 0
from_ = int(math.ceil(y*y_scope_from))
to_ = int(math.floor(y*y_scope_to))
for j in range(from_, to_):
sum_band += func(image,i,j)
a[i] = float(sum_band)/float(to_-from_)
return a
