class CorticalMapping:
def __init__(self):
self.R = None
self.C = None
self.fixation = None
def setup_cortex(self, cortex_left, cortex_right):
#Create and prepare cortex
self.C = Cortex()
lp = join(datadir, "cortices", "{0}loc.pkl".format(cortex_left))
rp = join(datadir, "cortices", "{0}loc.pkl".format(cortex_right))
self.C.loadLocs(lp, rp)
self.C.loadCoeffs(
join(datadir, "cortices", "{0}coeff.pkl".format(cortex_left)),
join(datadir, "cortices", "{0}coeff.pkl".format(cortex_right)))
def setup_retina(self, retina_resolution):
#Create and load retina
self.R = Retina()
self.R.info()
self.R.loadLoc(
join(datadir, "retinas", "{0}_loc.pkl".format(retina_resolution)))
self.R.loadCoeff(
join(datadir, "retinas",
"{0}_coeff.pkl".format(retina_resolution)))
# img = cv2.imread("{}/examples/mario.png".format(os.getcwd()), cv2.IMREAD_COLOR)
# print(os.getcwd())
# print(type(img))
#Prepare retina
# x = img.shape[1]/2
# y = img.shape[0]/2
# print("X: ", x)
# print("Y: ", y)
# print("Retina shape: ", img.shape)
x = 120.0
y = 112.0
self.fixation = (y, x)
self.R.prepare((224, 240, 3), self.fixation)
def cortical_transform(self, im_array):
V = self.R.sample(im_array, self.fixation)
cimg = self.C.cort_img(V)
# print("Cimg type: ", type(cimg))
return cimg
def backproject_transform(self, im_array):
V = self.R.sample(im_array, self.fixation)
tight = self.R.backproject_tight_last()
# print("Cimg type: ", type(cimg))
return tight
def arr_to_img(self, img_arr, index):
cv2.imwrite(
"{}/test_images/test_image_{}.jpg".format(os.getcwd(), index),
img_arr)
def test_imagevector_integrity(self):
print(
"Testing imagevector integrity over storing in model and storing in file..."
)
cap = utils.camopen()
ret, campic = cap.read()
R = Retina()
R.info()
R.loadLoc(os.path.join(datadir, "retinas", "ret50k_loc.pkl"))
R.loadCoeff(os.path.join(datadir, "retinas", "ret50k_coeff.pkl"))
x = campic.shape[1] / 2
y = campic.shape[0] / 2
fixation = (y, x)
R.prepare(campic.shape, fixation)
ret, img = cap.read()
if ret:
V = R.sample(img, fixation)
originalvector = ImageVector(V,
framenum=1,
timestamp="HH:MM:SS.SS",
label="dummy",
fixationy=y,
fixationx=x,
retinatype="50k")
self.assertTrue(np.array_equal(V, originalvector._vector),
'Vector has been modified by storage in model')
vectors = [originalvector]
ip.saveHDF5(os.path.join("testdata", "integritytest.h5"), vectors)
newvectors = ip.loadhdf5(os.path.join("testdata", "integritytest.h5"),
None)
newvector = newvectors[0]
self.assertTrue(np.array_equal(V, originalvector._vector),
'Vector has been modified by storage in HDF5')
ip.saveCSV(os.path.join("testdata", "integritytest.csv"), vectors)
newvectors = ip.loadCsv(os.path.join("testdata", "integritytest.csv"),
None)
newvector = newvectors[0]
self.assertTrue(np.array_equal(V, originalvector._vector),
'Vector has been modified by storage in CSV')
print("Vector has not been modified by the system")
#Open webcam cap = utils.camopen() #cap is the capture object (global) ret, campic = cap.read() #Create and load retina R = Retina() R.info() R.loadLoc(join(datadir, "retinas", "ret50k_loc.pkl")) R.loadCoeff(join(datadir, "retinas", "ret50k_coeff.pkl")) #Prepare retina x = campic.shape[1] / 2 y = campic.shape[0] / 2 fixation = (y, x) R.prepare(campic.shape, fixation) #Prepare pyramid pyr_path = join(datadir, "pyramid") L = utils.loadPickle(join(pyr_path, "50K_pyr_narrow_tessellations.pkl")) L2 = utils.loadPickle(join(pyr_path, "50K_pyr_wide_tessellations.pkl")) N = utils.loadPickle(join(pyr_path, "50K_pyr_narrow_normmaps.pkl")) N2 = utils.loadPickle(join(pyr_path, "50K_pyr_wide_normmaps.pkl")) C = utils.loadPickle(join(pyr_path, "50K_pyr_narrow_coeffs.pkl")) C2 = utils.loadPickle(join(pyr_path, "50K_pyr_wide_coeffs.pkl")) narrow = Pyramid(tess=L, coeffs=C, N=N, R=R) wide = Pyramid(tess=L2, coeffs=C2, N=N2, R=R) donarrow = False dowide = False