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 visualize(BI, title, pyr, dog=False):
for i in range(len(BI[:-1])):
if dog: im = np.true_divide(BI[i], pyr.norm_maps[i])
else: im = BI[i]
cv2.namedWindow(title + str(i), cv2.WINDOW_AUTOSIZE)
cv2.imshow(title + str(i), im)
#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"))
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 startRetina():
"""Instantiates Retina object and loads necessary files"""
retina = Retina(isGPUAvailable())
retina.loadLoc(join(datadir, "retinas", "ret50k_loc.pkl"))
retina.loadCoeff(join(datadir, "retinas", "ret50k_coeff.pkl"))
return retina
import os import uuid import opencvutils import retinautils import cv2 import base64 import datetime import tornado.web import tornado.ioloop from retinavision.retina import Retina from retinavision.cortex import Cortex from retinavision import datadir from os.path import join #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) #Create and prepare cortex C = Cortex() lp = join(datadir, "cortices", "50k_Lloc_tight.pkl") rp = join(datadir, "cortices", "50k_Rloc_tight.pkl") C.loadLocs(lp, rp)
import cv2
from retinavision.retina import Retina
from retinavision.cortex import Cortex
from retinavision import datadir, utils
from os.path import join
import datetime
beforeTime = datetime.datetime.now()
# Create and load retina
R = Retina(gpu=False)
R.info()
R.loadLoc(join(datadir, "retinas", "ret50k_loc.pkl"))
R.loadCoeff(join(datadir, "retinas", "ret50k_coeff.pkl"))
# R.loadLoc(join(datadir, "retinas", "8k_loc.pkl"))
# R.loadCoeff(join(datadir, "retinas", "8k_coeff.pkl"))
# Create and prepare cortex
C = Cortex(gpu=False)
lp = join(datadir, "cortices", "50k_Lloc_tight.pkl")
rp = join(datadir, "cortices", "50k_Rloc_tight.pkl")
# lp = join(datadir, "cortices", "8k_cort_leftloc.pkl")
# rp = join(datadir, "cortices", "8k_cort_rightloc.pkl")
C.loadLocs(lp, rp)
C.loadCoeffs(join(datadir, "cortices", "50k_Lcoeff_tight.pkl"),
join(datadir, "cortices", "50k_Rcoeff_tight.pkl"))
# C.loadCoeffs(join(datadir, "cortices", "8k_cort_leftcoeff.pkl"),
# join(datadir, "cortices", "8k_cort_rightcoeff.pkl"))
# fixation=None
cap = cv2.VideoCapture(0) # cap is the capture object (global)
ret, campic = cap.read()
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")