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")
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"))
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 numpy as np
import cv2
from os.path import join
import os
from retinavision.retina import Retina
from retinavision.cortex import Cortex
from retinavision import datadir, utils
R = Retina(gpu=False)
R.info()
R.loadLoc(join(datadir, "retinas", "ret50k_loc.pkl"))
R.loadCoeff(join(datadir, "retinas", "ret50k_coeff.pkl"))
#open cap and set resolution as 1280*720, the default is 640*320 which
#is too small for 50k node, so, we need change the resolution
cap = cv2.VideoCapture(0)
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 1280)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 720)
ret, campic = cap.read()
x = campic.shape[1] / 2
y = campic.shape[0] / 2
fixation = (y, x)
R.prepare(campic.shape, fixation)
ret, img = cap.read()
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
V = R.sample(img, fixation)
#back project
tight = R.backproject_last()
tight = cv2.cvtColor(tight, cv2.COLOR_BGR2RGB)
cv2.imwrite("tight.jpg", tight)