def cellTLs2ctrs(cellTLs, eye_shape):
ctrs = []
for cellTL in cellTLs:
ctrs.append(bf.tl2center(bf.cell2px(cellTL), eye_shape))
return ctrs
# bf.imshow(lighter)
# test eye detection
# eye_shape = (25, 50)
# eye1_tl = (200, 480)
# eye2_tl = (195, 655)
# eye1_ctr = bf.tl2center(eye1_tl, eye_shape)
# eye2_ctr = bf.tl2center(eye2_tl, eye_shape)
# svm, scaler = createSVM(training=img, eye_centers=[eye1_ctr, eye2_ctr], eye_shape=eye_shape)
# eyes = searchForEyesSVM(img=img, svm=svm, scaler=scaler, eye_shape=eye_shape, locs=[(190, 470), (190, 650)])
# print eyes
# test video eye detection
eye1_tl = (344, 409)
eye2_tl = (348, 515)
eye_shape = (24, 48)
eye1_ctr = bf.tl2center(eye1_tl, eye_shape)
eye2_ctr = bf.tl2center(eye2_tl, eye_shape)
eyes = [eye1_ctr, eye2_ctr]
if os.path.isfile("svm.pkl"):
svm_file = open("svm.pkl", "rb")
(svm, scaler) = pickle.load(svm_file)
svm_file.close()
else:
svm, scaler = createSVM(training=img, eye_centers=eyes, eye_shape=eye_shape)
svm_file = open("svm.pkl", "wb")
pickle.dump((svm, scaler), svm_file)
svm_file.close()
trackEyes(svm=svm, scaler=scaler)
