def test_detection(self):
nat = np.asarray(Image.open('data/nat-jpg/Nikon_D70s_0_22115.JPG'))
ff1 = np.asarray(Image.open('data/ff-jpg/Nikon_D70s_0_22193.JPG'))
ff2 = np.asarray(Image.open('data/ff-jpg/Nikon_D70s_1_23220.JPG'))
nat = prnu.cut_ctr(nat, (500, 500, 3))
ff1 = prnu.cut_ctr(ff1, (500, 500, 3))
ff2 = prnu.cut_ctr(ff2, (500, 500, 3))
w = prnu.extract_single(nat)
k1 = prnu.extract_single(ff1)
k2 = prnu.extract_single(ff2)
pce1 = [{}] * 4
pce2 = [{}] * 4
for rot_idx in range(4):
cc1 = prnu.crosscorr_2d(k1, np.rot90(w, rot_idx))
pce1[rot_idx] = prnu.pce(cc1)
cc2 = prnu.crosscorr_2d(k2, np.rot90(w, rot_idx))
pce2[rot_idx] = prnu.pce(cc2)
best_pce1 = np.max([p['pce'] for p in pce1])
best_pce2 = np.max([p['pce'] for p in pce2])
self.assertGreater(best_pce1, best_pce2)
def get_PCE_from_single_img(fingerprint,img_path):
img = prnu.cut_ctr(np.asarray(Image.open(img_path)), (pix_size, pix_size, 3))
detected_fingerprint = prnu.extract_single(img)
cc2d = prnu.crosscorr_2d(fingerprint, detected_fingerprint)
PCE = prnu.pce(cc2d)['pce']
print(PCE)
return PCE
def test_pce(self):
im = np.asarray(Image.open('data/prnu1.jpg'))[:500, :400]
w_all = prnu.extract_single(im)
y_os, x_os = 5, 8
w_cut = w_all[y_os:, x_os:]
cc1 = prnu.crosscorr_2d(w_cut, w_all)
cc2 = prnu.crosscorr_2d(w_all, w_cut)
pce1 = prnu.pce(cc1)
pce2 = prnu.pce(cc2)
self.assertSequenceEqual(
pce1['peak'], (im.shape[0] - y_os - 1, im.shape[1] - x_os - 1))
self.assertTrue(np.allclose(pce1['pce'], 134611.58644973233))
self.assertSequenceEqual(pce2['peak'], (y_os - 1, x_os - 1))
self.assertTrue(np.allclose(pce2['pce'], 134618.03404934643))
def test_crosscorr2d(self):
im = np.asarray(Image.open('data/prnu1.jpg'))[:1000, :800]
w_all = prnu.extract_single(im)
y_os, x_os = 300, 150
w_cut = w_all[y_os:, x_os:]
cc = prnu.crosscorr_2d(w_cut, w_all)
max_idx = np.argmax(cc.flatten())
max_y, max_x = np.unravel_index(max_idx, cc.shape)
peak_y = cc.shape[0] - 1 - max_y
peak_x = cc.shape[1] - 1 - max_x
peak_height = cc[max_y, max_x]
self.assertSequenceEqual((peak_y, peak_x), (y_os, x_os))
self.assertTrue(np.allclose(peak_height, 666995.0))
def test_extract(self):
im1 = np.array(Image.open('data/camera.jpg'))[:400, :500]
w = prnu.extract_single(im1)
self.assertSequenceEqual(w.shape, im1.shape[:2])