def test_missingBestBoundary(self):
data = FMDLData()
data.load_image(self.byteArrayImage)
validResults = cropImage(data)
self.assertFalse(validResults)
self.assertEqual(data.input_image_np_cropped, [])
def test_missingInputImage(self):
data = FMDLData()
data.bestBoundary = (0.36415937542915344, 0.059263408184051514, 0.9990353584289551,\
0.8910735845565796)
validResults = cropImage(data)
self.assertFalse(validResults)
self.assertEqual(data.input_image_np_cropped, [])
def test_badInputImage2(self):
data = FMDLData()
data.input_image_np = np.zeros(100)
data.bestBoundary = (1, 0, 1, 0)
validResults = cropImage(data)
self.assertFalse(validResults)
self.assertEqual(data.input_image_np_cropped, [])
def test_badBestBoundary(self):
data = FMDLData()
data.load_image(self.byteArrayImage)
data.bestBoundary = (1, 0, 1, 0)
validResults = cropImage(data)
self.assertFalse(validResults)
self.assertEqual(len(data.input_image_np_cropped), 0)
def test_badInputImage1(self):
data = FMDLData()
data.load_image(
'tests/networksAndImages-forUnitTesting/FMDL_2018.04.30_19.11.20.png'
)
data.bestBoundary = (1, 0, 1, 0)
validResults = cropImage(data)
self.assertFalse(validResults)
self.assertEqual(data.input_image_np_cropped, [])
def test_outputs(self):
data = FMDLData()
actualCopedImage = cv2.imread(
'tests/networksAndImages-forUnitTesting/cropped_FMDL_2018.04.30_19.11.20.png'
)
data.bestBoundary = (0.36415937542915344, 0.059263408184051514, 0.9990353584289551,\
0.8910735845565796)
data.load_image(self.byteArrayImage)
validResults = cropImage(data)
self.assertTrue(validResults)
self.assertTrue(
np.allclose(data.input_image_np_cropped,
actualCopedImage,
atol=1e-04))