def test_badInputImage(self):
data = FMDLData()
data.input_image_np_cropped = np.zeros(100)
data.roi_roidDelineatorSize = self.test_roiDetection
data.bestBoundary = (0.36415937542915344, 0.059263408184051514,
0.9990353584289551, 0.8910735845565796)
validResults = uncropImage(data)
self.assertFalse(validResults)
self.assertEqual(len(data.roi_actualSize), 0)
def test_missingBucketBoundaryWithMatInsideInConfig(self):
data = FMDLData()
data.config = Config(
{'minObjectsRequired':[['bucket', 'matInside']]},
[('minObjectsRequired',[ [[]], [['bucket']], [['matInside']], [['matInside', 'bucket']], [['bucket','matInside']] ])])
data.matInsideBoundary = (0.3406982123851776, 0.8910735845565796, 0.059263408184051514, 1.0)
getBestBoundaryToCropWith(data)
self.assertTrue(np.allclose(data.bucketBoundary, (0.3406982123851776, 0.8910735845565796, 0.059263408184051514, 1.0), atol=1e-04))
self.assertTrue(np.allclose(data.bestBoundary, (0.3406982123851776, 0.8910735845565796, 0.059263408184051514, 1.0), atol=1e-04))
def test_missingBucketBoundaryNoMatInsideInConfig(self):
data = FMDLData()
data.config = Config(
{'minObjectsRequired':[['bucket']]},
[('minObjectsRequired',[ [[]], [['bucket']], [['matInside']], [['matInside', 'bucket']], [['bucket','matInside']] ])])
data.matInsideBoundary = (0.36415937542915344, 0.050836026668548584, 0.9990353584289551, 0.9131188988685608)
getBestBoundaryToCropWith(data)
self.assertEqual(data.bestBoundary,())
def test_badRoiBoundaryContour(self):
data = FMDLData()
data.roi_boundary_contour = np.zeros((100, 1), int)
data.config = Config(
{'minContourArea': 8000,'roiBoundaryPointsReductionFactor': 0.01, "intersectingRoiMaxIterations": 5, "intersectingRoiStepSize": 0.001,},
[('intersectingRoiStepSize', 0.00001, 0.1, 'float'),('intersectingRoiMaxIterations', 0, 100, 'integer'),('minContourArea', 10, 100000, 'integer'),('roiBoundaryPointsReductionFactor',\
0.001, 0.1, 'float'),])
validResults = getRoiBoundaryPoints(data.roi_boundary_contour)
self.assertFalse(validResults)
self.assertEqual(len(data.approximated_roi_boundary), 0)
def test_inferOnSingleImage_badInputImage(self):
data = FMDLData()
data.config = Config(
{'roiDelineatorScoreThreshold': 0.5},
[('roiDelineatorScoreThreshold', 0, 100, 'float')])
data.input_image_np_cropped = np.zeros(100)
validResult = self.roiDelineator.inferOnSingleImage(data)
self.assertFalse(validResult)
self.assertEqual(len(data.roi_roidDelineatorSize), 0)
def test_missingRoiBoundary2(self):
data = FMDLData()
data.config = Config(
{'minContourArea': 8000,'roiBoundaryPointsReductionFactor': 0.01,
"intersectingRoiMaxIterations": 5, "intersectingRoiStepSize": 0.001,},
[('intersectingRoiStepSize', 0.00001, 0.1, 'float'),
('intersectingRoiMaxIterations', 0, 100, 'integer'),
('minContourArea', 10, 100000, 'integer'),
('roiBoundaryPointsReductionFactor',0.001, 0.1, 'float'),])
areIntersecting = areRoiBoundaryPointsIntersecting([])
self.assertTrue(areIntersecting)
def test_missingApproxRoi(self):
data = FMDLData()
validResults = validateApproximatedRoiBoundary(data)
self.assertFalse(validResults)
self.assertFalse(data.valid)
def test_badPostProcessedRoi(self):
data = FMDLData()
data.postProcessed_roi_actualSize = np.zeros((100, 1), int)
data.config = Config(
{
'minContourArea': 8000,
'roiBoundaryPointsReductionFactor': 0.01
},
[('minContourArea', 10, 100000, 'integer'),('roiBoundaryPointsReductionFactor',\
0.001, 0.1, 'float'),])
validResults = getRoiContour(data)
self.assertFalse(validResults)
self.assertEqual(len(data.approximated_roi_boundary), 0)
def test_missingEffectiveWidthModifier(self):
data = FMDLData()
data.config = Config(
{
'minBoundingBoxAspectRatio': 1.5,
'maxBoundingBoxAspectRatio': 3,
'measuredBucketWidthCM': 300,
"effectiveWidthYcoordMultiplier": -0.5,
"maxDiffBetweenAbsBucketEdgeSlopes": 5
}, [
('measuredBucketWidthCM', 10, 100000, 'float'),
('minBoundingBoxAspectRatio', 0.1, 10, 'float'),
('maxBoundingBoxAspectRatio', 0.1, 10, 'float'),
('effectiveWidthYcoordMultiplier', -1, 1, 'float'),
('maxDiffBetweenAbsBucketEdgeSlopes', 0, 100, 'float'),
])
data.load_image(self.byteArrayImage)
data.bucketBoundary = (0.3406982123851776, 0.059263408184051514, 1.0,
0.8910735845565796)
data.bucketBoundary = (4, 2, 1, 3)
data.config.effectiveWidthYcoordMultiplier = None
results = getDetectedBucketWidthAndHeightInPixels(data)
self.assertEqual(results, (-1, -1, -1, ()))
def test_badBucketBoundary(self):
data = FMDLData()
data.config = Config(
{'minBoundingBoxAspectRatio':1.5,'maxBoundingBoxAspectRatio': 3,'measuredBucketWidthCM':300,"effectiveWidthYcoordMultiplier":0.5,'maxDiffBetweenAbsBucketEdgeSlopes': 3},
[
('measuredBucketWidthCM', 10, 100000, 'float'),
('minBoundingBoxAspectRatio', 0.1, 10, 'float'),
('maxBoundingBoxAspectRatio', 0.1, 10, 'float'),
('effectiveWidthYcoordMultiplier', 0, 1, 'float'),
('maxDiffBetweenAbsBucketEdgeSlopes', 0, 100, 'float'),
])
data.load_image(self.byteArrayImage)
data.bucketBoundary = (0.3406982123851776, 0.8910735845565796, 0.059263408184051514, 1.0)
validResults1 = getPixel2CmConversionFactor(data)
data.bucketBoundary = (0, -0.8910735845565796, 0, 1.0)
validResults2 = getPixel2CmConversionFactor(data)
self.assertFalse(validResults1)
self.assertFalse(validResults2)
self.assertEqual(data.pixel2CM_conversion_factor , -1)
self.assertEqual(data.bucketWidthPX, -1)
self.assertEqual(data.bucketWidthPointsXCord, [])
def test_outputs_withCase_badCase3(self):
data = FMDLData()
data.load_image(self.byteArrayImage)
data.bucketBoundary = (0.20768868923187256, 0.15239688754081726,
0.869536280632019, 0.8369340896606445)
data.caseBoundary = (0.7303502559661865, 0.27012908458709717,
0.37515637278556824, 0.19773945212364197)
data.config = Config(
{
'minBoundingBoxAspectRatio': 1,
'maxBoundingBoxAspectRatio': 3,
'measuredBucketWidthCM': 300,
"effectiveWidthYcoordMultiplier": 0.5,
"maxDiffBetweenAbsBucketEdgeSlopes": 5
}, [
('measuredBucketWidthCM', 10, 100000, 'float'),
('minBoundingBoxAspectRatio', 0.1, 10, 'float'),
('maxBoundingBoxAspectRatio', 0.1, 10, 'float'),
('effectiveWidthYcoordMultiplier', 0, 1, 'float'),
('maxDiffBetweenAbsBucketEdgeSlopes', 0, 100, 'float'),
])
detected_bucketWidth_inPixels_withCase, detected_bucketWith_inPixels_fromBucketAlone,\
detected_bucketHeight_inPixels, bucketWidthPointsXCord = getDetectedBucketWidthAndHeightInPixels(data)
self.assertAlmostEqual(detected_bucketWidth_inPixels_withCase, 438)
self.assertAlmostEqual(detected_bucketWith_inPixels_fromBucketAlone,
438)
self.assertAlmostEqual(detected_bucketHeight_inPixels, 317)
self.assertAlmostEqual(bucketWidthPointsXCord[0], 98)
self.assertAlmostEqual(bucketWidthPointsXCord[1], 536)
def test_outputs_notInteresecting2(self):
data = FMDLData()
data.approximated_roi_boundary = self.groundTruth_approximated_roi_boundary
data.config = Config(
{'minContourArea': 8000,'roiBoundaryPointsReductionFactor': 0.01,
"intersectingRoiMaxIterations": 10, "intersectingRoiStepSize": 0.001,},
[('intersectingRoiStepSize', 0.00001, 0.1, 'float'),
('intersectingRoiMaxIterations', 0, 100, 'integer'),
('minContourArea', 10, 100000, 'integer'),
('roiBoundaryPointsReductionFactor',0.001, 0.1, 'float'),])
areIntersecting = areRoiBoundaryPointsIntersecting(data.approximated_roi_boundary[:,0,:])
self.assertFalse(areIntersecting)
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))
def test_missingRoiActualSize(self):
data = FMDLData()
data.config = Config(
{
'closingKernelSize': 7,
'closingIterations': 1,
'erosionKernelSize': 7,
'erosionIterations': 1,
}, [
('closingKernelSize', 1, 20),
('closingIterations', 0, 20),
('erosionKernelSize', 1, 20),
('erosionIterations', 0, 20),
])
validResults = postProcessRoi(data)
self.assertFalse(validResults)
self.assertEqual(len(data.postProcessed_roi_actualSize), 0)
def test_png3chan(self):
data = FMDLData()
testFilePath = 'tests/networksAndImages-forUnitTesting/3Chan_FMDL_2018.04.30_19.11.20.png'
with open(testFilePath, "rb") as imageFile:
f = imageFile.read()
byteArrayImage = bytearray(f)
data.load_image(byteArrayImage)
imageToTestAgainst = np.load(
'tests/networksAndImages-forUnitTesting/png_FMDL_2018.04.30_19.11.20.npy'
)
testImHeight, testImWidth, _ = imageToTestAgainst.shape
self.assertTrue(data.is_valid_image)
self.assertEqual(data.imageWidthPx, testImWidth)
self.assertEqual(data.imageHeightPx, testImHeight)
self.assertTrue(
np.allclose(data.input_image_np, imageToTestAgainst, atol=1e-04))
def test_missingBucketBoundary(self):
data = FMDLData()
data.load_image(self.byteArrayImage)
data.config = Config(
{'minBoundingBoxAspectRatio':1.5,'maxBoundingBoxAspectRatio': 3,'measuredBucketWidthCM':300,"effectiveWidthYcoordMultiplier":0.5,'maxDiffBetweenAbsBucketEdgeSlopes': 3},
[
('measuredBucketWidthCM', 10, 100000, 'float'),
('minBoundingBoxAspectRatio', 0.1, 10, 'float'),
('maxBoundingBoxAspectRatio', 0.1, 10, 'float'),
('effectiveWidthYcoordMultiplier', 0, 1, 'float'),
('maxDiffBetweenAbsBucketEdgeSlopes', 0, 100, 'float'),
])
validResults = getPixel2CmConversionFactor(data)
self.assertFalse(validResults)
self.assertEqual(data.pixel2CM_conversion_factor , -1)
self.assertEqual(data.bucketWidthPX, -1)
self.assertEqual(data.bucketWidthPointsXCord, [])
def test_badInputImage1(self):
data = FMDLData()
data.load_image(
'tests/networksAndImages-forUnitTesting/FMDL_2018.04.30_19.11.20.png'
)
data.bucketBoundary = (1, 2, 3, 4)
data.config = Config(
{
'minBoundingBoxAspectRatio': 1.5,
'maxBoundingBoxAspectRatio': 3,
'measuredBucketWidthCM': 300,
"effectiveWidthYcoordMultiplier": 0.5,
"maxDiffBetweenAbsBucketEdgeSlopes": 5
}, [
('measuredBucketWidthCM', 10, 100000, 'float'),
('minBoundingBoxAspectRatio', 0.1, 10, 'float'),
('maxBoundingBoxAspectRatio', 0.1, 10, 'float'),
('effectiveWidthYcoordMultiplier', 0, 1, 'float'),
('maxDiffBetweenAbsBucketEdgeSlopes', 0, 100, 'float'),
])
results = getDetectedBucketWidthAndHeightInPixels(data)
self.assertEqual(results, (-1, -1, -1, ()))
def test_bucketBoundaryWithWrongAspectRatio(self):
data = FMDLData()
data.load_image(self.byteArrayImage)
data.bucketBoundary = (4, 2, 1, 3)
data.config = Config(
{
'minBoundingBoxAspectRatio': 1.5,
'maxBoundingBoxAspectRatio': 3,
'measuredBucketWidthCM': 300,
"effectiveWidthYcoordMultiplier": 0.5,
"maxDiffBetweenAbsBucketEdgeSlopes": 5
}, [
('measuredBucketWidthCM', 10, 100000, 'float'),
('minBoundingBoxAspectRatio', 0.1, 10, 'float'),
('maxBoundingBoxAspectRatio', 0.1, 10, 'float'),
('effectiveWidthYcoordMultiplier', 0, 1, 'float'),
('maxDiffBetweenAbsBucketEdgeSlopes', 0, 100, 'float'),
])
results = getDetectedBucketWidthAndHeightInPixels(data)
self.assertEqual(results, (-1, -1, -1, ()))
def test_outputs_noCase(self):
data = FMDLData()
data.load_image(self.byteArrayImage)
data.bucketBoundary = (0.36322835087776184, 0.13493812084197998, 1.0,
0.8854146003723145)
data.config = Config(
{
'minBoundingBoxAspectRatio': 1,
'maxBoundingBoxAspectRatio': 3,
'measuredBucketWidthCM': 300,
"effectiveWidthYcoordMultiplier": 0.5,
"maxDiffBetweenAbsBucketEdgeSlopes": 5
}, [
('measuredBucketWidthCM', 10, 100000, 'float'),
('minBoundingBoxAspectRatio', 0.1, 10, 'float'),
('maxBoundingBoxAspectRatio', 0.1, 10, 'float'),
('effectiveWidthYcoordMultiplier', 0, 1, 'float'),
('maxDiffBetweenAbsBucketEdgeSlopes', 0, 100, 'float'),
])
detected_bucketWidth_inPixels_withCase, detected_bucketWith_inPixels_fromBucketAlone,\
detected_bucketHeight_inPixels, bucketWidthPointsXCord = getDetectedBucketWidthAndHeightInPixels(data)
self.assertAlmostEqual(detected_bucketWidth_inPixels_withCase, 481)
self.assertAlmostEqual(detected_bucketWith_inPixels_fromBucketAlone,
481)
self.assertAlmostEqual(detected_bucketHeight_inPixels, 306)
self.assertAlmostEqual(bucketWidthPointsXCord[0], 86)
self.assertAlmostEqual(bucketWidthPointsXCord[1], 567)
def test_inferOnSingleImage_missingInputImage(self):
data = FMDLData()
validResult = self.boxDetector.inferOnSingleImage(data)
self.assertFalse(validResult)
for itm1, item2 in zip(data.bucketBoundary, ()):
self.assertAlmostEqual(itm1, item2)
self.assertAlmostEqual(data.bucketScore, -1)
for itm1, item2 in zip(data.matInsideBoundary, ()):
self.assertAlmostEqual(itm1, item2)
self.assertAlmostEqual(data.matInsideScore, -1)
def test_badInputImage(self):
data = FMDLData()
testFilePath = 'tests/networksAndImages-forUnitTesting/bad_FMDL_2018.04.30_19.11.20.png'
with open(testFilePath, "rb") as imageFile:
f = imageFile.read()
byteArrayImage = bytearray(f)
data.load_image(byteArrayImage)
data.load_image(byteArrayImage)
self.assertFalse(data.is_valid_image)
def test_badBestBoundary(self):
data = FMDLData()
data.load_image(self.byteArrayImage)
data.roi_roidDelineatorSize = self.test_roiDetection
data.bestBoundary = (1, 0, 1, 0)
validResults = uncropImage(data)
self.assertFalse(validResults)
self.assertEqual(len(data.roi_actualSize), 0)
def test_badRoidDelineatorSize(self):
data = FMDLData()
data.load_image(self.byteArrayImage)
data.roi_roidDelineatorSize = np.zeros(100)
data.bestBoundary = (0.36415937542915344, 0.059263408184051514,
0.9990353584289551, 0.8910735845565796)
validResults = uncropImage(data)
self.assertFalse(validResults)
def test_bucketBoundaryWithWrongAspectRatio(self):
data = FMDLData()
data.load_image(self.byteArrayImage)
data.bucketBoundary = (1,2,3,4)
data.config = Config(
{'minBoundingBoxAspectRatio':1.5,'maxBoundingBoxAspectRatio': 3,'measuredBucketWidthCM':300,"effectiveWidthYcoordMultiplier":0.5,'maxDiffBetweenAbsBucketEdgeSlopes': 3},
[
('measuredBucketWidthCM', 10, 100000, 'float'),
('minBoundingBoxAspectRatio', 0.1, 10, 'float'),
('maxBoundingBoxAspectRatio', 0.1, 10, 'float'),
('effectiveWidthYcoordMultiplier', 0, 1, 'float'),
('maxDiffBetweenAbsBucketEdgeSlopes', 0, 100, 'float'),
])
validResults = getPixel2CmConversionFactor(data)
self.assertFalse(validResults)
def test_outputs(self):
data = FMDLData()
data.load_image(self.byteArrayImage)
data.roi_roidDelineatorSize = self.test_roiDetection
data.bestBoundary = (0.36415937542915344, 0.059263408184051514,
0.9990353584289551, 0.8910735845565796)
validResults = uncropImage(data)
actualRoiUncropped = cv2.imread(
'tests/networksAndImages-forUnitTesting/roiActualSize_FMDL_2018.04.30_19.11.20.png'
)
actualRoiUncropped = cv2.cvtColor(actualRoiUncropped,
cv2.COLOR_BGR2GRAY)
self.assertTrue(validResults)
self.assertTrue(
np.allclose(data.roi_actualSize, actualRoiUncropped, atol=1e-04))
def test_badInputImage1(self):
data = FMDLData()
data.load_image('tests/networksAndImages-forUnitTesting/FMDL_2018.04.30_19.11.20.png')
data.bucketBoundary = (1,2,3,4)
data.config = Config(
{'minBoundingBoxAspectRatio':1.5,'maxBoundingBoxAspectRatio': 3,'measuredBucketWidthCM':300,"effectiveWidthYcoordMultiplier":0.5,'maxDiffBetweenAbsBucketEdgeSlopes': 3},
[
('measuredBucketWidthCM', 10, 100000, 'float'),
('minBoundingBoxAspectRatio', 0.1, 10, 'float'),
('maxBoundingBoxAspectRatio', 0.1, 10, 'float'),
('effectiveWidthYcoordMultiplier', 0, 1, 'float'),
('maxDiffBetweenAbsBucketEdgeSlopes', 0, 100, 'float'),
])
validResults = getPixel2CmConversionFactor(data)
self.assertFalse(validResults)
self.assertEqual(data.pixel2CM_conversion_factor , -1)
self.assertEqual(data.bucketWidthPX, -1)
self.assertEqual(data.bucketWidthPointsXCord, [])
def test_outputs(self):
data = FMDLData()
data.load_image(self.byteArrayImage)
data.bucketBoundary = (0.3406982123851776, 0.059263408184051514, 1.0, 0.8910735845565796)
data.config = Config(
{'minBoundingBoxAspectRatio':1.5,'maxBoundingBoxAspectRatio': 3,'measuredBucketWidthCM':300,"effectiveWidthYcoordMultiplier":0.5,'maxDiffBetweenAbsBucketEdgeSlopes': 3},
[
('measuredBucketWidthCM', 10, 100000, 'float'),
('minBoundingBoxAspectRatio', 0.1, 10, 'float'),
('maxBoundingBoxAspectRatio', 0.1, 10, 'float'),
('effectiveWidthYcoordMultiplier', 0, 1, 'float'),
('maxDiffBetweenAbsBucketEdgeSlopes', 0, 100, 'float'),
])
validResults = getPixel2CmConversionFactor(data)
self.assertTrue(validResults)
self.assertTrue(np.allclose(data.pixel2CM_conversion_factor, (0.5639097744360902), atol=1e-04))
self.assertAlmostEqual(data.bucketWidthPX, 532)
self.assertEqual(data.bucketWidthPointsXCord[0], 38)
self.assertEqual(data.bucketWidthPointsXCord[1], 570)