def detectHumanBody():
"""
Detect one human body on an image.
"""
faceEngine = VLFaceEngine()
detector = faceEngine.createHumanDetector()
imageWithOneHuman = VLImage.load(filename=EXAMPLE_O)
pprint.pprint(
detector.detectOne(imageWithOneHuman, detectLandmarks=False).asDict())
imageWithSeveralHumans = VLImage.load(filename=EXAMPLE_SEVERAL_FACES)
pprint.pprint(
detector.detectOne(imageWithSeveralHumans,
detectLandmarks=False).asDict())
severalHumans = detector.detect([imageWithSeveralHumans],
detectLandmarks=True)
pprint.pprint([human.asDict() for human in severalHumans[0]])
imageWithoutHuman = VLImage.load(filename=EXAMPLE_WITHOUT_FACES)
pprint.pprint(
detector.detectOne(imageWithoutHuman, detectLandmarks=False) is None)
severalHumans = detector.detect(
[ImageForDetection(imageWithSeveralHumans, Rect(1, 1, 300.0, 300.0))])
pprint.pprint(severalHumans)
def test_batch_detect_by_area_with_human(self):
"""
Test batch human detection by area with human
"""
detection = self.detector.detect(images=[
ImageForDetection(image=VLIMAGE_ONE_FACE, detectArea=GOOD_AREA)
])
assert 1 == len(detection[0])
self.assertHumanDetection(detection[0], VLIMAGE_ONE_FACE)
def test_image_detection_with_transfer_option(self):
"""
Test structure image for detection
"""
detection = self.detector.detect(images=[
ImageForDetection(image=VLIMAGE_ONE_FACE, detectArea=GOOD_AREA)
])
self.assertHumanDetection(detection[0], VLIMAGE_ONE_FACE)
assert 1 == len(detection)
def test_detect_limit_bad_param(self):
"""
Test batch detection with negative limit number
"""
imageWithManyFaces = VLImage.load(filename=MANY_FACES)
self.detector.detect(images=[
ImageForDetection(image=imageWithManyFaces, detectArea=GOOD_AREA)
],
limit=-1)
def test_batch_detect_by_area_without_human(self):
"""
Test batch human detection by area without human
"""
detection = self.detector.detect(images=[
ImageForDetection(image=VLIMAGE_ONE_FACE,
detectArea=AREA_WITHOUT_FACE)
])
assert 1 == len(detection)
assert 0 == len(detection[0])
def test_image_detection_with_transfer_option(self):
"""
Test structure image for detection
"""
for detector in self.detectors:
with self.subTest(detectorType=detector.detectorType):
detection = detector.detect(images=[
ImageForDetection(image=VLIMAGE_ONE_FACE,
detectArea=GOOD_AREA)
])
self.assertFaceDetection(detection[0], VLIMAGE_ONE_FACE)
assert 1 == len(detection)
def test_batch_detect_by_area_with_face(self):
"""
Test batch face detection by area with face
"""
for detector in self.detectors:
with self.subTest(detectorType=detector.detectorType):
detection = detector.detect(images=[
ImageForDetection(image=VLIMAGE_ONE_FACE,
detectArea=GOOD_AREA)
])
assert 1 == len(detection[0])
self.assertFaceDetection(detection[0], VLIMAGE_ONE_FACE)
def test_batch_detect_by_area_without_face(self):
"""
Test batch face detection by area without face
"""
for detector in self.detectors:
with self.subTest(detectorType=detector.detectorType):
detection = detector.detect(images=[
ImageForDetection(image=VLIMAGE_ONE_FACE,
detectArea=AREA_WITHOUT_FACE)
])
assert 1 == len(detection)
assert 0 == len(detection[0])
def test_batch_detect_invalid_rectangle(self):
"""
Test batch face detection with an invalid rect
"""
for detector in self.detectors:
with self.subTest(detectorType=detector.detectorType):
with pytest.raises(LunaSDKException) as exceptionInfo:
detector.detect(images=[
ImageForDetection(image=VLIMAGE_ONE_FACE,
detectArea=Rect())
])
self.assertLunaVlError(exceptionInfo, LunaVLError.InvalidRect)
def test_batch_detect_in_area_outside_image(self):
"""
Test batch detection in area outside image
"""
for detector in self.detectors:
with self.subTest(detectorType=detector.detectorType):
with pytest.raises(LunaSDKException) as exceptionInfo:
detector.detect(images=[
ImageForDetection(image=VLIMAGE_ONE_FACE,
detectArea=OUTSIDE_AREA)
])
self.assertLunaVlError(exceptionInfo, LunaVLError.InvalidRect)
def test_detect_one_limit_bad_param(self):
"""
Test batch detection with negative limit number
"""
imageWithManyFaces = VLImage.load(filename=MANY_FACES)
for detector in self.detectors:
with self.subTest(detectorType=detector.detectorType):
with pytest.raises(TypeError) as exceptionInfo:
detector.detectOne(image=ImageForDetection(
image=imageWithManyFaces, detectArea=GOOD_AREA),
limit=-1)
assert isinstance(exceptionInfo.value,
TypeError) is True, "expected TypeError"
def test_batch_detect_invalid_rectangle(self):
"""
Test batch human detection with an invalid rect
"""
with pytest.raises(LunaSDKException) as exceptionInfo:
self.detector.detect(images=[
ImageForDetection(image=VLIMAGE_ONE_FACE, detectArea=Rect())
])
self.assertLunaVlError(exceptionInfo, LunaVLError.BatchedInternalError)
assert len(exceptionInfo.value.context
) == 1, "Expect one error in exception context"
self.assertReceivedAndRawExpectedErrors(exceptionInfo.value.context[0],
LunaVLError.InvalidRect)
def test_batch_detect_in_area_outside_image(self):
"""
Test batch detection in area outside image
"""
with pytest.raises(LunaSDKException) as exceptionInfo:
self.detector.detect(images=[
ImageForDetection(image=VLIMAGE_ONE_FACE,
detectArea=OUTSIDE_AREA)
])
self.assertLunaVlError(exceptionInfo, LunaVLError.BatchedInternalError)
assert len(exceptionInfo.value.context
) == 1, "Expect one error in exception context"
self.assertReceivedAndRawExpectedErrors(exceptionInfo.value.context[0],
LunaVLError.InvalidRect)
def test_batch_detect_invalid_rectangle(self):
"""
Test batch face detection with an invalid rect
"""
for detector in self.detectors:
with self.subTest(detectorType=detector.detectorType):
with pytest.raises(LunaSDKException) as exceptionInfo:
detector.detect(images=[
ImageForDetection(image=VLIMAGE_ONE_FACE,
detectArea=Rect())
])
self.assertLunaVlError(
exceptionInfo,
LunaVLError.BatchedInternalError.format(
"Failed validation."))
assert len(exceptionInfo.value.context
) == 1, "Expect one error in exception context"
self.assertReceivedAndRawExpectedErrors(
exceptionInfo.value.context[0],
LunaVLError.InvalidRect.format("Invalid rectangle"))
def detectFaces():
"""
Detect one face on an image.
"""
faceEngine = VLFaceEngine()
detector = faceEngine.createFaceDetector(DetectorType.FACE_DET_V1)
imageWithOneFace = VLImage.load(filename=EXAMPLE_O)
pprint.pprint(detector.detectOne(imageWithOneFace, detect5Landmarks=False, detect68Landmarks=False).asDict())
imageWithSeveralFaces = VLImage.load(filename=EXAMPLE_SEVERAL_FACES)
pprint.pprint(detector.detectOne(imageWithSeveralFaces, detect5Landmarks=False, detect68Landmarks=False).asDict())
severalFaces = detector.detect([imageWithSeveralFaces], detect5Landmarks=False, detect68Landmarks=False)
pprint.pprint([face.asDict() for face in severalFaces[0]])
imageWithoutFace = VLImage.load(filename=EXAMPLE_WITHOUT_FACES)
pprint.pprint(detector.detectOne(imageWithoutFace, detect5Landmarks=False, detect68Landmarks=False) is None)
severalFaces = detector.detect(
[ImageForDetection(imageWithSeveralFaces, Rect(1, 1, 300.0, 300.0))],
detect5Landmarks=False,
detect68Landmarks=False,
)
pprint.pprint(severalFaces)
