def detectFaces():
"""
Redetect faces on images.
"""
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())
detection = detector.detectOne(imageWithOneFace,
detect5Landmarks=False,
detect68Landmarks=False)
pprint.pprint(detector.redetectOne(image=imageWithOneFace, bBox=detection))
pprint.pprint(
detector.redetectOne(image=imageWithOneFace,
bBox=detection.boundingBox.rect))
imageWithSeveralFaces = VLImage.load(filename=EXAMPLE_SEVERAL_FACES)
severalFaces = detector.detect([imageWithSeveralFaces],
detect5Landmarks=False,
detect68Landmarks=False)
pprint.pprint(
detector.redetect(images=[
ImageForRedetection(
imageWithSeveralFaces,
[face.boundingBox.rect for face in severalFaces[0]]),
ImageForRedetection(imageWithOneFace,
[detection.boundingBox.rect]),
ImageForRedetection(imageWithOneFace, [Rect(0, 0, 1, 1)]),
]))
def test_batch_redetect_invalid_rectangle(self):
"""
Test batch re-detection with an invalid rect
"""
for detector in self.detectors:
with self.subTest(detectorType=detector.detectorType):
with pytest.raises(LunaSDKException) as exceptionInfo:
detector.redetect(images=[
ImageForRedetection(image=VLIMAGE_ONE_FACE,
bBoxes=[INVALID_RECT]),
ImageForRedetection(image=VLIMAGE_ONE_FACE,
bBoxes=[Rect(0, 0, 100, 100)]),
])
self.assertLunaVlError(
exceptionInfo,
LunaVLError.BatchedInternalError.format(
"Failed validation."))
assert len(exceptionInfo.value.context
) == 2, "Expect two error in exception context"
self.assertReceivedAndRawExpectedErrors(
exceptionInfo.value.context[0],
LunaVLError.InvalidRect.format("Invalid rectangle"))
self.assertReceivedAndRawExpectedErrors(
exceptionInfo.value.context[1],
LunaVLError.Ok.format("Ok"))
def detectHumans():
"""
Redetect human body on images.
"""
faceEngine = VLFaceEngine()
detector = faceEngine.createHumanDetector()
imageWithOneHuman = VLImage.load(filename=EXAMPLE_O)
detection = detector.detectOne(imageWithOneHuman, detectLandmarks=False)
pprint.pprint(detector.redetectOne(image=imageWithOneHuman,
bBox=detection))
pprint.pprint(
detector.redetectOne(image=imageWithOneHuman,
bBox=detection.boundingBox.rect))
imageWithSeveralHumans = VLImage.load(filename=EXAMPLE_SEVERAL_FACES)
severalHumans = detector.detect([imageWithSeveralHumans],
detectLandmarks=False)
pprint.pprint(
detector.redetect(images=[
ImageForRedetection(
imageWithSeveralHumans,
[human.boundingBox.rect for human in severalHumans[0]]),
ImageForRedetection(imageWithOneHuman,
[detection.boundingBox.rect]),
ImageForRedetection(imageWithOneHuman, [Rect(0, 0, 1, 1)]),
]))
def test_redetect_invalid_rectangle(self):
"""
Test batch re-detection with an invalid rect
"""
with pytest.raises(LunaSDKException) as exceptionInfo:
self.detector.redetect(images=[
ImageForRedetection(image=VLIMAGE_ONE_FACE,
bBoxes=[INVALID_RECT]),
ImageForRedetection(image=VLIMAGE_ONE_FACE,
bBoxes=[Rect(0, 0, 100, 100)]),
])
self.assertLunaVlError(exceptionInfo, LunaVLError.InvalidRect)
def test_rect_float(self):
"""
Test re-detection with an invalid rect
"""
for detector in self.detectors:
with self.subTest(detectorType=detector.detectorType):
detector.redetect(images=[ImageForRedetection(image=VLIMAGE_ONE_FACE, bBoxes=[ERROR_CORE_RECT])])
def test_match_redetect_one_image(self):
"""
Test match of values at different re-detections (redetectOne and redetect) with one image
"""
for image in (VLIMAGE_ONE_FACE, VLIMAGE_SMALL):
for detector in self.detectors:
with self.subTest(detectorType=detector.detectorType):
if detector.detectorType.name == "FACE_DET_V3":
self.skipTest("Skip for FaceDetV3. Different value")
continue
bBoxRect = detector.detectOne(image=image).boundingBox.rect
redetectOne = detector.redetectOne(image=image,
bBox=bBoxRect,
detect68Landmarks=True)
batchRedetect = detector.redetect(images=[
ImageForRedetection(image=image, bBoxes=[bBoxRect])
] * 3,
detect68Landmarks=True)
for redetect in batchRedetect:
for face in redetect:
assert face.boundingBox.asDict(
) == redetectOne.boundingBox.asDict()
assert face.landmarks5.asDict(
) == redetectOne.landmarks5.asDict()
assert face.landmarks68.asDict(
) == redetectOne.landmarks68.asDict()
def test_batch_redetect_in_area_outside_image(self):
"""
Test batch re-detection in area outside image
"""
for detector in self.detectors:
with self.subTest(detectorType=detector.detectorType):
if detector.detectorType.name == "FACE_DET_V3":
redetect = detector.redetect(
images=[ImageForRedetection(image=VLIMAGE_ONE_FACE, bBoxes=[OUTSIDE_AREA])]
)
self.assertFaceDetection(redetect[0], VLIMAGE_ONE_FACE)
else:
redetect = detector.redetect(
images=[ImageForRedetection(image=VLIMAGE_ONE_FACE, bBoxes=[OUTSIDE_AREA])]
)
assert redetect[0][0] is None
def test_batch_redetect_in_area_outside_image(self):
"""
Test batch re-detection in area outside image
"""
redetect = self.detector.redetect(images=[
ImageForRedetection(image=VLIMAGE_ONE_FACE, bBoxes=[OUTSIDE_AREA])
])
self.assertHumanDetection(redetect[0], VLIMAGE_ONE_FACE)
def test_rect_float(self):
"""
Test re-detection with an invalid rect
"""
self.detector.redetect(images=[
ImageForRedetection(image=VLIMAGE_ONE_FACE,
bBoxes=[ERROR_CORE_RECT])
])
def test_redetect_invalid_rectangle(self):
"""
Test batch re-detection with an invalid rect
"""
with pytest.raises(LunaSDKException) as exceptionInfo:
self.detector.redetect(images=[
ImageForRedetection(image=VLIMAGE_ONE_FACE,
bBoxes=[INVALID_RECT]),
ImageForRedetection(image=VLIMAGE_ONE_FACE,
bBoxes=[Rect(0, 0, 100, 100)]),
])
self.assertLunaVlError(exceptionInfo, LunaVLError.BatchedInternalError)
assert len(exceptionInfo.value.context
) == 2, "Expect two errors in exception context"
self.assertReceivedAndRawExpectedErrors(exceptionInfo.value.context[0],
LunaVLError.InvalidRect)
self.assertReceivedAndRawExpectedErrors(exceptionInfo.value.context[1],
LunaVLError.Ok)
def test_rect_float(self):
"""
Test re-detection with an invalid rect
"""
with pytest.raises(LunaSDKException) as exceptionInfo:
self.detector.redetect(images=[
ImageForRedetection(image=VLIMAGE_ONE_FACE,
bBoxes=[ERROR_CORE_RECT])
])
self.assertLunaVlError(exceptionInfo, LunaVLError.BatchedInternalError)
def test_batch_redetect_with_one_human(self):
"""
Test batch re-detection with one human image
"""
detection = self.detector.detectOne(image=VLIMAGE_ONE_FACE)
redetect = self.detector.redetect(images=[
ImageForRedetection(image=VLIMAGE_ONE_FACE,
bBoxes=[detection.boundingBox.rect])
])[0]
self.assertHumanDetection(redetect, VLIMAGE_ONE_FACE)
def test_batch_redetect(self):
"""
Test re-detection batch of images
"""
detectSeveral = self.detector.detect(
images=[VLIMAGE_ONE_FACE, VLIMAGE_SEVERAL_FACE])
redetect = self.detector.redetect(images=[
ImageForRedetection(
image=VLIMAGE_SEVERAL_FACE,
bBoxes=[human.boundingBox.rect for human in detectSeveral[1]]),
ImageForRedetection(image=VLIMAGE_ONE_FACE,
bBoxes=[detectSeveral[0][0].boundingBox.rect]),
])
assert 2 == len(redetect)
self.assertHumanDetection(redetect[0], VLIMAGE_SEVERAL_FACE)
self.assertHumanDetection(redetect[1], VLIMAGE_ONE_FACE)
assert 5 == len(redetect[0])
assert 1 == len(redetect[1])
def test_batch_redetect(self):
"""
Test re-detection batch of images
"""
for detector in self.detectors:
with self.subTest(detectorType=detector.detectorType):
detectSeveral = detector.detect(images=[VLIMAGE_ONE_FACE, VLIMAGE_SEVERAL_FACE])
redetect = detector.redetect(
images=[
ImageForRedetection(
image=VLIMAGE_SEVERAL_FACE, bBoxes=[face.boundingBox.rect for face in detectSeveral[1]]
),
ImageForRedetection(image=VLIMAGE_ONE_FACE, bBoxes=[detectSeveral[0][0].boundingBox.rect]),
]
)
self.assertFaceDetection(redetect[0], VLIMAGE_SEVERAL_FACE)
self.assertFaceDetection(redetect[1], VLIMAGE_ONE_FACE)
assert 2 == len(redetect)
assert 5 == len(redetect[0])
assert 1 == len(redetect[1])
def test_batch_redetect_with_one_face(self):
"""
Test batch re-detection with one face image
"""
for detector in self.detectors:
with self.subTest(detectorType=detector.detectorType):
detection = detector.detectOne(image=VLIMAGE_ONE_FACE)
redetect = detector.redetect(
images=[ImageForRedetection(image=VLIMAGE_ONE_FACE, bBoxes=[detection.boundingBox.rect])]
)[0]
self.assertFaceDetection(redetect, VLIMAGE_ONE_FACE)
def test_redetect_by_area_without_face(self):
"""
Test re-detection by area without face
"""
for detector in self.detectors:
with self.subTest(detectorType=detector.detectorType):
redetectOne = detector.redetectOne(image=VLIMAGE_ONE_FACE, bBox=Rect(0, 0, 100, 100))
redetect = detector.redetect(
images=[ImageForRedetection(image=VLIMAGE_ONE_FACE, bBoxes=[Rect(0, 0, 100, 100)])]
)[0][0]
assert redetectOne is None, "excepted None but found {}".format(redetectOne)
assert redetect is None, "excepted None but found {}".format(redetectOne)
def test_redetect_by_area_without_human(self):
"""
Test re-detection by area without human
"""
redetectOne = self.detector.redetectOne(image=VLIMAGE_ONE_FACE,
bBox=Rect(0, 0, 100, 100))
redetect = self.detector.redetect(images=[
ImageForRedetection(image=VLIMAGE_ONE_FACE,
bBoxes=[Rect(0, 0, 100, 100)])
])[0][0]
assert redetectOne is None, "excepted None but found {}".format(
redetectOne)
assert redetect is None, "excepted None but found {}".format(
redetectOne)
def test_redetect_invalid_rectangle(self):
"""
Test batch re-detection with an invalid rect
"""
for detector in self.detectors:
with self.subTest(detectorType=detector.detectorType):
with pytest.raises(LunaSDKException) as exceptionInfo:
detector.redetect(images=[
ImageForRedetection(image=VLIMAGE_ONE_FACE,
bBoxes=[INVALID_RECT])
])
self.assertLunaVlError(
exceptionInfo,
LunaVLError.BatchedInternalError.format("Unknown error"))
def test_match_redetect_one_image(self):
"""
Test match of values at different re-detections (redetectOne and redetect) with one image
"""
for image in (VLIMAGE_ONE_FACE, VLIMAGE_SMALL):
bBoxRect = self.detector.detectOne(image=image).boundingBox.rect
redetectOne = self.detector.redetectOne(image=image, bBox=bBoxRect)
batchRedetect = self.detector.redetect(
images=[ImageForRedetection(image=image, bBoxes=[bBoxRect])] *
3)
for redetect in batchRedetect:
for human in redetect:
assert human.boundingBox.asDict(
) == redetectOne.boundingBox.asDict()
async def asyncRedetectFaces():
"""
Async redetect faces on images.
"""
faceEngine = VLFaceEngine()
detector = faceEngine.createFaceDetector(DetectorType.FACE_DET_V3)
imageWithSeveralFaces = VLImage.load(filename=EXAMPLE_SEVERAL_FACES)
severalFaces = detector.detect([imageWithSeveralFaces],
detect5Landmarks=False,
detect68Landmarks=False)
detections = await detector.redetect(
images=[
ImageForRedetection(
imageWithSeveralFaces,
[face.boundingBox.rect for face in severalFaces[0]]),
],
asyncEstimate=True,
)
pprint.pprint(detections)
task1 = detector.redetect(
images=[
ImageForRedetection(imageWithSeveralFaces,
[severalFaces[0][0].boundingBox.rect]),
],
asyncEstimate=True,
)
task2 = detector.redetect(
images=[
ImageForRedetection(imageWithSeveralFaces,
[severalFaces[0][1].boundingBox.rect]),
],
asyncEstimate=True,
)
for task in (task1, task2):
pprint.pprint(task.get())
def test_rect_float(self):
"""
Test re-detection with an invalid rect
"""
for detector in self.detectors:
with self.subTest(detectorType=detector.detectorType):
with pytest.raises(LunaSDKException) as exceptionInfo:
detector.redetect(images=[
ImageForRedetection(image=VLIMAGE_ONE_FACE,
bBoxes=[ERROR_CORE_RECT])
])
self.assertLunaVlError(
exceptionInfo,
LunaVLError.ValidationFailed.format(
LunaVLError.InvalidRect.description))
def test_async_redetect_face(self):
"""
Test async redetect face
"""
detector = self.detectors[-1]
detectOne = detector.detectOne(image=VLIMAGE_ONE_FACE)
task = detector.redetectOne(image=VLIMAGE_ONE_FACE,
bBox=detectOne,
asyncEstimate=True)
self.assertAsyncEstimation(task, FaceDetection)
task = detector.redetect([
ImageForRedetection(VLIMAGE_ONE_FACE, [detectOne.boundingBox.rect])
] * 2,
asyncEstimate=True)
self.assertAsyncBatchEstimation(task, FaceDetection)
def test_async_redetect_human_body(self):
"""
Test async redetect human body
"""
detector = self.detector
detectOne = detector.detectOne(image=VLIMAGE_ONE_FACE)
task = detector.redetectOne(image=VLIMAGE_ONE_FACE,
bBox=detectOne,
asyncEstimate=True)
self.assertAsyncEstimation(task, HumanDetection)
task = detector.redetect([
ImageForRedetection(VLIMAGE_ONE_FACE, [detectOne.boundingBox.rect])
] * 2,
asyncEstimate=True)
self.assertAsyncBatchEstimation(task, HumanDetection)
def test_redetect_in_area_outside_image(self):
"""
Test re-detection face in area outside image
"""
# face on the bottom image boundary
image = VLImage.load(filename=FACE_WITH_MASK)
for detector in self.detectors:
with self.subTest(detectorType=detector.detectorType):
rect = detector.detectOne(image).boundingBox.rect
rect.width = image.rect.width - rect.x + 100
rect.height = image.rect.height - rect.y + 100
redetectOne = detector.redetectOne(image=image, bBox=rect)
self.assertFaceDetection(redetectOne, image)
redetect = detector.redetect(
images=[ImageForRedetection(image=image, bBoxes=[rect])])
self.assertFaceDetection(redetect[0], image)
def test_get_landmarks_for_batch_redetect(self):
"""
Test get and check landmark instances for batch re-detection
"""
for case in self.landmarksCases:
with self.subTest(landmarks5=case.detect5Landmarks, landmarks68=case.detect68Landmarks):
for detector in self.detectors:
with self.subTest(detectorType=detector.detectorType):
detectOne = detector.detectOne(image=VLIMAGE_ONE_FACE)
redetect = detector.redetect(
images=[ImageForRedetection(image=VLIMAGE_ONE_FACE, bBoxes=[detectOne.boundingBox.rect])],
detect68Landmarks=case.detect68Landmarks,
detect5Landmarks=case.detect5Landmarks,
)[0][0]
self.assertDetectionLandmarks(
detection=redetect, landmarks5=case.detect5Landmarks, landmarks68=case.detect68Landmarks
)