def test_detect_by_area_one_face(self):
image = VLImage.load(filename=ONE_FACE)
area = Rect(0, 0, 100, 100)
detection = TestDetector.detector.detectOne(image=image, detectArea=area)
assert detection is None
area = Rect(100, 100, image.rect.width - 100, image.rect.height - 100)
detection = TestDetector.detector.detectOne(image=image, detectArea=area)
isinstance(detection, FaceDetection)
def test_detect_by_area_and_not(self):
image = VLImage.load(filename=ONE_FACE)
area1 = Rect(0, 0, 100, 100)
area2 = Rect(100, 100, image.rect.width - 100, image.rect.height - 100)
detections = TestDetector.detector.detect(
images=[ImageForDetection(image, area1), ImageForDetection(image, area2), image]
)
assert 3 == len(detections)
assert 0 == len(detections[0])
assert 1 == len(detections[1])
assert 1 == len(detections[1])
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 detectFaces():
"""
Redect 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, detection=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 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_detect_one_invalid_rectangle(self):
"""
Test detection of one human with an invalid rect
"""
with pytest.raises(LunaSDKException) as exceptionInfo:
self.detector.detectOne(image=VLIMAGE_ONE_FACE, detectArea=Rect())
self.assertLunaVlError(exceptionInfo, LunaVLError.InvalidRect)
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 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)
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_load_image_from_file(self):
"""
Test load image from file
"""
imageWithOneFace = VLImage.load(filename=ONE_FACE)
assert imageWithOneFace.isValid()
assert imageWithOneFace.rect == Rect(0, 0, 912, 1080)
assert imageWithOneFace.filename == "one_face.jpg"
def test_load_image_from_url(self):
"""
Test load image from url
"""
url = "https://st.kp.yandex.net/im/kadr/3/1/4/kinopoisk.ru-Keira-Knightley-3142930.jpg"
imageWithOneFace = VLImage.load(url=url)
assert imageWithOneFace.isValid()
assert imageWithOneFace.rect == Rect(0, 0, 1000, 1288)
assert imageWithOneFace.filename == url
def test_detect_one_invalid_rectangle(self):
"""
Test detection of one face with an invalid rect
"""
for detector in self.detectors:
with self.subTest(detectorType=detector.detectorType):
with pytest.raises(LunaSDKException) as exceptionInfo:
detector.detectOne(image=VLIMAGE_ONE_FACE,
detectArea=Rect())
self.assertLunaVlError(exceptionInfo, 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.InvalidRect)
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_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 checkRectAttr(defaultRect: Rect):
"""
Validate attributes of Rect
Args:
defaultRect: rect object
"""
for rectType in ("coreRectI", "coreRectF"):
assert all(
isinstance(
getattr(defaultRect.__getattribute__(rectType), f"{coordinate}"),
float if rectType == "coreRectF" else int,
)
for coordinate in ("x", "y", "height", "width")
)
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_image_initialize(self):
path = Path(ONE_FACE)
with path.open("rb") as file:
binaryBody = file.read()
img = Image.open(ONE_FACE)
npBody = np.asarray(img)
coreBody = fe.Image()
coreBody.load(ONE_FACE)
InitCase = namedtuple("InitCase", ("initType", "body"))
cases = (InitCase("bytes",
binaryBody), InitCase("numpy array", npBody),
InitCase("core", coreBody))
for case in cases:
with self.subTest(initType=case.initType):
image = VLImage(body=case.body, filename=case.initType)
assert case.initType == image.filename
assert image.isValid()
assert image.rect == Rect(0, 0, 912, 1080)
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 test_image_initialize(self):
"""
Test create VLImage with image body
"""
binaryBody = Path(ONE_FACE).read_bytes()
bytearrayBody = bytearray(binaryBody)
imageWithOneFace = Image.open(ONE_FACE)
coreBody = fe.Image()
coreBody.load(ONE_FACE)
InitCase = namedtuple("InitCase", ("initType", "body"))
cases = (
InitCase("bytes", binaryBody),
InitCase("byte array", bytearrayBody),
InitCase("core", coreBody),
InitCase("pillow img", imageWithOneFace),
)
for case in cases:
with self.subTest(initType=case.initType):
imageVl = VLImage(body=case.body, filename=case.initType)
assert imageVl.isValid()
assert case.initType == imageVl.filename
assert imageVl.rect == Rect(0, 0, 912, 1080)
def test_detect_by_bad_area(self):
image = VLImage.load(filename=ONE_FACE)
area = Rect(100, 100, image.rect.width, image.rect.height)
detections = TestDetector.detector.detectOne(image=image, detectArea=area)
from lunavl.sdk.detectors.base import BaseDetection
from lunavl.sdk.detectors.facedetector import FaceDetection, FaceDetector, Landmarks5, Landmarks68
from lunavl.sdk.detectors.humandetector import HumanDetection, HumanDetector, Landmarks17
from lunavl.sdk.faceengine.engine import DetectorType
from lunavl.sdk.image_utils.geometry import Point
from lunavl.sdk.image_utils.geometry import Rect
from lunavl.sdk.image_utils.image import VLImage
from tests.base import BaseTestClass
from tests.resources import ONE_FACE, SEVERAL_FACES, SMALL_IMAGE, BAD_IMAGE, LARGE_IMAGE
VLIMAGE_SMALL = VLImage.load(filename=SMALL_IMAGE)
VLIMAGE_ONE_FACE = VLImage.load(filename=ONE_FACE)
VLIMAGE_BAD_IMAGE = VLImage.load(filename=BAD_IMAGE)
VLIMAGE_SEVERAL_FACE = VLImage.load(filename=SEVERAL_FACES)
VLIMAGE_LARGE_IMAGE = VLImage.load(filename=LARGE_IMAGE)
GOOD_AREA = Rect(100, 100, VLIMAGE_ONE_FACE.rect.width - 100,
VLIMAGE_ONE_FACE.rect.height - 100)
OUTSIDE_AREA = Rect(100, 100, VLIMAGE_ONE_FACE.rect.width,
VLIMAGE_ONE_FACE.rect.height)
SMALL_AREA = Rect(50, 50, 52, 52)
LARGE_AREA = Rect(1, 1, VLIMAGE_LARGE_IMAGE.rect.width - 1,
VLIMAGE_LARGE_IMAGE.rect.height - 1)
AREA_LARGER_IMAGE = Rect(100, 100, VLIMAGE_ONE_FACE.rect.width + 100,
VLIMAGE_ONE_FACE.rect.height + 100)
AREA_OUTSIDE_IMAGE = Rect(
VLIMAGE_ONE_FACE.rect.width,
VLIMAGE_ONE_FACE.rect.height,
VLIMAGE_ONE_FACE.rect.width + 100,
VLIMAGE_ONE_FACE.rect.height + 100,
)
AREA_WITHOUT_FACE = Rect(50, 50, 100, 100)
INVALID_RECT = Rect(0, 0, 0, 0)
def test_image_load_from_url(self):
url = "https://cdn1.savepice.ru/uploads/2019/4/15/194734af15c4fcd06dec6db86bbeb7cd-full.jpg"
image = VLImage.load(url=url)
assert image.isValid()
assert image.rect == Rect(0, 0, 497, 640)
assert image.source == url
def test_image_load_from_file(self):
image = VLImage.load(filename=ONE_FACE)
assert image.rect == Rect(0, 0, 912, 1080)
assert image.isValid()
assert image.source == "one_face.jpg"
from lunavl.sdk.base import BoundingBox, LandmarkWithScore
from lunavl.sdk.detectors.base import BaseDetection
from lunavl.sdk.detectors.facedetector import FaceDetection, FaceDetector, Landmarks5, Landmarks68
from lunavl.sdk.detectors.humandetector import HumanDetection, HumanDetector, Landmarks17
from lunavl.sdk.faceengine.engine import DetectorType
from lunavl.sdk.image_utils.geometry import Point
from lunavl.sdk.image_utils.geometry import Rect
from lunavl.sdk.image_utils.image import VLImage
from tests.base import BaseTestClass
from tests.resources import ONE_FACE, SEVERAL_FACES, SMALL_IMAGE
SINGLE_CHANNEL_IMAGE = Image.open(ONE_FACE).convert("L")
VLIMAGE_SMALL = VLImage.load(filename=SMALL_IMAGE)
VLIMAGE_ONE_FACE = VLImage.load(filename=ONE_FACE)
VLIMAGE_SEVERAL_FACE = VLImage.load(filename=SEVERAL_FACES)
GOOD_AREA = Rect(100, 100, VLIMAGE_ONE_FACE.rect.width - 100,
VLIMAGE_ONE_FACE.rect.height - 100)
OUTSIDE_AREA = Rect(100, 100, VLIMAGE_ONE_FACE.rect.width,
VLIMAGE_ONE_FACE.rect.height)
AREA_WITHOUT_FACE = Rect(50, 50, 100, 100)
INVALID_RECT = Rect(0, 0, 0, 0)
ERROR_CORE_RECT = Rect(0.1, 0.1, 0.1, 0.1) # anything out of range (0.1, 1)
class BaseDetectorTestClass(BaseTestClass):
"""
Base class for detectors tests
"""
#: detection class
detectionClass: Type[BaseDetection]