def test(self):
resetAutonomousDb()
rest = ImagingInterface(isManual=False)
# table should be empty
self.assertIsNone(rest.getNextCroppedImage())
# push image into the table so that we can get it
ret = rest.getNextRawImage()
self.assertIsNotNone(ret)
resp = rest.postCroppedImage(ret[1], ret[0], [22, 22], [236, 236])
cropId = int(resp.headers['X-Crop-Id'])
# post a second image so we can confirm it gets the first posted one first
resp = rest.postCroppedImage(ret[1], ret[0], [33, 33], [789, 789])
cropId2 = int(resp.headers['X-Crop-Id'])
self.assertNotEqual(cropId, cropId2)
result = rest.getNextCroppedImage()
self.assertIsNotNone(result)
self.assertIsNotNone(result[0])
self.assertEqual(result[1], cropId)
result = rest.getNextCroppedImage()
self.assertIsNotNone(result)
self.assertIsNotNone(result[0])
self.assertEqual(result[1], cropId2)
def test(self):
resetDb()
rest = ImagingInterface(isManual=False)
# empty table
self.assertIsNone(rest.getAllSubmittedTargets())
# create one target
ret = rest.getNextRawImage()
self.assertIsNotNone(ret)
resp = rest.postCroppedImage(ret[1], ret[0], [22, 22], [236, 236])
self.assertIsNotNone(resp)
self.assertEqual(resp.status_code,
200) # assert successful post to cropped
cropId = int(resp.headers['X-Crop-Id'])
classToPost = Classification(cropId, 'standard', 'NE', 'circle',
'white', 'T', 'yellow')
resp = rest.postClass(classToPost)
self.assertIsNotNone(resp)
classId = int(resp.headers['X-Class-Id'])
modelResult = rest.getClassById(classId)
self.assertIsNotNone(modelResult)
targetId = modelResult.target
# post a second crop and classification which goes to a different target:
resp = rest.postCroppedImage(ret[1], ret[0], [22, 22], [236, 236])
self.assertIsNotNone(resp)
self.assertEqual(resp.status_code,
200) # assert successful post to cropped
cropId2 = int(resp.headers['X-Crop-Id'])
# since it's shape is different, this should be a different target
classToPost = Classification(cropId2, 'standard', 'NE', 'square',
'orange', 'T', 'black')
resp = rest.postClass(classToPost)
self.assertIsNotNone(resp)
classId2 = int(resp.headers['X-Class-Id'])
modelResult = rest.getClassById(classId2)
self.assertIsNotNone(modelResult)
targetId2 = modelResult.target
self.assertNotEqual(targetId, targetId2)
self.assertIsNotNone(rest.postSubmitAllTargets())
resp = rest.getAllSubmittedTargets()
self.assertIsNotNone(resp)
self.assertEqual(len(resp), 2)
if resp[0].target == targetId:
self.assertEqual(resp[0].crop_id, cropId)
self.assertEqual(resp[1].crop_id, cropId2)
elif resp[0].target == targetId2:
self.assertEqual(resp[0].crop_id, cropId2)
else:
self.fail(
msg=
"errrmmm. One of the returned target ids does not match what we submitted"
)
def test(self):
resetManualDb()
rest = ImagingInterface()
ret = rest.getNextRawImage()
self.assertIsNotNone(ret)
self.assertEqual(len(ret), 2)
self.assertIsNotNone(ret[0])
self.assertIsNotNone(ret[1])
self.assertIsNotNone(ret[0].size) # (width, height) of image
self.assertNotEqual(id, -1)
def test(self):
resetManualDb()
rest = ImagingInterface()
ret = rest.getNextRawImage()
self.assertIsNotNone(ret)
resp = rest.postCroppedImage(ret[1], ret[0], [0, 0], [236, 236])
self.assertIsNotNone(resp)
self.assertEqual(resp.status_code, 200) # assert successful post
cropId = int(resp.headers['X-Crop-Id'])
self.assertIsNotNone(cropId)
self.assertNotEqual(cropId, -1)
def test(self):
resetManualDb()
rest = ImagingInterface()
# table should be empty
self.assertIsNone(rest.getCroppedImage(100))
# push image into the table so that we can get it
ret = rest.getNextRawImage()
self.assertIsNotNone(ret)
resp = rest.postCroppedImage(ret[1], ret[0], [22, 22], [236, 236])
cropId = int(resp.headers['X-Crop-Id'])
resp = rest.getCroppedImage(cropId)
self.assertIsNotNone(resp)
self.assertIsNotNone(resp[0])
self.assertEqual(resp[1], cropId)
def test(self):
resetDb()
rest = ImagingInterface()
ret = rest.getNextRawImage()
self.assertIsNotNone(ret)
resp = rest.postCroppedImage(ret[1], ret[0], [22, 22], [236, 236])
self.assertIsNotNone(resp)
self.assertEqual(resp.status_code,
200) # assert successful post to cropped
_, cropId, _ = rest.getNextCroppedImage(
) # get the cropId as they would in the gui
classToPost = Classification(cropId, 'standard', 'NE', 'circle',
'white', 'T', 'yellow')
resp = rest.postClass(classToPost)
self.assertIsNotNone(resp)
classId = resp.headers['X-Class-Id']
self.assertIsNotNone(classId)
self.assertNotEqual(int(classId), -1)
# should fail to update stuff that doesn't exist
stuffToUpdate = Classification(None, None, "SE", "square", None, "Y",
"purple")
self.assertIsNone(rest.updateClass(int(classId) + 20, stuffToUpdate))
resp = rest.updateClass(classId, stuffToUpdate)
# confirm update claims success
self.assertIsNotNone(resp)
self.assertEqual(resp.status_code, 200)
# confirm update was acutlaly successful
updated = rest.getClassById(classId)
self.assertIsNotNone(updated)
self.assertEqual(updated.crop_id, cropId)
self.assertEqual(updated.type, 'standard')
self.assertEqual(updated.orientation, 'SE')
self.assertEqual(updated.shape, 'square')
self.assertEqual(updated.background_color, 'white')
self.assertEqual(updated.alphanumeric, "Y")
self.assertEqual(updated.alphanumeric_color, "purple")
def test(self):
resetDb()
rest = ImagingInterface()
# empty table
self.assertIsNone(rest.getSubmittedTargetById(100))
ret = rest.getNextRawImage()
self.assertIsNotNone(ret)
resp = rest.postCroppedImage(ret[1], ret[0], [22, 22], [236, 236])
self.assertIsNotNone(resp)
self.assertEqual(resp.status_code,
200) # assert successful post to cropped
cropId = int(resp.headers['X-Crop-Id'])
classToPost = Classification(cropId, 'standard', 'NE', 'circle',
'white', 'T', 'yellow')
resp = rest.postClass(classToPost)
self.assertIsNotNone(resp)
classId = int(resp.headers['X-Class-Id'])
modelResult = rest.getClassById(classId)
self.assertIsNotNone(modelResult)
targetId = modelResult.target
# should still be none since the target is unsubmitted
self.assertIsNone(rest.getSubmittedTargetById(targetId))
# submit the target
resp = rest.postSubmitTargetById(targetId)
self.assertIsNotNone(resp)
# now lets see if the getter works:
resp = rest.getSubmittedTargetById(targetId)
self.assertIsNotNone(resp)
self.assertIsInstance(resp, Classification)
self.assertEqual(resp.target, targetId)
self.assertEqual(resp.crop_id, cropId)
self.assertEqual(resp.type, 'standard')
self.assertEqual(resp.shape, 'circle')
self.assertEqual(resp.orientation, 'NE')
self.assertEqual(resp.background_color, 'white')
self.assertEqual(resp.alphanumeric, 'T')
self.assertEqual(resp.alphanumeric_color, 'yellow')
self.assertEqual(resp.submitted, 'pending')
def test(self):
resetDb()
rest = ImagingInterface()
# should get none when we try and post on empty table
self.assertIsNone(rest.postSubmitTargetById(100))
ret = rest.getNextRawImage()
self.assertIsNotNone(ret)
resp = rest.postCroppedImage(ret[1], ret[0], [22, 22], [236, 236])
self.assertIsNotNone(resp)
self.assertEqual(resp.status_code,
200) # assert successful post to cropped
cropId = int(resp.headers['X-Crop-Id'])
classToPost = Classification(cropId, 'standard', 'NE', 'circle',
'white', 'T', 'yellow')
resp = rest.postClass(classToPost)
self.assertIsNotNone(resp)
classId = int(resp.headers['X-Class-Id'])
modelResult = rest.getClassById(classId)
self.assertIsNotNone(modelResult)
targetId = modelResult.target
# trying to submit an id that doesn't exist should also fail
self.assertIsNone(rest.postSubmitTargetById(targetId + 20))
resp = rest.postSubmitTargetById(targetId)
self.assertIsNotNone(resp)
self.assertEqual(resp.status_code, 200)
# confirm that the classification's status has changed to submitted
modelResult = rest.getClassById(classId)
self.assertIsNotNone(modelResult)
self.assertIsNotNone(modelResult.target)
self.assertEqual(modelResult.submitted, 'submitted')
# trying to submit the same target again should fail:
self.assertIsNone(rest.postSubmitTargetById(targetId))
def test(self):
resetDb()
rest = ImagingInterface()
ret = rest.getNextRawImage()
self.assertIsNotNone(ret)
resp = rest.postCroppedImage(ret[1], ret[0], [22, 22], [236, 236])
self.assertIsNotNone(resp)
self.assertEqual(resp.status_code,
200) # assert successful post to cropped
_, cropId, _ = rest.getNextCroppedImage(
) # get the cropId as they would in the gui
classToPost = Classification(cropId, 'standard', 'NE', 'circle',
'white', 'T', 'yellow')
resp = rest.postClass(classToPost)
self.assertIsNotNone(resp)
classId = resp.headers['X-Class-Id']
self.assertIsNotNone(classId)
self.assertNotEqual(int(classId), -1)
def test(self):
resetManualDb()
rest = ImagingInterface()
# table should be empty
self.assertIsNone(rest.getCroppedImageInfo(100))
# push image into the table so that we can get it
ret = rest.getNextRawImage()
self.assertIsNotNone(ret)
resp = rest.postCroppedImage(ret[1], ret[0], [22, 22], [236, 236])
cropId = int(resp.headers['X-Crop-Id'])
# post a second image just for funnsies
resp = rest.postCroppedImage(ret[1], ret[0], [33, 33], [789, 789])
cropId2 = int(resp.headers['X-Crop-Id'])
resp = rest.getAllCroppedInfo()
self.assertIsNotNone(resp)
# verify the returned data is what we put in
self.assertEqual(len(resp), 2)
modelA = resp[0]
modelB = resp[1]
if modelA.cropId == cropId:
self.assertEqual(modelA.imgId, ret[1]) #image_id
self.assertTrue(hasattr(modelA, 'path'))
self.assertTrue(hasattr(modelA, 'time_stamp'))
self.assertEqual(modelA.tl[0], 22)
self.assertEqual(modelA.tl[1], 22)
self.assertEqual(modelA.br[0], 236)
self.assertEqual(modelA.br[1], 236)
self.assertFalse(modelA.isTapped)
# check model B
self.assertEqual(modelB.imgId, ret[1]) #image_id
self.assertTrue(hasattr(modelB, 'path'))
self.assertTrue(hasattr(modelB, 'time_stamp'))
self.assertEqual(modelB.tl[0], 33)
self.assertEqual(modelB.tl[1], 33)
self.assertEqual(modelB.br[0], 789)
self.assertEqual(modelB.br[1], 789)
self.assertFalse(modelB.isTapped)
elif modelA.cropId == cropId2:
self.assertEqual(modelA.imgId, ret[1]) #image_id
self.assertTrue(hasattr(modelA, 'path'))
self.assertTrue(hasattr(modelA, 'time_stamp'))
self.assertEqual(modelA.tl[0], 33)
self.assertEqual(modelA.tl[1], 33)
self.assertEqual(modelA.br[0], 789)
self.assertEqual(modelA.br[1], 789)
self.assertFalse(modelA.isTapped)
#check model b
self.assertEqual(modelB.imgId, ret[1]) #image_id
self.assertTrue(hasattr(modelB, 'path'))
self.assertTrue(hasattr(modelB, 'time_stamp'))
self.assertEqual(modelB.tl[0], 22)
self.assertEqual(modelB.tl[1], 22)
self.assertEqual(modelB.br[0], 236)
self.assertEqual(modelB.br[1], 236)
self.assertFalse(modelB.isTapped)
else:
self.fail()
def test(self):
resetDb()
rest = ImagingInterface()
# should get none if classification/pend list is empty:
self.assertIsNone(rest.getPendingSubmissions())
ret = rest.getNextRawImage()
self.assertIsNotNone(ret)
resp = rest.postCroppedImage(ret[1], ret[0], [22, 22], [236, 236])
self.assertIsNotNone(resp)
self.assertEqual(resp.status_code,
200) # assert successful post to cropped
cropId = int(resp.headers['X-Crop-Id'])
classToPost = Classification(cropId, 'standard', 'NE', 'circle',
'white', 'T', 'yellow')
resp = rest.postClass(classToPost)
self.assertIsNotNone(resp)
classId = resp.headers['X-Class-Id']
resp = rest.getPendingSubmissions()
self.assertIsNotNone(resp)
self.assertEqual(len(resp), 1)
self.assertEqual(len(resp[0]), 1)
self.assertEqual(resp[0][0].class_id, int(classId))
self.assertEqual(resp[0][0].crop_id, int(cropId))
# post a second crop and classification which goes to a different target:
resp = rest.postCroppedImage(ret[1], ret[0], [22, 22], [236, 236])
self.assertIsNotNone(resp)
self.assertEqual(resp.status_code,
200) # assert successful post to cropped
cropId2 = int(resp.headers['X-Crop-Id'])
# since it's shape is different, this should be a different target
classToPost = Classification(cropId2, 'standard', 'NE', 'square',
'orange', 'T', 'black')
resp = rest.postClass(classToPost)
self.assertIsNotNone(resp)
classId2 = int(resp.headers['X-Class-Id'])
resp = rest.getPendingSubmissions()
self.assertIsNotNone(resp)
self.assertEqual(len(resp), 2)
self.assertEqual(len(resp[0]), 1)
self.assertEqual(len(resp[1]), 1)
# post a third crop and classification which goes to one of our already existing targets
resp = rest.postCroppedImage(ret[1], ret[0], [22, 22], [236, 236])
self.assertIsNotNone(resp)
self.assertEqual(resp.status_code,
200) # assert successful post to cropped
cropId3 = int(resp.headers['X-Crop-Id'])
# this should be a match with target2
classToPost = Classification(cropId3, 'standard', 'SE', 'square',
'purple', 'T', 'black')
resp = rest.postClass(classToPost)
self.assertIsNotNone(resp)
classId3 = int(resp.headers['X-Class-Id'])
self.assertNotEqual(classId2, classId3)
resp = rest.getPendingSubmissions()
self.assertIsNotNone(resp)
self.assertEqual(len(resp), 2)
if len(resp[0]) == 2:
self.assertEqual(resp[0][1].type, 'standard')
self.assertEqual(resp[0][1].shape, 'square')
self.assertEqual(resp[0][0].alphanumeric, 'T')
self.assertEqual(resp[1][0].class_id, int(classId))
self.assertEqual(resp[1][0].crop_id, int(cropId))
elif len(resp[1]) == 2:
self.assertEqual(resp[0][0].class_id, int(classId))
self.assertEqual(resp[0][0].crop_id, int(cropId))
self.assertEqual(resp[1][1].type, 'standard')
self.assertEqual(resp[1][1].shape, 'square')
self.assertEqual(resp[1][0].alphanumeric, 'T')
else:
self.fail(msg="one of the targets should have two classifications")
def test(self):
resetDb()
rest = ImagingInterface()
ret = rest.getNextRawImage()
self.assertIsNotNone(ret)
# get stuff into the cropped and classification table
resp = rest.postCroppedImage(ret[1], ret[0], [22, 22], [236, 236])
self.assertIsNotNone(resp)
self.assertEqual(resp.status_code,
200) # assert successful post to cropped
_, cropId, _ = rest.getNextCroppedImage(
) # get the cropId as they would in the gui
classToPost = Classification(cropId, 'standard', 'NE', 'circle',
'white', 'T', 'yellow')
resp = rest.postClass(classToPost)
self.assertIsNotNone(resp)
classId = int(resp.headers['X-Class-Id'])
# post a second crop and classification:
resp = rest.postCroppedImage(ret[1], ret[0], [22, 22], [236, 236])
self.assertIsNotNone(resp)
self.assertEqual(resp.status_code,
200) # assert successful post to cropped
_, cropId2, _ = rest.getNextCroppedImage(
) # get the cropId as they would in the gui
classToPost = Classification(cropId2, 'off_axis', 'NE', 'square',
'orange', 'T', 'black')
resp = rest.postClass(classToPost)
self.assertIsNotNone(resp)
classId2 = int(resp.headers['X-Class-Id'])
# get all:
resp = rest.getAllClass()
self.assertIsNotNone(resp)
self.assertEqual(len(resp), 2)
modelA = resp[0]
modelB = resp[1]
if modelA.class_id == classId:
#check model A
self.assertEqual(modelA.crop_id, cropId)
self.assertEqual(modelA.class_id, classId)
self.assertEqual(modelA.type, 'standard')
self.assertEqual(modelA.orientation, 'NE')
self.assertEqual(modelA.shape, 'circle')
self.assertEqual(modelA.background_color, 'white')
self.assertEqual(modelA.alphanumeric, 'T')
self.assertEqual(modelA.alphanumeric_color, 'yellow')
self.assertEqual(modelA.submitted, 'unsubmitted')
self.assertEqual(modelA.description, '')
self.assertIsNotNone(modelA.target)
# check model B
self.assertEqual(modelB.crop_id, cropId2)
self.assertEqual(modelB.class_id, classId2)
self.assertEqual(modelB.type, 'off_axis')
self.assertEqual(modelB.orientation, 'NE')
self.assertEqual(modelB.shape, 'square')
self.assertEqual(modelB.background_color, 'orange')
self.assertEqual(modelB.alphanumeric, 'T')
self.assertEqual(modelB.alphanumeric_color, 'black')
self.assertEqual(modelB.submitted, 'unsubmitted')
self.assertEqual(modelB.description, '')
self.assertIsNotNone(modelB.target)
elif modelA.class_id == classId2:
#check model B
self.assertEqual(modelB.crop_id, cropId)
self.assertEqual(modelB.class_id, classId)
self.assertEqual(modelB.type, 'standard')
self.assertEqual(modelB.orientation, 'NE')
self.assertEqual(modelB.shape, 'circle')
self.assertEqual(modelB.background_color, 'white')
self.assertEqual(modelB.alphanumeric, 'T')
self.assertEqual(modelB.alphanumeric_color, 'yellow')
self.assertEqual(modelB.submitted, 'unsubmitted')
self.assertEqual(modelB.description, '')
self.assertIsNotNone(modelB.target)
# check model A
self.assertEqual(modelA.crop_id, cropId2)
self.assertEqual(modelA.class_id, classId2)
self.assertEqual(modelA.type, 'off_axis')
self.assertEqual(modelA.orientation, 'NE')
self.assertEqual(modelA.shape, 'square')
self.assertEqual(modelA.background_color, 'orange')
self.assertEqual(modelA.alphanumeric, 'T')
self.assertEqual(modelA.alphanumeric_color, 'black')
self.assertEqual(modelA.submitted, 'unsubmitted')
self.assertEqual(modelA.description, '')
self.assertIsNotNone(modelA.target)
else:
self.fail()
class AutonomousManager():
def __init__(self,
serverHost,
serverPort,
detection=True,
classification=True,
img_start=None,
submit_interval=120,
show=False):
"""
Initialize a top-level autonomous manager
@param serverHost: Local ip address of the machine the imaging server is running on
@param serverPort: Port the server is running on. Default 5000
@param detection: Whether the detector should be run by this manager. Default: True
@param classification: Whether the classifiers should be run by this manager. Default: False
"""
print("Autonomous Startup")
self._should_shutdown = False
self.client = ImagingInterface(serverHost,
serverPort,
isDebug=False,
isManual=False)
self.submit_interval = submit_interval
self.show = show
# for manually specifying which image in the server to start detection on
self.img_start = img_start
self.img_num = img_start
# we give the option of having a machine thats running this Manager run
# ONLY the detection algorithm, or ONLY the classification algorithm,
# or both
self.doDetection = detection
self.doClassification = classification
if detection and classification:
self.detector = AutonomousDetection()
self.classifier = AutonomousClassification()
elif not detection:
print("Turning off classification for this autonomous process")
self.detector = AutonomousDetection()
self.doClassification = False
self.doDetection = True
elif not classification:
print("Turning off detection for this autonomous process")
self.classifier = AutonomousClassification()
self.doDetection = False
self.doClassification = True
if not classification and not detection:
print("ERROR:: Cant disable both detection and classification!")
exit(1)
def submitTargets(self):
"""
submit all pending autonomous targets
"""
print("Submitting all pending targets...")
self.client.postSubmitAllTargets()
def runClassification(self):
"""
If this autonomous manager is set todo so, run classification on an available
cropped image, if any.
"""
toClassify = self.client.getNextCroppedImage()
if toClassify is not None:
imgToClassify = np.array(toClassify[0])[:, :, ::-1]
cropId = toClassify[1]
cropInfo = self.client.getCroppedImageInfo(cropId)
if cropInfo is None:
print("Failed to get cropped image info!")
return # couldnt get info on the cropped image? weird..
rawInfo = self.client.getImageInfo(cropInfo.imgId)
stateMeas = None
if rawInfo is None:
print(
"Failed to get raw image info while attempting to classify!"
)
else:
# get the state measurement closest to the raw image timestamp
stateMeas = self.client.getStateByTs(rawInfo.time_stamp)
classified = None
if stateMeas is not None:
# if we were able to get a state measurement close to our raw img timestamp use it to try and decide orientation
classified = self.classifier.classify(imgToClassify,
show=False,
yaw=stateMeas.yaw)
else:
# attempt to classify without orientation data
classified = self.classifier.classify(imgToClassify,
show=False)
# print("Crop #: %i" % (cropId))
if self.show:
to_display = self.classifier.blur_crop.copy()
cv2.putText(to_display, str(cropId), (5, 50),
cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 1,
cv2.LINE_AA)
cv2.imshow('Crop', to_display)
key = cv2.waitKey(1) & 0xFF
if classified is not None:
print("Successfully classified crop {}!".format(cropId))
print(
"\tshape={},letter={},shapeClr={}letterClr={},orientation={}"
.format(classified['shape'], classified['letter'],
classified['shapeColor'],
classified['letterColor'],
classified['orientation']))
# TODO: Always assuming standard target for now..
toPost = Classification(cropId,
"standard",
orientation=classified['orientation'],
shape=classified['shape'],
bgColor=classified['shapeColor'],
alpha=classified['letter'],
alphaColor=classified['letterColor'])
self.client.postClass(toPost)
else:
print("Crop # %i rejected as false positive" % (cropId))
def runDetection(self):
"""
If this autonomous manager is set todo so, run detection on an available
raw image, if any.
One issue here is client_rest expects/returns a PIL image and the
detector expects/returns an opencv image (aka numpy array). So
this method has to deal with converting between the two
"""
if self.img_start is not None:
toDetect = self.client.getRawImage(
self.img_num) #returns None if the image id doesn't exist
if toDetect is not None:
self.img_num += 1
else:
toDetect = self.client.getNextRawImage(
) # returns tuple of (image, image_id)
# if there are new raw images to process
if toDetect is not None:
imgToDetect = np.array(toDetect[0])[:, :, ::-1]
imgId = toDetect[1]
results = self.detector.detect(imgToDetect, 0)
print('Img #: %i' % (imgId), ' Results: %i' % (len(results)))
print(hasattr(self.detector, 'keypoints_image'))
if self.show: # and hasattr(self.detector, 'keypoints_image'):
to_display = self.detector.keypoints_image.copy()
cv2.putText(to_display, str(imgId), (10, 50),
cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 1,
cv2.LINE_AA)
cv2.imshow('Detected', to_display)
key = cv2.waitKey(1) & 0xFF
# if the detector actually returned something that's not an empty list
if results is not None and results:
# then lets post each of its cropped images to the server
for detectedTarget in results:
pilCrop = cv2.cvtColor(detectedTarget.crop,
cv2.COLOR_BGR2RGB)
pilCrop = Image.fromarray(pilCrop)
self.client.postCroppedImage(imgId, pilCrop,
detectedTarget.topLeft,
detectedTarget.bottomRight)
def run(self):
"""
Sit and spin, checking for new images and processing them as necessary
"""
last_submit = time.time()
while 1:
if not self.client.ping(
): # confirm we can still connect to the server
print("WARN:: Cannot connect to server")
time.sleep(5)
if self.doDetection:
self.runDetection()
if self.doClassification:
self.runClassification()
if (time.time() - last_submit) > self.submit_interval:
self.submitTargets()
last_submit = time.time()
time.sleep(0.1)
def shutdown(self):
self._should_shutdown = True