def RappFaceDetection(self, imageString, image):
path = imageORimageString(imageString, image) #path of saved image.
ch = RappPlatformAPI(address=addr)
response = ch.faceDetection(
path) # Use the server's path of the image.
return response
class FaceDetectionTests(unittest.TestCase):
def setUp(self):
self.ch = RappPlatformAPI()
rospack = rospkg.RosPack()
self.pkgDir = rospack.get_path('rapp_testing_tools')
def test_closeStraight(self):
imagepath = path.join(self.pkgDir, 'test_data', 'face_samples',
'klpanagi_close_straight.jpg')
response = self.ch.faceDetection(imagepath)
valid_faces = [{
'up_left_point': {
'y': 450.0,
'x': 640.0
},
'down_right_point': {
'y': 662.0,
'x': 852.0
}
}]
self.assertEqual(response['error'], u'')
self.assertEqual(response['faces'], valid_faces)
def test_lenna(self):
imagepath = path.join(self.pkgDir, 'test_data', 'Lenna.png')
response = self.ch.faceDetection(imagepath)
valid_faces = [{
'up_left_point': {
'y': 201.0,
'x': 213.0
},
'down_right_point': {
'y': 378.0,
'x': 390.0
}
}]
self.assertEqual(response['error'], u'')
self.assertEqual(response['faces'], valid_faces)
def test_multipleFaces(self):
imagepath = path.join(self.pkgDir, 'test_data', 'face_samples', \
'multi_faces_frames', 'multi_faces.jpg')
response = self.ch.faceDetection(imagepath)
self.assertEqual(response['error'], u'')
self.assertEqual(len(response['faces']), 3)
def test_notExistentFile(self):
imagepath = path.join(self.pkgDir, 'face_samples', \
'multi_faces_frames', 'multi_faces.jpg')
response = self.ch.faceDetection(imagepath)
self.assertNotEqual(response['error'], u'')
def test_erroneousFileType(self):
imagepath = 3
response = self.ch.faceDetection(imagepath)
self.assertNotEqual(response['error'], u'')
# Delay to stabilize the head
time.sleep(1)
image_name = "img_" + str(i * 3 + j) + ".jpg"
# Capture an image from the NAO cameras
rh.vision.capturePhoto("/home/nao/" + image_name, "front", "640x480")
# Get the photo to the PC
rh.utilities.moveFileToPC("/home/nao/" + image_name, \
home + image_name)
imageFilepath = home + image_name
# Get the responses
qr_resp = ch.qrDetection(imageFilepath)
face_resp = ch.faceDetection(imageFilepath, False)
obj_resp = ch.objectRecognitionCaffe(imageFilepath)
# Prints for debugging purposes
print str(global_counter) + ": " + str(qr_resp)
print str(global_counter) + ": " + str(face_resp)
print str(global_counter) + ": " + str(obj_resp)
print "\n"
# Store the objects and the respective head angles
# Store the unique QR codes
if len(qr_resp['qr_centers']) != 0:
# Transform Image-frame angles to NAO-frame
obj_frame_ang = pointToRads(
qr_resp['qr_centers'][0]['x'],
qr_resp['qr_centers'][0]['y'],
