def test_for_four(self):
four_allowed = 1-numpy.clip(cv2.imread("Resources/four_allowed.png", cv2.IMREAD_GRAYSCALE), 0, 1)
contours = ImagePreprocessor.find_contours(four_allowed)
number_of_recognized_signs1 = ImagePreprocessor.calculate_number_of_signs(four_allowed, contours)
self.assertEqual(4, number_of_recognized_signs1)
def test_if_odd(self):
two_allowed = 1 - numpy.clip(cv2.imread("Resources/odd.png", cv2.IMREAD_GRAYSCALE), 0, 1)
contours = ImagePreprocessor.find_contours(two_allowed)
number_of_recognized_signs = ImagePreprocessor.calculate_number_of_signs(two_allowed, contours)
number_of_recognized_signs = number_of_recognized_signs % 2
self.assertEqual(1, number_of_recognized_signs)
def test_extract_lane_shape(self):
data_in = numpy.clip(
cv2.imread("Resources/Lane_Fork_Noise.png", cv2.IMREAD_GRAYSCALE),
0, 1)
contours = ImagePreprocessor.find_contours(data_in)
data_out = ImagePreprocessor.extract_lane_shape(data_in, contours)
expected = numpy.clip(
cv2.imread("Resources/Lane_Fork_Clean.png", cv2.IMREAD_GRAYSCALE),
0, 1)
numpy.testing.assert_array_equal(data_out, expected)
def process_frame(self, image):
"""
Processes the frame captured by Cozmo's camera
:param image: Current frame from Cozmo's feed
:type image: PIL image
"""
# Convert image to binary
bin_img = ImagePreprocessor.pil_rgb_to_numpy_binary(image)
# Find contours on image
contours = ImagePreprocessor.find_contours(bin_img)
# Extract lane shape and remove noise
lane_img = ImagePreprocessor.extract_lane_shape(bin_img, contours)
# Create image for later display
display_img = cv2.cvtColor(lane_img * 255, cv2.COLOR_GRAY2BGR)
# Counting signs and overwrite attribute in Lane Analyzer
if RobotStatusController.enable_sign_recognition and \
not Settings.disable_sign_detection and \
not RobotStatusController.disable_autonomous_behavior:
RobotStatusController.sign_count = ImagePreprocessor.calculate_number_of_signs(
display_img, contours)
self.sign_handler.react_to_signs(RobotStatusController.sign_count)
lane_correction = 0
if not RobotStatusController.disable_autonomous_behavior:
# Calculate lane correction based on image data
lane_correction = self.corr_calculator.calculate_lane_correction(
lane_img)
if not RobotStatusController.is_in_packet_station:
crossing_type = CrossingTypeIdentifier.analyze_frame(lane_img)
if crossing_type is not None:
Navigator.navigate()
if not RobotStatusController.disable_autonomous_behavior:
# If correction is required let Cozmo correct
if lane_correction is not None:
self.drive_controller.correct(lane_correction)
# Update current frame
self.current_cam_frame = display_img * 255
# Show cam live preview if enabled
if Settings.show_live_preview:
# self.preview_utils.show_cam_frame(bin_img*255)
self.preview_utils.show_cam_frame(display_img)