def create_visuals(robots, actual_map_name, out):
db = get_easy_algo_db()
actual_map = db.create_instance(FAMILY_SEGMAPS, actual_map_name)
res = OrderedDict()
res2 = OrderedDict()
for i, robot_name in enumerate(sorted(robots)):
dtu.logger.info('%d/%d: %s' % (i, len(robots), robot_name))
try:
gp = GroundProjection(robot_name)
except (NoCameraInfoAvailable, NoHomographyInfoAvailable) as e:
dtu.logger.warning('skipping %r: %s' % (robot_name, e))
continue
gpg = gp.get_ground_projection_geometry()
pose = np.eye(3)
simulated_data = \
simulate_image(actual_map, pose, gpg, blur_sigma=1)
res[robot_name] = simulated_data.rectified_synthetic_bgr
res2[robot_name] = simulated_data.distorted_synthetic_bgr
if not res:
msg = 'No images to draw.'
dtu.logger.error(msg)
else:
output = os.path.join(out, 'distorted')
dtu.write_bgr_images_as_jpgs(res2, output)
output = os.path.join(out, 'rectified')
dtu.write_bgr_images_as_jpgs(res, output)
def look_at(log, output, anti_instagram, line_detector, image_prep,
lane_filter, all_details):
filename = get_local_bag_file(log)
bag = rosbag.Bag(filename)
vehicle_name = dtu.which_robot(bag)
dtu.logger.info('Vehicle name: %s' % vehicle_name)
gp = GroundProjection(vehicle_name)
topic = dtu.get_image_topic(bag)
res = dtu.d8n_read_all_images_from_bag(bag, topic, max_images=1)
image_cv = res[0]['rgb']
# dtu.logger.debug(dtu.describe_value(image_cv))
image_cv_bgr = dtu.bgr_from_rgb(image_cv)
dtu.DuckietownConstants.show_timeit_benchmarks = True
res, _stats = run_pipeline(image_cv_bgr,
gp=gp,
anti_instagram_name=anti_instagram,
line_detector_name=line_detector,
image_prep_name=image_prep,
lane_filter_name=lane_filter,
all_details=all_details)
res = dtu.resize_small_images(res)
dtu.write_bgr_images_as_jpgs(res, output)
def single_image_histograms():
p = dtu.require_resource('frame0002.jpg')
image_cv = dtu.image_cv_from_jpg_fn(p)
res = go(image_cv)
outd = dtu.get_output_dir_for_test()
dtu.write_bgr_images_as_jpgs(res, outd)
def go(self):
vehicle_name = dtu.get_current_robot_name() if dtu.on_duckiebot(
) else "default"
output = self.options.output
if output is None:
output = 'out-pipeline' # + dtu.get_md5(self.options.image)[:6]
self.info('No --output given, using %s' % output)
if self.options.image is not None:
image_filename = self.options.image
if image_filename.startswith('http'):
image_filename = dtu.get_file_from_url(image_filename)
bgr = dtu.bgr_from_jpg_fn(image_filename)
else:
print("Validating using the ROS image stream...")
import rospy
from sensor_msgs.msg import CompressedImage
topic_name = os.path.join('/', vehicle_name,
'camera_node/image/compressed')
print('Let\'s wait for an image. Say cheese!')
# Dummy to get ROS message
rospy.init_node('single_image')
img_msg = None
try:
img_msg = rospy.wait_for_message(topic_name,
CompressedImage,
timeout=10)
print('Image captured!')
except rospy.ROSException as e:
print(
'\n\n\nDidn\'t get any message!: %s\n MAKE SURE YOU USE DT SHELL COMMANDS OF VERSION 4.1.9 OR HIGHER!\n\n\n'
% (e, ))
bgr = dtu.bgr_from_rgb(dtu.rgb_from_ros(img_msg))
self.info('Picture taken: %s ' % str(bgr.shape))
gp = GroundProjection(vehicle_name)
dtu.DuckietownConstants.show_timeit_benchmarks = True
res, _stats = run_pipeline(
bgr,
gp,
line_detector_name=self.options.line_detector,
image_prep_name=self.options.image_prep,
anti_instagram_name=self.options.anti_instagram,
lane_filter_name=self.options.lane_filter)
self.info('Resizing images..')
res = dtu.resize_small_images(res)
self.info('Writing images..')
dtu.write_bgr_images_as_jpgs(res, output)
def test_synthetic(actual_map_name, template, robot_name, line_detector_name,
image_prep_name, lane_filter_name, pose_or_location, outd):
np.random.seed(42)
db = get_easy_algo_db()
actual_map = db.create_instance(FAMILY_SEGMAPS, actual_map_name)
# first, load calibration for robot
easy_algo_db = get_easy_algo_db()
dtu.logger.debug('looking for localization template %r' % template)
localization_template = easy_algo_db.create_instance(
FAMILY_LOC_TEMPLATES, template)
gp = get_ground_projection(robot_name)
# GroundProjectionGeometry
gpg = gp.get_ground_projection_geometry()
if pose_or_location.shape == (3, 3): # SE(2)
pose = pose_or_location
location = localization_template.coords_from_pose(pose)
else:
location = pose_or_location
pose = localization_template.pose_from_coords(location)
simulation_data = simulate_image(actual_map, pose, gpg, blur_sigma=0.3)
image = simulation_data.distorted_synthetic_bgr
# anti_instagram_name='identity' # skip
anti_instagram_name = 'baseline'
all_details = False
res, stats = run_pipeline(image,
gp,
line_detector_name=line_detector_name,
image_prep_name=image_prep_name,
lane_filter_name=lane_filter_name,
anti_instagram_name=anti_instagram_name,
all_details=all_details,
ground_truth=pose,
actual_map=actual_map)
error = np.empty_like(location)
for k in error.dtype.fields:
error[k] = stats['estimate'][k] - location[k]
stats['error'] = error
res = dtu.resize_small_images(res)
dtu.write_bgr_images_as_jpgs(res, outd, extra_string=outd.split('/')[-1])
return res, stats
def go(self):
output = self.options.output
if output is None:
output = 'out-pipeline' # + dtu.get_md5(self.options.image)[:6]
self.info('No --output given, using %s' % output)
if self.options.image is not None:
image_filename = self.options.image
if image_filename.startswith('http'):
image_filename = dtu.get_file_from_url(image_filename)
bgr = dtu.bgr_from_jpg_fn(image_filename)
else:
self.info('Taking a picture. Say cheese!')
out = os.path.join(output, 'frame.jpg')
bgr = dtu.bgr_from_raspistill(out)
self.info('Picture taken: %s ' % str(bgr.shape))
bgr = dtu.d8_image_resize_fit(bgr, 640)
self.info('Resized to: %s ' % str(bgr.shape))
vehicle_name = dtu.get_current_robot_name()
gp = GroundProjection(vehicle_name)
if False:
_res = run_pipeline(
bgr,
gp,
line_detector_name=self.options.line_detector,
image_prep_name=self.options.image_prep,
anti_instagram_name=self.options.anti_instagram,
lane_filter_name=self.options.lane_filter)
dtu.DuckietownConstants.show_timeit_benchmarks = True
res, _stats = run_pipeline(
bgr,
gp,
line_detector_name=self.options.line_detector,
image_prep_name=self.options.image_prep,
anti_instagram_name=self.options.anti_instagram,
lane_filter_name=self.options.lane_filter)
self.info('resizing')
res = dtu.resize_small_images(res)
self.info('writing')
dtu.write_bgr_images_as_jpgs(res, output)
def go(self):
robot_name = dtu.get_current_robot_name()
output = self.options.output
if output is None:
output = 'out-calibrate-extrinsics' # + dtu.get_md5(self.options.image)[:6]
self.info('No --output given, using %s' % output)
if self.options.input is None:
print("{}\nCalibrating using the ROS image stream...\n".format(
"*" * 20))
import rospy
from sensor_msgs.msg import CompressedImage
topic_name = os.path.join('/', robot_name,
'camera_node/image/compressed')
print('Topic to listen to is: %s' % topic_name)
print('Let\'s wait for an image. Say cheese!')
# Dummy for getting a ROS message
rospy.init_node('calibrate_extrinsics')
img_msg = None
try:
img_msg = rospy.wait_for_message(topic_name,
CompressedImage,
timeout=10)
print('Image captured!')
except rospy.ROSException as e:
print(
'\n\n\n'
'Didn\'t get any message!: %s\n '
'MAKE SURE YOU USE DT SHELL COMMANDS OF VERSION 4.1.9 OR HIGHER!'
'\n\n\n' % (e, ))
bgr = dtu.bgr_from_rgb(dtu.rgb_from_ros(img_msg))
print('Picture taken: %s ' % str(bgr.shape))
else:
print('Loading input image %s' % self.options.input)
bgr = dtu.bgr_from_jpg_fn(self.options.input)
if bgr.shape[1] != 640:
interpolation = cv2.INTER_CUBIC
bgr = dtu.d8_image_resize_fit(bgr, 640, interpolation)
print('Resized to: %s ' % str(bgr.shape))
# Disable the old calibration file
print("Disableing old homography")
disable_old_homography(robot_name)
print("Obtaining camera info")
try:
camera_info = get_camera_info_for_robot(robot_name)
except Exception as E:
print("Error on obtaining camera info!")
print(E)
print("Get default homography")
try:
homography_dummy = get_homography_default()
except Exception as E:
print("Error on getting homography")
print(E)
print("Rectify image")
try:
rect = Rectify(camera_info)
except Exception as E:
print("Error rectifying image!")
print(E)
print("Calculate GPG")
try:
gpg = GroundProjectionGeometry(camera_info.width,
camera_info.height,
homography_dummy.reshape((3, 3)))
except Exception as E:
print("Error calculating GPG!")
print(E)
print("Ordered Dict")
res = OrderedDict()
try:
bgr_rectified = rect.rectify(bgr, interpolation=cv2.INTER_CUBIC)
res['bgr'] = bgr
res['bgr_rectified'] = bgr_rectified
_new_matrix, res['rectified_full_ratio_auto'] = rect.rectify_full(
bgr, ratio=1.65)
(result_gpg, status) = gpg.estimate_homography(bgr_rectified)
if status is not None:
raise Exception(status)
save_homography(result_gpg.H, robot_name)
msg = '''
To check that this worked well, place the robot on the road, and run:
rosrun complete_image_pipeline single_image
Look at the produced jpgs.
'''
print(msg)
except Exception as E:
print(E)
finally:
dtu.write_bgr_images_as_jpgs(res, output)
def go(self):
robot_name = dtu.get_current_robot_name()
output = self.options.output
if output is None:
output = 'out-calibrate-extrinsics' # + dtu.get_md5(self.options.image)[:6]
self.info('No --output given, using %s' % output)
if self.options.input is None:
print("{}\nCalibrating using the ROS image stream...\n".format(
"*" * 20))
import rospy
from sensor_msgs.msg import CompressedImage
topic_name = os.path.join('/', robot_name,
'camera_node/image/compressed')
print('Topic to listen to is: %s' % topic_name)
print('Let\'s wait for an image. Say cheese!')
# Dummy for getting a ROS message
rospy.init_node('calibrate_extrinsics')
img_msg = None
try:
img_msg = rospy.wait_for_message(topic_name,
CompressedImage,
timeout=10)
print('Image captured!')
except rospy.ROSException as e:
print(
'\n\n\nDidn\'t get any message!: %s\n MAKE SURE YOU USE DT SHELL COMMANDS OF VERSION 4.1.9 OR HIGHER!\n\n\n'
% (e, ))
bgr = dtu.bgr_from_rgb(dtu.rgb_from_ros(img_msg))
self.info('Picture taken: %s ' % str(bgr.shape))
else:
self.info('Loading input image %s' % self.options.input)
bgr = dtu.bgr_from_jpg_fn(self.options.input)
if bgr.shape[1] != 640:
interpolation = cv2.INTER_CUBIC
bgr = dtu.d8_image_resize_fit(bgr, 640, interpolation)
self.info('Resized to: %s ' % str(bgr.shape))
# Disable the old calibration file
disable_old_homography(robot_name)
camera_info = get_camera_info_for_robot(robot_name)
homography_dummy = get_homography_default()
gpg = GroundProjectionGeometry(camera_info, homography_dummy)
res = OrderedDict()
try:
bgr_rectified = gpg.rectify(bgr, interpolation=cv2.INTER_CUBIC)
res['bgr'] = bgr
res['bgr_rectified'] = bgr_rectified
_new_matrix, res['rectified_full_ratio_auto'] = gpg.rectify_full(
bgr, ratio=1.65)
result = estimate_homography(bgr_rectified)
dtu.check_isinstance(result, HomographyEstimationResult)
if result.bgr_detected_refined is not None:
res['bgr_detected_refined'] = result.bgr_detected_refined
if not result.success:
raise Exception(result.error)
save_homography(result.H, robot_name)
msg = '''
To check that this worked well, place the robot on the road, and run:
rosrun complete_image_pipeline single_image
Look at the produced jpgs.
'''
self.info(msg)
finally:
dtu.write_bgr_images_as_jpgs(res, output)
def process_log(self, bag_in, prefix_in, bag_out, prefix_out,
utils): #@UnusedVariable
log_name = utils.get_log().log_name
vehicle_name = dtu.which_robot(bag_in)
dtu.logger.info('Vehicle name: %s' % vehicle_name)
gp = GroundProjection(vehicle_name)
topic = dtu.get_image_topic(bag_in)
bgcolor = dtu.ColorConstants.BGR_DUCKIETOWN_YELLOW
sequence = bag_in.read_messages_plus(topics=[topic])
for _i, mp in enumerate(sequence):
bgr = dtu.bgr_from_rgb(dtu.rgb_from_ros(mp.msg))
res, stats = run_pipeline(bgr,
gp=gp,
line_detector_name=self.line_detector,
image_prep_name=self.image_prep,
lane_filter_name=self.lane_filter,
anti_instagram_name=self.anti_instagram,
all_details=self.all_details)
rect = (480, 640) if not self.all_details else (240, 320)
res = dtu.resize_images_to_fit_in_rect(res, rect, bgcolor=bgcolor)
print('abs: %s window: %s fron log: %s' %
(mp.time_absolute, mp.time_window,
mp.time_from_physical_log_start))
headers = [
"Robot: %s log: %s time: %.2f s" %
(vehicle_name, log_name, mp.time_from_physical_log_start),
"Algorithms | color correction: %s | preparation: %s | detector: %s | filter: %s"
% (
self.anti_instagram,
self.image_prep,
self.line_detector,
self.lane_filter,
)
]
res = dtu.write_bgr_images_as_jpgs(res,
dirname=None,
bgcolor=bgcolor)
cv_image = res['all']
for head in reversed(headers):
max_height = 35
cv_image = dtu.add_header_to_bgr(cv_image,
head,
max_height=max_height)
otopic = "all"
omsg = dtu.d8_compressed_image_from_cv_image(
cv_image, same_timestamp_as=mp.msg)
t = rospy.Time.from_sec(mp.time_absolute) # @UndefinedVariable
print('written %r at t = %s' % (otopic, t.to_sec()))
bag_out.write(prefix_out + '/' + otopic, omsg, t=t)
for name, value in stats.items():
utils.write_stat(prefix_out + '/' + name, value, t=t)
