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()
# noinspection PyUnresolvedReferences
output = self.options.output
if output is None:
output = "out/pipeline" # + dtu.get_md5(self.options.image)[:6]
self.info(f"No --output given, using {output}")
# noinspection PyUnresolvedReferences
opt_image = self.options.image
if opt_image is not None:
image_filename = opt_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("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")
self.info("Let's wait for an image. Say cheese!")
# Dummy to get ROS message
rospy.init_node("single_image")
try:
img_msg = cast(
CompressedImage,
rospy.wait_for_message(topic_name,
CompressedImage,
timeout=10))
self.info("Image captured")
except rospy.ROSException as e:
self.info(
f"\n\n\nDidn't get any message: {e}\n MAKE SURE YOU USE DT SHELL COMMANDS OF VERSION "
"4.1.9 OR HIGHER!\n\n\n")
raise
bgr = dtu.bgr_from_rgb(dru.rgb_from_ros(img_msg))
self.info(f"Picture taken: {str(bgr.shape)} ")
dtu.DuckietownConstants.show_timeit_benchmarks = True
res, _stats = run_pipeline(bgr)
self.info("Resizing images..")
res = dtu.resize_small_images(res)
self.info("Writing images..")
dtu.write_bgr_images_as_jpgs(res, output)
def look_at(
log,
output: str,
anti_instagram: str,
line_detector: str,
image_prep: str,
lane_filter: str,
all_details: bool,
) -> None:
filename = get_local_bag_file(log)
bag = rosbag.Bag(filename)
vehicle_name = dbu.which_robot(bag)
dtu.logger.info(f"Vehicle name: {vehicle_name}")
brp = dbu.BagReadProxy(bag)
rcg = get_robot_camera_geometry_from_log(brp)
topic = dbu.get_image_topic(bag)
res = dbu.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,
gpg=rcg.gpg,
rectifier=rcg.rectifier,
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 create_visuals(robots: List[str], actual_map_name: str, out: str):
db = get_easy_algo_db()
actual_map = db.create_instance(FAMILY_SEGMAPS, actual_map_name)
res = {}
res2 = {}
for i, robot_name in enumerate(sorted(robots)):
logger.info(f"{i}/{len(robots)}: {robot_name}")
rcg = get_robot_camera_geometry(robot_name)
pose = np.eye(3)
simulated_data = simulate_image(actual_map, pose, gpg=rcg.gpg, rectifier=rcg.rectifier, 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 go(self):
robot_name = dtu.get_current_robot_name()
# noinspection PyUnresolvedReferences
output = self.options.output
# noinspection PyUnresolvedReferences
the_input = self.options.input
if output is None:
output = "out/calibrate-extrinsics" # + dtu.get_md5(self.options.image)[:6]
self.info(f"No --output given, using {output}")
if the_input is None:
self.info(
("{}\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")
logger.info(f"Topic to listen to is: {topic_name}")
self.info("Let's wait for an image. Say cheese!")
# Dummy for getting a ROS message
rospy.init_node("calibrate_extrinsics")
try:
img_msg = rospy.wait_for_message(topic_name,
CompressedImage,
timeout=10)
self.info("Image captured")
except rospy.ROSException as e:
print((
"\n\n\n"
f"Didn't get any message: {e}\n "
"MAKE SURE YOU USE DT SHELL COMMANDS OF VERSION 4.1.9 OR HIGHER."
))
raise
img_msg = cast(CompressedImage, img_msg)
bgr = dtu.bgr_from_rgb(dru.rgb_from_ros(img_msg))
self.info(f"Picture taken: {str(bgr.shape)} ")
else:
self.info(f"Loading input image {the_input}")
bgr = dtu.bgr_from_jpg_fn(the_input)
if bgr.shape[1] != 640:
interpolation = cv2.INTER_CUBIC
bgr = dtu.d8_image_resize_fit(bgr, 640, interpolation)
self.info(f"Resized to: {str(bgr.shape)} ")
# Disable the old calibration file
self.info("Disableing old homography")
disable_old_homography(robot_name)
self.info("Obtaining camera info")
try:
camera_info = get_camera_info_for_robot(robot_name)
except Exception as e:
msg = "Error on obtaining camera info."
raise Exception(msg) from e
self.info("Get default homography")
try:
homography_dummy = get_homography_default()
except Exception as e:
msg = "Error on getting homography."
raise Exception(msg) from e
self.info("Rectify image")
try:
rect = Rectify(camera_info)
except Exception as e:
msg = "Error rectifying image."
raise Exception(msg) from e
self.info("Calculate GPG")
try:
gpg = GroundProjectionGeometry(camera_info.width,
camera_info.height,
homography_dummy.reshape((3, 3)))
except Exception as e:
msg = "Error calculating GroundProjectionGeometry."
raise Exception(msg) from e
self.info("Ordered Dict")
res = {}
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.
"""
self.info(msg)
except Exception as E:
self.error(E)
finally:
dtu.write_bgr_images_as_jpgs(res, output)
def test_synthetic(
actual_map_name: str,
template,
robot_name: str,
line_detector_name: str,
image_prep_name: str,
lane_filter_name: str,
pose_or_location,
outd: str,
seed: int = 42,
) -> Tuple[object, object]:
np.random.seed(seed)
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(f"looking for localization template {template!r}")
localization_template = easy_algo_db.create_instance(
FAMILY_LOC_TEMPLATES, template)
rcg = get_robot_camera_geometry(robot_name)
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=rcg.gpg,
rectifier=rcg.rectifier,
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,
gpg=rcg.gpg,
rectifier=rcg.rectifier,
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 process_log(
self,
bag_in: dbu.BagReadProxy,
prefix_in: str,
bag_out,
prefix_out: str,
utils: ProcessorUtilsInterface,
):
log_name = utils.get_log().log_name
vehicle_name = dbu.which_robot(bag_in)
logger.info(f"Vehicle name: {vehicle_name}")
topic = dbu.get_image_topic(bag_in)
rcg = get_robot_camera_geometry_from_log(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(dru.rgb_from_ros(mp.msg))
res, stats = run_pipeline(
bgr,
gpg=rcg.gpg,
rectifier=rcg.rectifier,
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)
msg = (
f"abs: {mp.time_absolute} window: {mp.time_window} from log: "
f"{mp.time_from_physical_log_start}")
dtu.logger.info(msg)
headers = [
f"Robot: {vehicle_name} log: {log_name} time: {mp.time_from_physical_log_start:.2f} s",
f"Algorithms | color correction: {self.anti_instagram} | preparation: {self.image_prep} | "
f"detector: {self.line_detector} | filter: {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 = dru.d8_compressed_image_from_cv_image(
cv_image, same_timestamp_as=mp.msg)
t = rospy.Time.from_sec(mp.time_absolute)
dtu.logger.info(f"written {otopic!r} at t = {t.to_sec()}")
bag_out.write(prefix_out + "/" + otopic, omsg, t=t)
for name, value in list(stats.items()):
utils.write_stat(prefix_out + "/" + name, value, t=t)