def get_messages(broker: str, topic: str):
consumer = TimeOrderedGeneratorWithTimeout(broker,
"list_messages", [
TopicInfo(topic),
],
100,
None,
True,
begin_flag=BeginFlag.BEGINNING)
ret = consumer.getMessage()
return ret
def main():
parser = argparse.ArgumentParser(
epilog="""Description:
Plays video from a jpeg topic, visualizes main points of a human skeleton linked with colorful lines.
Displays the result on screen ('-d') or stores in a kafka topic with '-o' parameter.
Required topics:
- <prefix>.cam.0.lowres.Image.jpg
- <prefix>.cam.0.skeletons.SkeletonRecord.json
""",
formatter_class=argparse.RawTextHelpFormatter)
parser.add_argument("broker",
help="The name of the kafka broker.",
type=str)
parser.add_argument("prefix",
help="Prefix of topics (base|skeleton).",
type=str)
parser.add_argument('-f', "--full_screen", action='store_true')
parser.add_argument('-d', "--display", action='store_true')
parser.add_argument('-o',
'--output',
help='write output image into kafka topic',
action='store_true')
args = parser.parse_args()
if not args.display and not args.output:
parser.error(
"Missing argument: -d (display output) or -o (write output to kafka) is needed"
)
if args.output:
producer = Producer({'bootstrap.servers': args.broker})
overlay = cv2.imread('resources/powered_by_white.png',
cv2.IMREAD_UNCHANGED)
img_topic = f"{args.prefix}.cam.0.lowres.Image.jpg"
skeleton_topic = f"{args.prefix}.cam.0.skeletons.SkeletonRecord.json"
output_topic_name = f"{args.prefix}.cam.0.skeleton.Image.jpg"
# handle full screen
window_name = "DEMO: Human skeleton"
if args.full_screen:
cv2.namedWindow(window_name, cv2.WINDOW_NORMAL)
cv2.setWindowProperty(window_name, cv2.WND_PROP_FULLSCREEN,
cv2.WINDOW_FULLSCREEN)
# read message, draw and display them
consumer = TimeOrderedGeneratorWithTimeout(
args.broker, "skeleton",
[TopicInfo(img_topic), TopicInfo(skeleton_topic)], 100, None, True)
i = 0
for msgs in consumer.getMessage():
for time, v in message_list_to_frame_structure(msgs).items():
img = v[args.prefix]["0"]["image"]
if type(img) == np.ndarray:
# draw skeletons
for skeleton_id, skeleton in v[
args.prefix]["0"]["skeleton"].items():
img = draw_skeleton_with_background(
img, skeleton["points"])
# draw ultinous logo
img = draw_overlay(img, overlay, Position.BOTTOM_RIGHT)
# produce output topic
if args.output:
producer.produce(output_topic_name,
value=encode_image_to_message(img),
timestamp=time)
producer.poll(0)
if i % 100 == 0:
producer.flush()
i += 1
# display
if args.display:
cv2.imshow(window_name, img)
k = cv2.waitKey(33)
if k == 113: # The 'q' key to stop
break
elif k == -1: # normally -1 returned,so don't print it
continue
else:
print(f"Press 'q' key for EXIT!")
def main():
parser = argparse.ArgumentParser(
epilog="""Description:
Plays a video from a jpeg topic, visualizes the head detections and tracks.
Displays the result on screen ('-d') or stores result in kafka ('-o').
Required topics:
- <prefix>.cam.0.lowres.Image.jpg
- <prefix>.cam.0.dets.ObjectDetectionRecord.json
- <prefix>.cam.0.tracks.TrackChangeRecord.json
""",
formatter_class=argparse.RawTextHelpFormatter)
parser.add_argument("broker",
help="The name of the kafka broker.",
type=str)
parser.add_argument("prefix",
help="Prefix of topics (base|skeleton).",
type=str)
parser.add_argument('-f', "--full_screen", action='store_true')
parser.add_argument('-d', "--display", action='store_true')
parser.add_argument('-o',
'--output',
help='write output image into kafka topic',
action='store_true')
args = parser.parse_args()
if not args.display and not args.output:
parser.error(
"Missing argument: -d (display output) or -o (write output to kafka) is needed"
)
if args.output:
producer = Producer({'bootstrap.servers': args.broker})
overlay = cv2.imread('resources/powered_by_white.png',
cv2.IMREAD_UNCHANGED)
image_topic = f"{args.prefix}.cam.0.lowres.Image.jpg"
detection_topic = f"{args.prefix}.cam.0.dets.ObjectDetectionRecord.json"
track_topic = f"{args.prefix}.cam.0.tracks.TrackChangeRecord.json"
output_topic_name = f"{args.prefix}.cam.0.tracks.Image.jpg"
# handle full screen
window_name = "DEMO: Head detection"
if args.full_screen:
cv2.namedWindow(window_name, cv2.WINDOW_NORMAL)
cv2.setWindowProperty(window_name, cv2.WND_PROP_FULLSCREEN,
cv2.WINDOW_FULLSCREEN)
# read message, draw and display them
consumer = TimeOrderedGeneratorWithTimeout(args.broker, "detection", [
TopicInfo(image_topic),
TopicInfo(track_topic, drop=False),
TopicInfo(detection_topic)
], 100, None, True)
i = 0
tracks: DefaultDict[Any, Track] = defaultdict(lambda: Track(next(colors)))
for msgs in consumer.getMessage():
for time, v in message_list_to_frame_structure(msgs).items():
for track_key, track_val in v[args.prefix]["0"]["track"].items():
if track_val["end_of_track"]:
if track_key in tracks:
del tracks[track_key]
continue
point = track_val["point"]["x"], track_val["point"]["y"]
tracks[track_key].add_point(point)
img = v[args.prefix]["0"]["image"]
if type(img) == np.ndarray:
# draw bounding_box
for head_detection in v[args.prefix]["0"]["head_detection"]:
object_detection_record = v[args.prefix]["0"][
"head_detection"][head_detection]["bounding_box"]
if object_detection_record["type"] == "PERSON_HEAD":
img = draw_nice_bounding_box(
img, object_detection_record["bounding_box"],
(10, 95, 255))
for t_key, t in tracks.items():
cv2.polylines(img=img,
pts=[np.array(t.points, np.int32)],
isClosed=False,
color=t.color,
thickness=3)
# draw ultinous logo
img = draw_overlay(img, overlay, Position.BOTTOM_RIGHT)
# produce output topic
if args.output:
producer.produce(output_topic_name,
value=encode_image_to_message(img),
timestamp=time)
producer.poll(0)
if i % 100 == 0:
producer.flush()
i = 0
i += 1
# display
if args.display:
cv2.imshow(window_name, img)
k = cv2.waitKey(33)
if k == 113: # The 'q' key to stop
break
elif k == -1: # normally -1 returned,so don't print it
continue
else:
print(f"Press 'q' key for EXIT!")
def main():
parser = argparse.ArgumentParser(
epilog=
"""Description:
Plays a video from a jpeg topic,
visualizes the head detection with an orage bounding box around a head
and writes demography data (gender & age) data above the heads.
Displays ('-d') or stores ('-o') the result of this demo in the kafka topic.
Required topics:
- <prefix>.cam.0.lowres.Image.jpg
- <prefix>.cam.0.dets.ObjectDetectionRecord.json
- <prefix>.cam.0.genders.GenderRecord.json
- <prefix>.cam.0.ages.AgeRecord.json
"""
, formatter_class=argparse.RawTextHelpFormatter
)
parser.add_argument("broker", help="The name of the kafka broker.", type=str)
parser.add_argument("prefix", help="Prefix of topics (base|skeleton).", type=str)
parser.add_argument('-f', "--full_screen", action='store_true')
parser.add_argument('-d', "--display", action='store_true')
parser.add_argument('-o', '--output', help='write output image into kafka topic', action='store_true')
args = parser.parse_args()
if not args.display and not args.output:
parser.error("Missing argument: -d (display output) or -o (write output to kafka) is needed")
if args.output:
producer = Producer({'bootstrap.servers': args.broker})
overlay = cv2.imread('resources/powered_by_white.png', cv2.IMREAD_UNCHANGED)
image_topic = f"{args.prefix}.cam.0.lowres.Image.jpg"
detection_topic = f"{args.prefix}.cam.0.dets.ObjectDetectionRecord.json"
gender_topic = f"{args.prefix}.cam.0.genders.GenderRecord.json"
age_topic = f"{args.prefix}.cam.0.ages.AgeRecord.json"
output_topic_name = f"{args.prefix}.cam.0.demography.Image.jpg"
# handle full screen
window_name = "DEMO: Demography (gender & age)"
if args.full_screen:
cv2.namedWindow(window_name, cv2.WINDOW_NORMAL)
cv2.setWindowProperty(window_name, cv2.WND_PROP_FULLSCREEN, cv2.WINDOW_FULLSCREEN)
# read message, draw and display them
consumer = TimeOrderedGeneratorWithTimeout(
args.broker,
"detection",
[
TopicInfo(image_topic),
TopicInfo(detection_topic),
TopicInfo(gender_topic),
TopicInfo(age_topic),
],
100,
None,
True
)
i = 0
for msgs in consumer.getMessage():
for time, v in message_list_to_frame_structure(msgs).items():
img = v[args.prefix]["0"]["image"]
if type(img) == np.ndarray:
for head_detection in v[args.prefix]["0"]["head_detection"]:
object_detection_record = v[args.prefix]["0"]["head_detection"][head_detection]["bounding_box"]
age_record = v[args.prefix]["0"]["head_detection"][head_detection]["age"]
gender_record = v[args.prefix]["0"]["head_detection"][head_detection]["gender"]
age = "" if age_record['age'] == {} else age_record['age']
gender = "" if gender_record['gender'] == {} else gender_record['gender']
# draw bounding_box
img = draw_nice_bounding_box(
img,
object_detection_record["bounding_box"],
(10, 95, 255)
)
# write age and gender
img = draw_nice_text(
img,
str(gender) + " " + str(age),
object_detection_record["bounding_box"],
(10, 95, 255)
)
# draw ultinous logo
img = draw_overlay(img, overlay, Position.BOTTOM_RIGHT)
# produce output topic
if args.output:
producer.produce(output_topic_name, value=encode_image_to_message(img), timestamp=time)
producer.poll(0)
if i % 100 == 0:
producer.flush()
i += 1
# display
if args.display:
cv2.imshow(window_name, img)
k = cv2.waitKey(33)
if k == 113: # The 'q' key to stop
break
elif k == -1: # normally -1 returned,so don't print it
continue
else:
print(f"Press 'q' key for EXIT!")
def main():
parser = argparse.ArgumentParser(
epilog="""Description:
Plays video from a jpeg topic, and visualize the head pose records with 3 diff color lines.
[see: The yaw, pitch, and roll angles in the human head motion]
Displays ('-d') or stores ('-o') the result of this demo in the kafka topic.
Required topics:
- <prefix>.cam.0.lowres.Image.jpg
- <prefix>.cam.0.dets.ObjectDetectionRecord.json
- <prefix>.cam.0.poses.HeadPose3DRecord.json
""",
formatter_class=argparse.RawTextHelpFormatter)
parser.add_argument("broker",
help="The name of the kafka broker.",
type=str)
parser.add_argument("prefix",
help="Prefix of topics (base|skeleton).",
type=str)
parser.add_argument('-f', "--full_screen", action='store_true')
parser.add_argument('-d', "--display", action='store_true')
parser.add_argument('-o',
'--output',
help='write output image into kafka topic',
action='store_true')
args = parser.parse_args()
if not args.display and not args.output:
parser.error(
"Missing argument: -d (display output) or -o (write output to kafka) is needed"
)
if args.output:
producer = Producer({'bootstrap.servers': args.broker})
overlay = cv2.imread('resources/powered_by_white.png',
cv2.IMREAD_UNCHANGED)
image_topic = f"{args.prefix}.cam.0.lowres.Image.jpg"
detection_topic = f"{args.prefix}.cam.0.dets.ObjectDetectionRecord.json"
pose_topic = f"{args.prefix}.cam.0.poses.HeadPose3DRecord.json"
output_topic_name = f"{args.prefix}.cam.0.head_pose.Image.jpg"
# handle full screen
window_name = "DEMO: Head pose"
if args.full_screen:
cv2.namedWindow(window_name, cv2.WINDOW_NORMAL)
cv2.setWindowProperty(window_name, cv2.WND_PROP_FULLSCREEN,
cv2.WINDOW_FULLSCREEN)
# read message, draw and display them
consumer = TimeOrderedGeneratorWithTimeout(args.broker, "detection", [
TopicInfo(image_topic),
TopicInfo(detection_topic),
TopicInfo(pose_topic),
], 100, None, True)
i = 0
for msgs in consumer.getMessage():
for time, v in message_list_to_frame_structure(msgs).items():
img = v[args.prefix]["0"]["image"]
if type(img) == np.ndarray:
# draw bounding_box
for head_detection in v[args.prefix]["0"]["head_detection"]:
object_detection_record = v[args.prefix]["0"][
"head_detection"][head_detection]["bounding_box"]
if object_detection_record["type"] == "PERSON_HEAD":
pose_record = v[args.prefix]["0"]["head_detection"][
head_detection]["head_pose"]
if "pose" in pose_record:
img = draw_head_pose(
img,
pose_record["pose"],
object_detection_record["bounding_box"],
)
# draw ultinous logo
img = draw_overlay(img, overlay, Position.BOTTOM_RIGHT)
# produce output topic
if args.output:
producer.produce(output_topic_name,
value=encode_image_to_message(img),
timestamp=time)
producer.poll(0)
if i % 100 == 0:
producer.flush()
i += 1
# display
if args.display:
cv2.imshow(window_name, img)
k = cv2.waitKey(33)
if k == 113: # The 'q' key to stop
break
elif k == -1: # normally -1 returned,so don't print it
continue
else:
print(f"Press 'q' key for EXIT!")