def circle_detector(ipc_push_url, pair_url, source_path, batch_size=20):
# ipc setup
import zmq
import zmq_tools
zmq_ctx = zmq.Context()
process_pipe = zmq_tools.Msg_Pair_Client(zmq_ctx, pair_url)
# logging setup
import logging
logging.getLogger("OpenGL").setLevel(logging.ERROR)
logger = logging.getLogger()
logger.handlers = []
logger.setLevel(logging.INFO)
logger.addHandler(zmq_tools.ZMQ_handler(zmq_ctx, ipc_push_url))
# create logger for the context of this function
logger = logging.getLogger(__name__)
# imports
from time import sleep
from video_capture import File_Source, EndofVideoError
from circle_detector import CircleTracker
try:
# TODO: we need fill_gaps=True for correct frame indices to paint the circle
# markers on the world stream. But actually we don't want to process gap frames
# with the marker detector. We should make an option to only receive non-gap
# frames, but with gap-like indices?
src = File_Source(SimpleNamespace(),
source_path,
timing=None,
fill_gaps=True)
frame = src.get_frame()
logger.info("Starting calibration marker detection...")
frame_count = src.get_frame_count()
queue = []
circle_tracker = CircleTracker()
while True:
while process_pipe.new_data:
topic, n = process_pipe.recv()
if topic == "terminate":
process_pipe.send({
"topic": "exception",
"reason": "User terminated."
})
logger.debug("Process terminated")
sleep(1.0)
return
progress = 100.0 * frame.index / frame_count
markers = [
m for m in circle_tracker.update(frame.gray)
if m["marker_type"] == "Ref"
]
if len(markers):
ref = {
"norm_pos": markers[0]["norm_pos"],
"screen_pos": markers[0]["img_pos"],
"timestamp": frame.timestamp,
"index_range":
tuple(range(frame.index - 5, frame.index + 5)),
"index": frame.index,
}
queue.append((progress, ref))
else:
queue.append((progress, None))
if len(queue) > batch_size:
# dequeue batch
data = queue[:batch_size]
del queue[:batch_size]
process_pipe.send({"topic": "progress", "data": data})
frame = src.get_frame()
except EndofVideoError:
process_pipe.send({"topic": "progress", "data": queue})
process_pipe.send({"topic": "finished"})
logger.debug("Process finished")
except Exception:
import traceback
process_pipe.send({
"topic": "exception",
"reason": traceback.format_exc()
})
logger.debug("Process raised Exception")
sleep(1.0)
def circle_detector(ipc_push_url, pair_url, source_path, batch_size=20):
# ipc setup
import zmq
import zmq_tools
zmq_ctx = zmq.Context()
process_pipe = zmq_tools.Msg_Pair_Client(zmq_ctx, pair_url)
# logging setup
import logging
logging.getLogger("OpenGL").setLevel(logging.ERROR)
logger = logging.getLogger()
logger.handlers = []
logger.setLevel(logging.INFO)
logger.addHandler(zmq_tools.ZMQ_handler(zmq_ctx, ipc_push_url))
# create logger for the context of this function
logger = logging.getLogger(__name__)
# imports
import cv2
from time import sleep
from circle_detector import find_concetric_circles
from video_capture import File_Source, EndofVideoFileError
from methods import normalize
try:
src = File_Source(Empty(), source_path, timed_playback=False)
frame = src.get_frame()
logger.info('Starting calibration marker detection...')
frame_count = src.get_frame_count()
queue = []
while True:
while process_pipe.new_data:
topic, n = process_pipe.recv()
if topic == 'terminate':
process_pipe.send(topic='exception',
payload={"reason": "User terminated."})
logger.debug("Process terminated")
sleep(1.0)
return
progress = 100. * frame.index / frame_count
markers = find_concetric_circles(frame.gray, min_ring_count=3)
if len(markers) > 0:
detected = True
marker_pos = markers[0][0][
0] # first marker innermost ellipse, pos
pos = normalize(marker_pos, (frame.width, frame.height),
flip_y=True)
else:
detected = False
pos = None
if detected:
second_ellipse = markers[0][1]
col_slice = int(second_ellipse[0][0] - second_ellipse[1][0] /
2), int(second_ellipse[0][0] +
second_ellipse[1][0] / 2)
row_slice = int(second_ellipse[0][1] - second_ellipse[1][1] /
2), int(second_ellipse[0][1] +
second_ellipse[1][1] / 2)
marker_gray = frame.gray[slice(*row_slice), slice(*col_slice)]
avg = cv2.mean(marker_gray)[0]
center = marker_gray[int(second_ellipse[1][1]) // 2,
int(second_ellipse[1][0]) // 2]
rel_shade = center - avg
ref = {}
ref["norm_pos"] = pos
ref["screen_pos"] = marker_pos
ref["timestamp"] = frame.timestamp
ref['index'] = frame.index
if rel_shade > 30:
ref['type'] = 'stop_marker'
else:
ref['type'] = 'calibration_marker'
queue.append((progress, ref))
else:
queue.append((progress, None))
if len(queue) > batch_size:
# dequeue batch
data = queue[:batch_size]
del queue[:batch_size]
process_pipe.send(topic='progress', payload={'data': data})
frame = src.get_frame()
except EndofVideoFileError:
process_pipe.send(topic='progress', payload={'data': queue})
process_pipe.send(topic='finished', payload={})
logger.debug("Process finished")
except:
import traceback
process_pipe.send(topic='exception',
payload={'reason': traceback.format_exc()})
logger.debug("Process raised Exception")
sleep(1.0)
def circle_detector(ipc_push_url, pair_url, source_path, batch_size=20):
# ipc setup
import zmq
import zmq_tools
zmq_ctx = zmq.Context()
process_pipe = zmq_tools.Msg_Pair_Client(zmq_ctx, pair_url)
# logging setup
import logging
logging.getLogger("OpenGL").setLevel(logging.ERROR)
logger = logging.getLogger()
logger.handlers = []
logger.setLevel(logging.INFO)
logger.addHandler(zmq_tools.ZMQ_handler(zmq_ctx, ipc_push_url))
# create logger for the context of this function
logger = logging.getLogger(__name__)
# imports
from time import sleep
from video_capture import File_Source, EndofVideoFileError
from circle_detector import CircleTracker
try:
src = File_Source(Empty(), source_path, timed_playback=False)
frame = src.get_frame()
logger.info('Starting calibration marker detection...')
frame_count = src.get_frame_count()
queue = []
circle_tracker = CircleTracker()
while True:
while process_pipe.new_data:
topic, n = process_pipe.recv()
if topic == 'terminate':
process_pipe.send(topic='exception',
payload={"reason": "User terminated."})
logger.debug("Process terminated")
sleep(1.0)
return
progress = 100. * frame.index / frame_count
markers = [
m for m in circle_tracker.update(frame.gray)
if m['marker_type'] == 'Ref'
]
if len(markers):
ref = {
"norm_pos": markers[0]['norm_pos'],
"screen_pos": markers[0]['img_pos'],
"timestamp": frame.timestamp,
'index': frame.index
}
queue.append((progress, ref))
else:
queue.append((progress, None))
if len(queue) > batch_size:
# dequeue batch
data = queue[:batch_size]
del queue[:batch_size]
process_pipe.send(topic='progress', payload={'data': data})
frame = src.get_frame()
except EndofVideoFileError:
process_pipe.send(topic='progress', payload={'data': queue})
process_pipe.send(topic='finished', payload={})
logger.debug("Process finished")
except Exception:
import traceback
process_pipe.send(topic='exception',
payload={'reason': traceback.format_exc()})
logger.debug("Process raised Exception")
sleep(1.0)
def circle_detector(ipc_push_url, pair_url,
source_path, timestamps_path, batch_size=20):
# ipc setup
import zmq
import zmq_tools
zmq_ctx = zmq.Context()
process_pipe = zmq_tools.Msg_Pair_Client(zmq_ctx, pair_url)
# logging setup
import logging
logging.getLogger("OpenGL").setLevel(logging.ERROR)
logger = logging.getLogger()
logger.handlers = []
logger.setLevel(logging.INFO)
logger.addHandler(zmq_tools.ZMQ_handler(zmq_ctx, ipc_push_url))
# create logger for the context of this function
logger = logging.getLogger(__name__)
# imports
import cv2
import numpy as np
from time import sleep
from circle_detector import find_concetric_circles
from video_capture import File_Source, EndofVideoFileError
from methods import normalize
try:
src = File_Source(Empty(), source_path, np.load(timestamps_path), timed_playback=False)
frame = src.get_frame()
logger.info('Starting calibration marker detection...')
frame_count = src.get_frame_count()
queue = []
while True:
while process_pipe.new_data:
topic, n = process_pipe.recv()
if topic == 'terminate':
process_pipe.send(topic='exception', payload={"reason": "User terminated."})
logger.debug("Process terminated")
sleep(1.0)
return
progress = 100.*frame.index/frame_count
markers = find_concetric_circles(frame.gray, min_ring_count=3)
if len(markers) > 0:
detected = True
marker_pos = markers[0][0][0] # first marker innermost ellipse, pos
pos = normalize(marker_pos, (frame.width, frame.height), flip_y=True)
else:
detected = False
pos = None
if detected:
second_ellipse = markers[0][1]
col_slice = int(second_ellipse[0][0]-second_ellipse[1][0]/2), int(second_ellipse[0][0]+second_ellipse[1][0]/2)
row_slice = int(second_ellipse[0][1]-second_ellipse[1][1]/2), int(second_ellipse[0][1]+second_ellipse[1][1]/2)
marker_gray = frame.gray[slice(*row_slice), slice(*col_slice)]
avg = cv2.mean(marker_gray)[0]
center = marker_gray[int(second_ellipse[1][1])//2, int(second_ellipse[1][0])//2]
rel_shade = center-avg
ref = {}
ref["norm_pos"] = pos
ref["screen_pos"] = marker_pos
ref["timestamp"] = frame.timestamp
ref['index'] = frame.index
if rel_shade > 30:
ref['type'] = 'stop_marker'
else:
ref['type'] = 'calibration_marker'
queue.append((progress, ref))
else:
queue.append((progress, None))
if len(queue) > batch_size:
# dequeue batch
data = queue[:batch_size]
del queue[:batch_size]
process_pipe.send(topic='progress', payload={'data': data})
frame = src.get_frame()
except EndofVideoFileError:
process_pipe.send(topic='progress', payload={'data': queue})
process_pipe.send(topic='finished', payload={})
logger.debug("Process finished")
except:
import traceback
process_pipe.send(topic='exception', payload={'reason': traceback.format_exc()})
logger.debug("Process raised Exception")
sleep(1.0)