def __init__(self):
self.current_profile_dxf = []
Cad.__init__(self)
try:
opts, args = getopt.getopt(sys.argv[1:], "h", ["help"])
except getopt.error, msg:
print msg
print "for help use --help"
sys.exit(2)
def __init__(self):
save_out = sys.stdout
save_err = sys.stderr
wx.App.__init__(self)
sys.stdout = save_out
sys.stderr = save_err
Cad.__init__(self)
heekscad.init()
try:
opts, args = getopt.getopt(sys.argv[1:], "h", ["help"])
except getopt.error, msg:
print msg
print "for help use --help"
sys.exit(2)
def __init__(self):
save_out = sys.stdout
save_err = sys.stderr
wx.App.__init__(self)
sys.stdout = save_out
sys.stderr = save_err
Cad.__init__(self)
heekscad.init()
try:
opts, args = getopt.getopt(sys.argv[1:], "h", ["help"])
except getopt.error, msg:
print msg
print "for help use --help"
sys.exit(2)
def generate_video_traffic(job):
''' Generate traffic file for the whole video.
Args:
in_db_file - should have all the images for which traffic is generated
job - the same as for process_video
'''
assertParamIsThere(job, 'in_db_file')
assertParamIsThere(job, 'out_video_dir')
setParamUnlessThere(job, 'frame_range', '[::]')
assertParamIsThere(job, 'video_dir')
video = Video(video_dir=job['video_dir'])
camera = video.build_camera()
assert op.exists(atcity(job['in_db_file'])), \
'in db %s does not exist' % atcity(job['in_db_file'])
conn_in = sqlite3.connect(atcity(job['in_db_file']))
c_in = conn_in.cursor()
c_in.execute('SELECT time FROM images')
timestamps = c_in.fetchall()
conn_in.close()
cad = Cad()
if 'speed_kph' in job:
model = TrafficModel(camera,
video,
cad=cad,
speed_kph=job['speed_kph'])
elif 'num_cars' in job:
model = TrafficModelRandom(camera,
video,
cad=cad,
num_cars_mean=job['num_cars'])
else:
assert False
diapason = Diapason(len(timestamps), job['frame_range'])
traffic = {'in_db_file': job['in_db_file']}
traffic['frames'] = []
for frame_id in diapason.frame_range:
logging.info('generating traffic for frame %d' % frame_id)
timestamp = timestamps[frame_id][0]
time = parseTimeString(timestamp)
traffic_frame = model.get_next_frame(time)
traffic_frame['frame_id'] = frame_id # for validating
traffic['frames'].append(traffic_frame)
return traffic
if __name__ == "__main__":
setupLogging('log/augmentation/traffic.log', logging.DEBUG, 'w')
video_dir = 'augmentation/scenes/cam166/Feb23-09h'
collection_names = [
'7c7c2b02ad5108fe5f9082491d52810',
'uecadcbca-a400-428d-9240-a331ac5014f6'
]
timestamp = datetime.now()
video = Video(video_dir)
camera = video.build_camera()
cad = Cad(collection_names)
#model = TrafficModel (camera, video, cad=cad, speed_kph=10, burn_in=True)
model = TrafficModelRandom(camera, video, cad, num_cars_mean=10)
# cv2.imshow('lanesmap', model.generate_map())
# cv2.waitKey(-1)
while True:
model.get_next_frame(timestamp)
display = fit_image_to_screen(model.generate_map())
cv2.imshow('lanesmap', display)
key = cv2.waitKey(-1)
if key == 27: break
# traffic_path = op.join(WORK_RENDER_DIR, TRAFFIC_FILENAME)
# with open(traffic_path, 'w') as f:
def process_video(job):
assertParamIsThere(job, 'video_dir')
video = Video(video_dir=job['video_dir'])
camera = video.build_camera()
# some parameters
assertParamIsThere(job, 'traffic_file')
setParamUnlessThere(job, 'save_blender_files', False)
setParamUnlessThere(
job, 'out_video_dir',
op.join('augmentation/video', 'cam%s' % camera.info['cam_id'],
video.info['video_name']))
setParamUnlessThere(job, 'no_annotations', False)
setParamUnlessThere(job, 'timeout', 1000000000)
setParamUnlessThere(job, 'frame_range', '[::]')
setParamUnlessThere(job, 'save_blender_files', False)
job['render_individual_cars'] = not job['no_annotations']
# load camera dimensions (compare it to everything for extra safety)
width0 = camera.info['camera_dims']['width']
height0 = camera.info['camera_dims']['height']
# for checking timeout
start_time = datetime.now()
cad = Cad()
# upload info on parsed vehicles to the monitor server
monitor = None # MonitorDatasetClient (cam_id=camera.info['cam_id'])
# load traffic info
traffic_video = json.load(open(atcadillac(job['traffic_file'])))
# reader and writer
video_reader = ReaderVideo()
image_vfile = op.join(job['out_video_dir'], 'image.avi')
mask_vfile = op.join(job['out_video_dir'], 'mask.avi')
video_writer = SimpleWriter(image_vfile, mask_vfile, {'unsafe': True})
(conn, c) = dbInit(traffic_video['in_db_file'],
op.join(job['out_video_dir'], 'traffic.db'))
c.execute('SELECT imagefile,maskfile,width,height,time FROM images')
image_entries = c.fetchall()
c.execute('DELETE FROM images')
#assert len(traffic_video['frames']) >= len(image_entries), \
# 'traffic json is too small %d < %d' % (len(traffic_video['frames']), len(image_entries))
diapason = Diapason(len(image_entries), job['frame_range'])
num_processes = int(multiprocessing.cpu_count() / 2 + 1)
pool = multiprocessing.Pool(processes=num_processes)
# each frame_range chunk is processed in parallel
for frame_range in diapason.frame_range_as_chunks(pool._processes):
logging.info('chunk of frames %d to %d' %
(frame_range[0], frame_range[-1]))
# quit, if reached the timeout
time_passed = datetime.now() - start_time
logging.info('passed: %s' % time_passed)
if (time_passed.total_seconds() > job['timeout'] * 60):
logging.warning('reached timeout %d. Passed %s' %
(job['timeout'], time_passed))
break
# collect frame jobs
frame_jobs = []
for frame_id in frame_range:
(in_backfile, in_maskfile, width, height,
_) = image_entries[frame_id]
assert (width0 == width
and height0 == height), (width0, width, height0, height)
logging.info('collect job for frame number %d' % frame_id)
back = video_reader.imread(in_backfile)
traffic = traffic_video['frames'][frame_id]
assert traffic['frame_id'] == frame_id, '%d vs %d' % (
traffic['frame_id'], frame_id)
traffic['save_blender_files'] = job['save_blender_files']
frame_jobs.append((video, camera, traffic, back, job))
#for i, (out_image, out_mask, work_dir) in enumerate(sequentialworker(frame_jobs)):
for i, (out_image, out_mask,
work_dir) in enumerate(pool.imap(worker, frame_jobs)):
frame_id = frame_range[i]
logging.info('processed frame number %d' % frame_id)
assert out_image is not None and out_mask is not None
out_imagefile = video_writer.imwrite(out_image)
out_maskfile = video_writer.maskwrite(out_mask)
logging.info('out_imagefile: %s, out_maskfile: %s' %
(out_imagefile, out_maskfile))
# update out database
(_, _, width, height, time) = image_entries[frame_id]
c.execute(
'INSERT INTO images(imagefile,maskfile,width,height,time) VALUES (?,?,?,?,?)',
(out_imagefile, out_maskfile, width, height, time))
logging.info('wrote frame %d' % c.lastrowid)
if not job['no_annotations']:
extract_annotations(work_dir, c, cad, camera, out_imagefile,
monitor)
if not job['save_blender_files']:
shutil.rmtree(work_dir)
conn.commit()
conn.close()
pool.close()
pool.join()
