def main(): # pragma: no cover
parser = argparse.ArgumentParser(
prog='BeesBook pipeline batch processor',
description='Batch process video using the beesbook pipeline')
parser.add_argument('video_root_path', help='root path of input videos', type=str)
for arg, kwargs in chain(get_shared_positional_arguments(), get_shared_optional_arguments()):
parser.add_argument(arg, **kwargs)
args = parser.parse_args()
pipeline_cmd = None
if os.path.exists(os.path.join(os.getcwd(), 'bb_pipeline')):
pipeline_cmd = os.path.join(os.getcwd(), 'bb_pipeline')
else:
pipeline_cmd = shutil.which('bb_pipeline')
assert(pipeline_cmd is not None)
video_files = []
for root, dirs, files in os.walk(args.video_root_path):
for file in files:
video_files.append(os.path.join(root, file))
logger.info('Processing files: \n\t{}'.format('\n\t'.join(video_files)))
for fname in video_files:
cmd_args = [fname] + \
list([args.__dict__[param] for param, _ in get_shared_positional_arguments()])
for param, _ in get_shared_optional_arguments():
if param[2:] in args.__dict__:
cmd_args.append(param)
cmd_args.append(str(args.__dict__[param[2:]]))
call([pipeline_cmd] + cmd_args)
def main(): # pragma: no cover
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
if 'PIPELINE_TMP_DIR' in os.environ:
compile_dir = '{}/theano_compile_process_{}'.format(os.environ['PIPELINE_TMP_DIR'], rank)
os.environ["THEANO_FLAGS"] = ("base_compiledir='{}'".format(compile_dir))
atexit.register(delete_folder, compile_dir)
from pipeline.cmdline import logger
info = lambda msg: logger.info('Process {}: {}'.format(rank, msg))
video_list_path, repo_output_path, ts_format, text_root_path = parse_args(comm)
video_paths = [s.strip() for s in open(video_list_path, 'r').readlines()]
if rank is 0:
logger.info('There are {} processes'.format(comm.Get_size()))
if rank < len(video_paths):
process_video(video_paths[rank],
repo_output_path,
ts_format,
text_root_path,
rank)
else:
logger.warning('Process {}: No file to process'.format(rank))
info('Reached Barrier.')
comm.Barrier()
info('Exiting.')
def main(): # pragma: no cover
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
if 'PIPELINE_TMP_DIR' in os.environ:
compile_dir = '{}/theano_compile_process_{}'.format(
os.environ['PIPELINE_TMP_DIR'], rank)
os.environ["THEANO_FLAGS"] = (
"base_compiledir='{}'".format(compile_dir))
atexit.register(delete_folder, compile_dir)
from pipeline.cmdline import logger
info = lambda msg: logger.info('Process {}: {}'.format(rank, msg))
video_list_path, repo_output_path, ts_format, text_root_path = parse_args(
comm)
video_paths = [s.strip() for s in open(video_list_path, 'r').readlines()]
if rank is 0:
logger.info('There are {} processes'.format(comm.Get_size()))
if rank < len(video_paths):
process_video(video_paths[rank], repo_output_path, ts_format,
text_root_path, rank)
else:
logger.warning('Process {}: No file to process'.format(rank))
info('Reached Barrier.')
comm.Barrier()
info('Exiting.')
def main(): # pragma: no cover
comm = MPI.COMM_WORLD
rank = comm.Get_rank()
if "PIPELINE_TMP_DIR" in os.environ:
compile_dir = "{}/theano_compile_process_{}".format(
os.environ["PIPELINE_TMP_DIR"], rank)
os.environ["THEANO_FLAGS"] = f"base_compiledir='{compile_dir}'"
atexit.register(delete_folder, compile_dir)
from pipeline.cmdline import logger
info = lambda msg: logger.info(f"Process {rank}: {msg}")
video_list_path, repo_output_path, ts_format, text_root_path = parse_args(
comm)
video_paths = [s.strip() for s in open(video_list_path).readlines()]
if rank == 0:
logger.info(f"There are {comm.Get_size()} processes")
if rank < len(video_paths):
process_video(video_paths[rank], repo_output_path, ts_format,
text_root_path, rank)
else:
logger.warning(f"Process {rank}: No file to process")
info("Reached Barrier.")
comm.Barrier()
info("Exiting.")
def main(): # pragma: no cover
parser = argparse.ArgumentParser(
prog='BeesBook pipeline',
description='Process a video using the beesbook pipeline')
parser.add_argument('video_path', help='path of input video', type=str)
for arg, kwargs in chain(get_shared_positional_arguments(), get_shared_optional_arguments()):
parser.add_argument(arg, **kwargs)
args = parser.parse_args()
logger.info('Processing video: {}'.format(args.video_path))
logger.info('Config: {}'.format(args))
process_video(args)
def main(): # pragma: no cover
parser = argparse.ArgumentParser(
prog='BeesBook pipeline',
description='Process a video using the beesbook pipeline')
parser.add_argument('video_path', help='path of input video', type=str)
for arg, kwargs in chain(get_shared_positional_arguments(),
get_shared_optional_arguments()):
parser.add_argument(arg, **kwargs)
args = parser.parse_args()
logger.info('Processing video: {}'.format(args.video_path))
logger.info('Config: {}'.format(args))
process_video(args)
def main(): # pragma: no cover
parser = argparse.ArgumentParser(
prog="BeesBook pipeline",
description="Process a video using the beesbook pipeline",
)
parser.add_argument("video_path", help="path of input video", type=str)
for arg, kwargs in chain(get_shared_positional_arguments(),
get_shared_optional_arguments()):
parser.add_argument(arg, **kwargs)
args = parser.parse_args()
logger.info(f"Processing video: {args.video_path}")
logger.info(f"Config: {args}")
process_video(args)
def process_video(args):
config = get_auto_config()
logger.info('Initializing {} pipeline(s)'.format(args.num_threads))
plines = [Pipeline([Image, Timestamp], [PipelineResult], **config)
for _ in range(args.num_threads)]
logger.info('Loading bb_binary repository {}'.format(args.repo_output_path))
repo = Repository(args.repo_output_path)
camId, _, _ = parse_video_fname(args.video_path)
logger.info('Parsed camId = {}'.format(camId))
gen_processor = GeneratorProcessor(plines, lambda: BBBinaryRepoSink(repo, camId=camId))
logger.info('Processing video frames from {}'.format(args.video_path))
gen_processor(video_generator(args.video_path, args.timestamp_format, args.text_root_path))
def main(): # pragma: no cover
parser = argparse.ArgumentParser(
prog='BeesBook pipeline batch processor',
description='Batch process video using the beesbook pipeline')
parser.add_argument('video_root_path',
help='root path of input videos',
type=str)
for arg, kwargs in chain(get_shared_positional_arguments(),
get_shared_optional_arguments()):
parser.add_argument(arg, **kwargs)
args = parser.parse_args()
pipeline_cmd = None
if os.path.exists(os.path.join(os.getcwd(), 'bb_pipeline')):
pipeline_cmd = os.path.join(os.getcwd(), 'bb_pipeline')
else:
pipeline_cmd = shutil.which('bb_pipeline')
assert (pipeline_cmd is not None)
video_files = []
for root, dirs, files in os.walk(args.video_root_path):
for file in files:
video_files.append(os.path.join(root, file))
logger.info('Processing files: \n\t{}'.format('\n\t'.join(video_files)))
for fname in video_files:
cmd_args = [fname] + \
list([args.__dict__[param] for param, _ in get_shared_positional_arguments()])
for param, _ in get_shared_optional_arguments():
if param[2:] in args.__dict__:
cmd_args.append(param)
cmd_args.append(str(args.__dict__[param[2:]]))
call([pipeline_cmd] + cmd_args)
def process_video(args):
config = get_auto_config()
logger.info('Initializing {} pipeline(s)'.format(args.num_threads))
plines = [
Pipeline([Image, Timestamp], [PipelineResult], **config)
for _ in range(args.num_threads)
]
logger.info('Loading bb_binary repository {}'.format(
args.repo_output_path))
repo = Repository(args.repo_output_path)
camId, _, _ = parse_video_fname(args.video_path)
logger.info('Parsed camId = {}'.format(camId))
gen_processor = GeneratorProcessor(
plines, lambda: BBBinaryRepoSink(repo, camId=camId))
logger.info('Processing video frames from {}'.format(args.video_path))
gen_processor(
video_generator(args.video_path, args.timestamp_format,
args.text_root_path))