def fault_cl():
# Create new config
(cfg_path, cfg) = make_config(master_port='5010',
worker_port='5011',
path='/tmp/config_test')
# Setup and ingest video
with Client(master='localhost:5010',
workers=[],
config_path=cfg_path,
no_workers_timeout=120,
enable_watchdog=False,
debug=True) as cl:
(vid1_path, vid2_path) = download_videos()
cl.load_op(
os.path.abspath(
os.path.join(cwd, '..', 'build/tests/libscanner_tests.so')),
os.path.abspath(
os.path.join(cwd, '..', 'build/tests/test_ops_pb2.py')))
cl.ingest_videos([('test1', vid1_path), ('test2', vid2_path)])
yield cl
# Tear down
run([
'rm', '-rf', cfg['storage']['db_path'], cfg_path, vid1_path,
vid2_path
])
def timeout_cl():
# Create new config
(cfg_path, cfg) = make_config(master_port='5155', worker_port='5160')
# Setup and ingest video
master = 'localhost:5155'
workers = ['localhost:{:04d}'.format(5160 + d) for d in range(4)]
with Client(config_path=cfg_path,
no_workers_timeout=120,
master=master,
workers=workers,
enable_watchdog=False) as cl:
(vid1_path, vid2_path) = download_videos()
cl.ingest_videos([('test1', vid1_path), ('test2', vid2_path)])
yield cl
for worker in workers:
channel = grpc.insecure_channel(worker)
worker_stub = protobufs.WorkerStub(channel)
try:
worker_stub.Shutdown(protobufs.Empty(),
timeout=cl._grpc_timeout)
except grpc.RpcError as e:
pass
# Tear down
run([
'rm', '-rf', cfg['storage']['db_path'], cfg_path, vid1_path,
vid2_path
])
def cl():
# Create new config
(cfg_path, cfg) = make_config()
# Setup and ingest video
with Client(config_path=cfg_path, debug=True) as cl:
(vid1_path, vid2_path) = download_videos()
cl.load_op(
os.path.abspath(
os.path.join(cwd, '..', 'build/tests/libscanner_tests.so')),
os.path.abspath(
os.path.join(cwd, '..', 'build/tests/test_ops_pb2.py')))
cl.ingest_videos([('test1', vid1_path), ('test2', vid2_path)])
cl.ingest_videos([('test1_inplace', vid1_path),
('test2_inplace', vid2_path)],
inplace=True)
yield cl
# Tear down
run([
'rm', '-rf', cfg['storage']['db_path'], cfg_path, vid1_path,
vid2_path
])
def no_workers_cl():
# Create new config
(cfg_path, cfg) = make_config(master_port='5020', worker_port='5021')
# Setup and ingest video
with Client(workers=[],
config_path=cfg_path,
enable_watchdog=False,
debug=True) as cl:
(vid1_path, vid2_path) = download_videos()
cl.ingest_videos([('test1', vid1_path), ('test2', vid2_path)])
yield cl
# Tear down
run([
'rm', '-rf', cfg['storage']['db_path'], cfg_path, vid1_path,
vid2_path
])
def sc():
# Create new config
(cfg_path, cfg) = make_config()
# Setup and ingest video
with Client(config_path=cfg_path, debug=True) as sc:
(vid1_path, vid2_path) = download_videos()
sc.ingest_videos([('test1', vid1_path), ('test2', vid2_path)])
sc.ingest_videos([('test1_inplace', vid1_path),
('test2_inplace', vid2_path)],
inplace=True)
yield sc
# Tear down
run([
'rm', '-rf', cfg['storage']['db_path'], cfg_path, vid1_path,
vid2_path
])
def blacklist_cl():
# Create new config
(cfg_path, cfg) = make_config(master_port='5055', worker_port='5060')
# Setup and ingest video
master = 'localhost:5055'
workers = ['localhost:{:04d}'.format(5060 + d) for d in range(4)]
with Client(config_path=cfg_path,
no_workers_timeout=120,
master=master,
workers=workers,
enable_watchdog=False) as cl:
(vid1_path, vid2_path) = download_videos()
cl.ingest_videos([('test1', vid1_path), ('test2', vid2_path)])
yield cl
# Tear down
run([
'rm', '-rf', cfg['storage']['db_path'], cfg_path, vid1_path,
vid2_path
])
def main():
print("Prepare videos and frames")
# video = Video.objects.filter(path__contains='men_single_final_gold')[0]
# movie_path = video.path
# movie_name = video.item_name()
sc = Client()
stride = 1
input_stream = NamedVideoStream(sc, movie_name, path=movie_path)
frame = sc.io.Input([input_stream])
strided_frame = sc.streams.Stride(frame, [stride])
print('Running Scanner MaskRCNN op')
maskrcnn_frame = sc.ops.MaskRCNNDetectObjects(
frame=strided_frame,
device=DeviceType.GPU, #if sc.has_gpu() else DeviceType.CPU,
batch=8,
confidence_threshold=0.5,
min_image_size=800)
maskrcnn_stream = NamedStream(sc, movie_name + '_maskrcnn')
output_op = sc.io.Output(maskrcnn_frame, [maskrcnn_stream])
sc.run(output_op,
scannerpy.common.PerfParams.estimate(),
cache_mode=scannerpy.CacheMode.Ignore)
print('Writing MaskRCNN metadata into frames')
drawn_frame = sc.ops.DrawMaskRCNN(frame=strided_frame,
bundled_data=sc.io.Input(
[maskrcnn_stream]),
min_score_thresh=0.5)
drawn_stream = NamedVideoStream(sc, movie_name + '_maskrcnn_draw')
output_op = sc.io.Output(drawn_frame, [drawn_stream])
sc.run(output_op,
scannerpy.common.PerfParams.estimate(),
cache_mode=scannerpy.CacheMode.Overwrite)
drawn_stream.save_mp4('/app/result/' + movie_name + '_maskrcnn')
def main():
print("Prepare videos and frames")
video = Video.objects.filter(path__contains='wim')[0]
video_path = video.path
video_name = video.item_name()
sc = Client()
stride = 1
input_stream = NamedVideoStream(sc, video_name, path=video_path)
frame = sc.io.Input([input_stream])
# run on all frames
# running_frame = sc.streams.Stride(frame, [stride])
hit_annotation = pickle.load(
open('/app/data/pkl/hit_annotation_tennis.pkl',
'rb'))[video_name + '.mp4']
# run on selected frames
# hit_dict = []
# for h in hit_annotation.values():
# hit_dict += h
hit_dict = hit_annotation
# frame_ids = [i for point in hit_dict for i in range(point[0]['fid']-25, point[-1]['fid']+25) ]
frame_ids = [
i for point in hit_dict for i in range(point[0] - 25, point[-1] + 25)
]
frame_ids.sort()
running_frame = sc.streams.Gather(frame, [frame_ids])
print('Running Scanner DensePose op on %d frames' % (len(frame_ids)))
densepose_frame = sc.ops.DensePoseDetectPerson(frame=running_frame,
device=DeviceType.GPU,
batch=1,
confidence_threshold=0.5,
nms_threshold=0.2)
densepose_stream = NamedStream(sc, video_name + '_densepose')
output_op = sc.io.Output(densepose_frame, [densepose_stream])
sc.run(output_op,
scannerpy.common.PerfParams.estimate(),
cache_mode=scannerpy.CacheMode.Overwrite)
exit()
print('Writing DensePose metadata into frames')
drawn_frame = sc.ops.DrawDensePose(frame=running_frame,
bundled_data=sc.io.Input(
[densepose_stream]),
min_score_thresh=0.5,
show_body=True)
drawn_stream = NamedVideoStream(sc, video_name + '_densepose_draw_uvbody')
output_op = sc.io.Output(drawn_frame, [drawn_stream])
sc.run(output_op,
scannerpy.common.PerfParams.estimate(),
cache_mode=scannerpy.CacheMode.Overwrite)
drawn_stream.save_mp4('/app/result/' + video_name + '_densepose_uvbody')
drawn_frame = sc.ops.DrawDensePose(frame=running_frame,
bundled_data=sc.io.Input(
[densepose_stream]),
min_score_thresh=0.5,
show_body=False)
drawn_stream = NamedVideoStream(sc, video_name + '_densepose_draw_full')
output_op = sc.io.Output(drawn_frame, [drawn_stream])
sc.run(output_op,
scannerpy.common.PerfParams.estimate(),
cache_mode=scannerpy.CacheMode.Overwrite)
drawn_stream.save_mp4('/app/result/' + video_name + '_densepose_full')
from scannerpy import Client
sc = Client(workers=[
'ocean.pdl.local.cmu.edu:15559', 'crissy.pdl.local.cmu.edu:15559'
])