def query(path):
rv = []
fps = 30
sample_every = 3
all_frames = VideoToFrames(LocalVideoDecoder(path))()
sampled_frames = Slice(step=sample_every, end=300)(all_frames)
detections = Detection(server_list=[
'cloudlet031.elijah.cs.cmu.edu:5000',
'cloudlet031.elijah.cs.cmu.edu:5001'
])(sampled_frames)
person_detections = DetectionFilterFlatten(['person'], 0.3)(detections)
coalesced_persons = CoalesceByLast(bounds_merge_op=Bounds3D.span,
predicate=iou_at_least(0.1),
epsilon=sample_every *
3)(person_detections)
long_coalesced_persons = Filter(pred_fn=lambda framegrps: framegrps.bounds.
length() > fps * 3 # 3 seconds
)(coalesced_persons)
framegrps = VideoCropFrameGroup(
LRULocalVideoDecoder(path))(long_coalesced_persons)
for _, fg in enumerate(run_to_finish(framegrps)):
rv.append((fg.bounds, fg.get_mp4(), 'mp4'))
return rv
def query(path, session, *args, **kwargs):
assert isinstance(session, Session)
session.log('error', "Enter query fn")
rv = []
all_frames = VideoToFrames(LocalVideoDecoder(path))()
sampled_frames = Slice(step=30, end=1800)(all_frames)
detections = Detection('cloudlet031.elijah.cs.cmu.edu', 5000)(sampled_frames)
person_detections = DetectionFilterFlatten(['bus'], 0.3)(detections)
# SIFT filter
fil_sift_extract_spec = FilterSpec(
"sift-extract",
code=Blob(open("fil_homography.py", 'rb').read()),
arguments=['ExtractFilter', 'SIFT'],
min_score=1.
)
fil_sift_match_spec = FilterSpec(
"sift-match",
code=Blob(open("fil_homography.py", 'rb').read()),
arguments=['MatchFilter', 'SIFT', 0.7],
dependencies=[fil_sift_extract_spec, ],
blob_argument=Blob(open("brandenburg_hi_blob.zip", 'rb').read()),
min_score=5
)
matched_patches = RGBDiamondSearch(session, [fil_sift_extract_spec, fil_sift_match_spec])(person_detections)
for _, intrvl in enumerate(run_to_finish(matched_patches)):
rv.append((intrvl.bounds, intrvl.jpeg, 'jpg'))
return rv
def query(path, session, *args, **kwargs):
assert isinstance(session, Session)
session.log('error', "Enter query fn")
rv = []
all_frames = VideoToFrames(LocalVideoDecoder(path))()
sampled_frames = Slice(step=30, end=1800)(all_frames)
detections = Detection('cloudlet031.elijah.cs.cmu.edu',
5000)(sampled_frames)
person_detections = DetectionFilterFlatten(['bus'], 0.3)(detections)
# filter vertical 'vert' or 'horz'
orient_spec = FilterSpec("orient",
Blob(FIL_ORIENTATION_CODE),
arguments=[
'vert',
],
min_score=1.)
oriented_patches = RGBDiamondSearch(session, [
orient_spec,
])(person_detections)
for _, intrvl in enumerate(run_to_finish(oriented_patches)):
rv.append((intrvl.bounds, intrvl.jpeg, 'jpg'))
return rv
def query(path):
rv = []
all_frames = VideoToFrames(LocalVideoDecoder(path))()
sampled_frames = Slice(step=30, end=300)(all_frames)
detections = Detection('cloudlet031.elijah.cs.cmu.edu',
5000)(sampled_frames)
person_detections = DetectionFilterFlatten(['person'], 0.3)(detections)
for _, intrvl in enumerate(run_to_finish(person_detections)):
rv.append((intrvl.bounds, intrvl.jpeg))
return rv
from stsearch.interval import *
from stsearch.op import *
from stsearch.utils import run_to_finish
from stsearch.videolib import *
INPUT_NAME = "example.mp4"
OUTPUT_DIR = Path(__file__).stem + "_output"
if __name__ == "__main__":
os.makedirs(OUTPUT_DIR, exist_ok=True)
intervals_to_crop = [
Interval(Bounds3D(t1=30, t2=330, x1=0, x2=.5, y1=0, y2=.5),
{'msg': "ts 30-330 upper left crop"}),
Interval(Bounds3D(300, 420, .25, .75, .4, .6),
{'msg': "ts 300-420 center crop"})
]
crop_intervals = FromIterable(intervals_to_crop)()
framegroups = LocalVideoCropFrameGroup(INPUT_NAME)(crop_intervals)
for k, fg in enumerate(run_to_finish(framegroups)):
assert isinstance(fg, FrameGroupInterval)
out_name = f"{OUTPUT_DIR}/{k}-{fg['t1']}-{fg['t2']}.mp4"
fg.savevideo(out_name)
logger.debug(f"saved {out_name}")
logger.info(
"You should find 2 .mp4 files, cropped -- spatially and temporally -- from the input."
)