def runFull(src, cache=False, cleanUp=True, limit=6000, optimizer=True):
if cleanUp:
if os.path.exists('/tmp/videos'):
shutil.rmtree('/tmp/videos')
manager = FullStorageManager(CustomTagger(FixedCameraBGFGSegmenter().segment, batch_size=30), CropSplitter(),
'/tmp/videos')
manager.put(src, 'test',
args={'encoding': XVID, 'size': -1, 'sample': 1.0, 'offset': 0, 'limit': limit, 'batch_size': 30,
'num_processes': 4, 'background_scale': 1}, hwang=False)
if cache:
manager.cache('test', Condition(label='foreground'), hwang=False)
clips = manager.get('test', Condition(label='foreground'))
region = Box(200, 550, 350, 750)
pipelines = []
d = SplitterOptimizer()
for c in clips:
pipeline = c[KeyPoints()][ActivityMetric('one', region)][
Filter('one', [-0.25, -0.25, 1, -0.25, -0.25], 1.5, delay=10)]
if optimizer:
pipeline = d.optimize(pipeline)
pipelines.append(pipeline)
result = counts(pipelines, ['one'], stats=True)
logrecord('full', ({'size': limit, 'cache': cache, 'optimizer': optimizer, 'file': src,
'folder_size': get_size('/tmp/videos')}), 'get', str(result), 's')
if cache:
manager.uncache('test', Condition(label='foreground'))
def runSimpleOpt(src, tot=-1, sel=0.1):
cleanUp()
manager = SimpleStorageManager('videos')
now = timer()
manager.put(src,
'test',
args={
'encoding': XVID,
'size': -1,
'sample': 1.0,
'offset': 0,
'limit': tot,
'batch_size': 100,
'num_processes': 4
})
put_time = timer() - now
print("Put time for simple:", put_time)
region = Box(515, 200, 700, 600)
sel = sel / 2
clips = manager.get('test', lambda f: True)
pipelines = []
for c in clips:
pipeline = c[KeyPoints()][ActivityMetric('one', region)][Filter(
'one', [-0.25, -0.25, 1, -0.25, -0.25], 1.5, delay=10)]
d = SplitterOptimizer()
pipelines.append(d.optimize(pipeline))
result = counts(pipelines, ['one'], stats=True)
logrecord('simple', ({'file': src}), 'get', str(result), 's')
def runFullOpt(src, tot=1000, sel=0.1):
cleanUp()
manager = FullStorageManager(
CustomTagger(FixedCameraBGFGSegmenter().segment, batch_size=20),
CropSplitter(), 'videos')
now = timer()
manager.put(src,
'test',
args={
'encoding': XVID,
'size': -1,
'sample': 1.0,
'offset': 0,
'limit': tot,
'batch_size': 20,
'num_processes': 4,
'background_scale': 1
})
put_time = timer() - now
print("Put time for full opt:", put_time)
left = Box(1600, 1600, 1700, 1800)
middle = Box(1825, 1600, 1975, 1800)
right = Box(2050, 1600, 2175, 1800)
sel = sel / 2
clips = manager.get('test',
Condition(label='foreground', custom_filter=None))
pipelines = []
d = SplitterOptimizer()
for c in clips:
pipeline = c[GoodKeyPoints()][ActivityMetric(
'left', left)][ActivityMetric('middle', middle)][ActivityMetric(
'right',
right)][Filter('left', [1, 1, 1], 3,
delay=25)][Filter('middle', [1, 1, 1],
3,
delay=25)][Filter('right',
[1, 1, 1],
3,
delay=25)]
pipeline = d.optimize(pipeline)
pipelines.append(pipeline)
result = counts(pipelines, ['left', 'middle', 'right'], stats=True)
logrecord('fullopt', ({
'size': tot,
'sel': sel,
'file': src
}), 'get', str(result), 's')
def runNaiveOpt(src, tot=-1, sel=0.1):
cleanUp()
c = VideoStream(src, limit=tot)
sel = sel / 2
region = Box(515, 200, 700, 600)
pipelines = \
c[KeyPoints()][ActivityMetric('one', region)][
Filter('one', [-0.25, -0.25, 1, -0.25, -0.25], 1.5, delay=10)]
d = SplitterOptimizer()
pipelines = d.optimize(pipelines)
result = count(pipelines, ['one'], stats=True)
logrecord('naive', ({'file': src}), 'get', str(result), 's')
def runFullOpt(src, tot=1000, sel=0.1):
cleanUp()
manager = FullStorageManager(
CustomTagger(FixedCameraBGFGSegmenter().segment, batch_size=20),
CropSplitter(), 'videos')
now = timer()
manager.put(src,
'test',
args={
'encoding': XVID,
'size': -1,
'sample': 1.0,
'offset': 0,
'limit': tot,
'batch_size': 20,
'num_processes': 4,
'background_scale': 1
})
put_time = timer() - now
print("Put time for simple:", put_time)
region = Box(200, 550, 350, 750)
sel = sel / 2
clips = manager.get(
'test',
Condition(label='foreground',
custom_filter=time_filter(tot // 2 - int(tot * sel),
tot // 2 + int(tot * sel))))
pipelines = []
d = SplitterOptimizer()
for c in clips:
pipeline = c[KeyPoints()][ActivityMetric('one', region)][Filter(
'one', [-0.25, -0.25, 1, -0.25, -0.25], 1.5, delay=10)]
pipeline = d.optimize(pipeline)
pipelines.append(pipeline)
result = counts(pipelines, ['one'], stats=True)
logrecord('fullopt', ({
'size': tot,
'sel': sel,
'file': src
}), 'get', str(result), 's')
def runFullOpt(src, tot=1000, sel=0.1):
cleanUp()
manager = FullStorageManager(
CustomTagger(FixedCameraBGFGSegmenter(movement_threshold=21,
blur=7,
movement_prob=0.10).segment,
batch_size=100), CropSplitter(), 'videos')
manager.put(src,
'test',
args={
'encoding': XVID,
'size': -1,
'sample': 1.0,
'offset': 0,
'limit': tot,
'batch_size': 100
})
region = Box(500, 350, 750, 450)
sel = sel / 2
clips = manager.get(
'test',
Condition(label='foreground',
custom_filter=time_filter(tot // 2 - int(tot * sel),
tot // 2 + int(tot * sel))))
pipelines = []
d = SplitterOptimizer()
for c in clips:
pipeline = c[KeyPoints(blur=3)][ActivityMetric('one', region)][Filter(
'one', [-0.5, 1, -0.5], 0.25, delay=40)]
pipeline = d.optimize(pipeline)
pipelines.append(pipeline)
result = counts(pipelines, ['one'], stats=True)
logrecord('fullopt', ({
'size': tot,
'sel': sel,
'file': src
}), 'get', str(result), 's')
def doexperiments_ks(budget=1000000000):
for i in range(0, 300, 50):
cleanUp()
manager = FullStorageManager(
CustomTagger(FixedCameraBGFGSegmenter().segment, batch_size=100),
CropSplitter(), 'videos')
manager.put('tcam.mp4',
'test',
args={
'encoding': XVID,
'size': -1,
'sample': 1.0,
'offset': 0,
'limit': 2000,
'batch_size': 100,
'num_processes': 4,
'background_scale': 1
})
clips = manager.get('test', Condition(label='foreground'))
region = spatial_selectivity(buffer=i)
d = SplitterOptimizer()
pipelines = []
for c in clips:
pipeline = c[KeyPoints()][ActivityMetric('one', region)][Filter(
'one', [-0.25, -0.25, 1, -0.25, -0.25], 1.5, delay=10)]
pipeline = d.optimize(pipeline)
pipelines.append(pipeline)
result, time1 = counts(pipelines, ['one'], stats=True)
d.cacheKnapsack(manager, budget)
clips = manager.get('test', Condition(label='foreground'))
pipelines = []
for c in clips:
pipeline = c[KeyPoints()][ActivityMetric('one', region)][Filter(
'one', [-0.25, -0.25, 1, -0.25, -0.25], 1.5, delay=10)]
pipeline = d.optimize(pipeline)
pipelines.append(pipeline)
result, time2 = counts(pipelines, ['one'], stats=True)
print(i, budget, time1['elapsed'], time2['elapsed'])
from splitter.full_manager.full_manager import FullStorageManager
from splitter.optimizer.splitter import SplitterOptimizer
from splitter.struct import CustomTagger, VideoStream, Box
from splitter.tracking.contour import KeyPoints
from splitter.tracking.event import Filter, ActivityMetric
if len(sys.argv) < 2:
print("Enter filename as argv[1]")
exit(1)
filename = sys.argv[1]
vs = VideoStream(filename, hwang=True, rows=range(0, 8000, 400))
region = Box(200, 550, 350, 750)
d = SplitterOptimizer()
pipeline = vs[KeyPoints()][ActivityMetric('one', region)][Filter(
'one', [-0.25, -0.25, 1, -0.25, -0.25], 1.5, delay=10)]
# pipeline = d.optimize(pipeline)
result = count(pipeline, ['one'], stats=True)
print("Hwang:", result)
vs = VideoStream(filename, hwang=False, limit=500)
region = Box(200, 550, 350, 750)
d = SplitterOptimizer()
pipeline = vs[KeyPoints()][ActivityMetric('one', region)][Filter(
'one', [-0.25, -0.25, 1, -0.25, -0.25], 1.5, delay=10)]
# pipeline = d.optimize(pipeline)
from splitter.optimizer.splitter import SplitterOptimizer
for i in range(10, 1, -1):
scale = i / 10.0
new_file = set_quality('tcam.mp4', 'tcam-' + str(scale) + ".avi", 25,
scale)
c = VideoStream('tcam-' + str(scale) + ".avi", limit=1000)
region = Box(200, 550, 350, 750)
#print(scale, )
#region2 = Box(region.x0*scale, region.y0*scale, region.x1*scale, region.y1*scale)
#region3 = Box(region.x0*scale*1.1, region.y0*scale*1.1, region.x1*scale*1.1, region.y1*scale*1.1)
#scale = get_scale('tcam-'+str(scale)+".avi")
d = SplitterOptimizer(adaptive_blur=True)
pipelines = c[KeyPoints()][ActivityMetric('one', region)][Filter(
'one', [-0.25, -0.25, 1, -0.25, -0.25], 1.5, delay=10)]
d.optimize(pipelines)
result = count(pipelines, ['one'], stats=True)
print('Resolution', scale, result)
"""
for i in range(25,60,3):
region = Box(200,550,350,750)
from splitter.optimizer.splitter import SplitterOptimizer
d = SplitterOptimizer(adaptive_blur=True)
v = VideoStream(str(i)+'tcam.avi', limit=1000)
v = v[KeyPoints()][ActivityMetric('one', region)][Filter('one', [-0.25,-0.25,1,-0.25,-0.25],1.5, delay=10)]
#c = IteratorVideoStream(itertools.chain(*v), v)
d.optimize(v)