def test_tagger():
# logging.basicConfig(level=logging.DEBUG)
urllib.request.urlretrieve(
"https://www.dropbox.com/s/6adl0d91l5lokbu/cut4.mp4?dl=1",
"/tmp/test.mp4")
if os.path.exists('/tmp/videos'):
shutil.rmtree('/tmp/videos')
manager = FullStorageManager(
CustomTagger(FixedCameraBGFGSegmenter().segment, batch_size=20),
CropSplitter(),
'/tmp/videos',
'/tmp/videos',
dsn='dbname=postgres user=postgres password=postgres host=127.0.0.1')
start = time.time()
output = manager.put('/tmp/test.mp4',
'test',
parallel=False,
args={
'encoding': XVID,
'size': -1,
'sample': 1.0,
'offset': 0,
'limit': 1000,
'batch_size': 20,
'num_processes': 8,
'background_scale': 1
})
end = time.time()
print("Without background resizing:", end - start)
res = manager.get('test', Condition(label='foreground'))
shape1 = next(next(res))['data'].shape
assert shape1[2] == 3
manager = FullStorageManager(
CustomTagger(FixedCameraBGFGSegmenter().segment, batch_size=20),
CropSplitter(),
'/tmp/videos',
'/tmp/videos',
dsn='dbname=postgres user=postgres password=postgres host=127.0.0.1')
start = time.time()
output = manager.put('/tmp/test.mp4',
'test',
parallel=False,
args={
'encoding': XVID,
'size': -1,
'sample': 1.0,
'offset': 0,
'limit': 1000,
'batch_size': 20,
'num_processes': 8,
'background_scale': 0.2
})
end = time.time()
print("With background resizing:", end - start)
res = manager.get('test', Condition(label='foreground'))
shape2 = next(next(res))['data'].shape
assert shape2[2] == 3
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 = DeepLensOptimizer()
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 runFull(src, tot=-1, sel=0.1):
cleanUp()
manager = FullStorageManager(
CustomTagger(FixedCameraBGFGSegmenter().segment, batch_size=100),
CropSplitter(), 'videos')
now = timer()
manager.put(src,
'test',
args={
'encoding': XVID,
'size': -1,
'sample': 1.0,
'offset': 0,
'limit': tot,
'batch_size': 100,
'num_processes': 12
})
put_time = timer() - now
print("Put time for simple:", put_time)
region = Box(515, 200, 700, 600)
sel = sel / 2
clips = manager.get('test', Condition(label='foreground'))
pipelines = []
for c in clips:
pipelines.append(c[KeyPoints()][ActivityMetric('one', region)][Filter(
'one', [-0.25, -0.25, 1, -0.25, -0.25], 1.5, delay=10)])
result = counts(pipelines, ['one'], stats=True)
logrecord('full', ({'file': src}), 'get', str(result), 's')
def put(video, name, segmentation_args):
manager = FullStorageManager(\
CustomTagger(\
FixedCameraBGFGSegmenter(**segmentation_args).segment, \
batch_size=STORAGE_ARGS['batch_size']), \
CropSplitter(), FOLDER)
manager.put(video, name, args=STORAGE_ARGS, hwang=False)
def fullQuality(index=0):
if os.path.exists('videos'):
shutil.rmtree('videos')
manager = FullStorageManager(
CustomTagger(FixedCameraBGFGSegmenter(blur=11,
movement_threshold=11).segment,
batch_size=200), CropSplitter(), 'videos')
now = datetime.datetime.now()
filename = FOLDER + 'crash{0}.mp4'.format(index)
manager.put(filename,
'test',
args={
'encoding': XVID,
'size': -1,
'sample': 1.0,
'offset': 0,
'limit': -1,
'batch_size': 200,
'num_processes': 4,
'background_scale': 1
},
hwang=False)
#no queries to the background, lowest quality for speed to be within 5%
manager.set_quality('test',
Condition(label='background'),
qscale=52,
rscale=0.1)
manager.set_quality('test',
Condition(label='foreground'),
qscale=44,
rscale=1)
put_result = (datetime.datetime.now() - now).total_seconds()
logrecord('fullq', ({
'folder_size': get_size('videos')
}), 'put', str(put_result), 's')
now = datetime.datetime.now()
clips = manager.get('test', Condition(label='foreground'))
for c in clips:
pipeline_get(c[MotionVectors()][Speed()])
result = (datetime.datetime.now() - now).total_seconds()
logrecord('fullq', ({
'folder_size': get_size('videos')
}), '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 = DeepLensOptimizer()
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 get(name, condition): manager = FullStorageManager(\ CustomTagger(\ FixedCameraBGFGSegmenter().segment, \ batch_size=STORAGE_ARGS['batch_size']), \ CropSplitter(), FOLDER) clips = manager.get(name, condition) srcs = [] for c in clips: if isinstance(c, IteratorVideoStream): srcs.extend(c.sources) else: srcs.append(c.src) return srcs
def runFull(src, tot=1000, sel=0.1):
cleanUp()
manager = FullStorageManager(
CustomTagger(FixedCameraBGFGSegmenter().segment, batch_size=100),
CropSplitter(),
'videos',
'./videos',
dsn='dbname=header user=postgres password=secret host=127.0.0.1')
now = timer()
manager.put(src,
'test',
args={
'encoding': XVID,
'size': -1,
'sample': 1.0,
'offset': 0,
'limit': tot,
'batch_size': 100,
'num_processes': 4,
'background_scale': 1
})
put_time = timer() - now
print("Put time for full:", 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 = []
for c in clips:
pipelines.append(c[KeyPoints()][ActivityMetric('one', region)][Filter(
'one', [-0.25, -0.25, 1, -0.25, -0.25], 1.5, delay=10)])
result = counts(pipelines, ['one'], stats=True)
logrecord('full', ({
'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 = DeepLensOptimizer()
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'])
def runFull(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 = []
for c in clips:
pipelines.append(c[KeyPoints(blur=3)][ActivityMetric('one', region)][Filter('one', [-0.5,1,-0.5], 0.25, delay=40)])
result = counts(pipelines, ['one'], stats=True)
logrecord('full',({'size': tot, 'sel': sel, 'file': src}), 'get', str(result), 's')
def runFullOpt(src, tot=1000, sel=0.1):
cleanUp()
manager = FullStorageManager(CustomTagger(FixedCameraBGFGSegmenter().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(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 = DeepLensOptimizer()
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)[1]['elapsed']
logrecord('fullopt',({'size': tot, 'sel': sel, 'file': src}), 'get', str(result), 's')
from deeplens.full_manager.full_video_processing import CropSplitter
from deeplens.struct import *
from deeplens.tracking.background import FixedCameraBGFGSegmenter
from deeplens.utils import *
from deeplens.dataflow.map import *
from deeplens.full_manager.full_manager import *
from deeplens.utils.testing_utils import *
import os
import shutil
if os.path.exists('./videos'):
shutil.rmtree('./videos')
manager = FullStorageManager(
CustomTagger(FixedCameraBGFGSegmenter().segment, batch_size=5),
CropSplitter(), 'videos')
manager.put(0,
'test',
args={
'encoding': XVID,
'size': -1,
'sample': 1.0,
'offset': 0,
'limit': 100,
'batch_size': 5
})
def runFull(src, tot=1000, batch_size=20):
# cleanUp()
folder = '/bulk/videos'
manager = FullStorageManager(
CustomTagger(FixedCameraBGFGSegmenter().segment,
batch_size=batch_size), CropSplitter(), folder)
# now = timer()
# manager.put(src, 'test',
# args={'encoding': 'X264', 'size': -1, 'sample': 1.0, 'offset': 0, 'limit': tot, 'batch_size': batch_size,
# 'num_processes': 4, 'background_scale': 1})
# put_time = timer() - now
# print("Put time for full:", put_time)
print("Batch size:", batch_size, "Folder size:", get_size(folder))
left = Box(1600, 1600, 1700, 1800)
middle = Box(1825, 1600, 1975, 1800)
right = Box(2050, 1600, 2175, 1800)
# left = Box(1600 / 3, 1600 / 3, 1700 / 3, 1800 / 3)
# middle = Box(1825 / 3, 1600 / 3, 1975 / 3, 1800 / 3)
# right = Box(2050 / 3, 1600 / 3, 2175 / 3, 1800 / 3)
# left = Box(1600 / 2, 1600 / 2, 1700 / 2, 1800 / 2)
# middle = Box(1825 / 2, 1600 / 2, 1975 / 2, 1800 / 2)
# right = Box(2050 / 2, 1600 / 2, 2175 / 2, 1800 / 2)
clips = manager.get('test',
Condition(label='foreground', custom_filter=None),
large=True)
pipelines = []
total_counts = {}
total_frames = 0
total_time = 0
for c in tqdm(clips):
this_result = count(c[GoodKeyPoints()][ActivityMetric(
'left', left)][ActivityMetric('middle', middle)][ActivityMetric(
'right',
right)][Filter('left', [1], 1,
delay=25)][Filter('middle', [1], 1,
delay=25)][Filter('right',
[1],
1,
delay=25)],
['left', 'middle', 'right'],
stats=True)
print(this_result)
total_counts = {
k: total_counts.get(k, 0) + this_result[0].get(k, 0)
for k in set(total_counts) | set(this_result[0])
}
total_frames += this_result[1]['frames']
total_time += this_result[1]['elapsed']
result = total_counts, {'frames': total_frames, 'elapsed': total_time}
logrecord('full', ({
'size': tot,
'batch_size': batch_size,
'file': src,
'folder_size': get_size(folder)
}), 'get', str(result), 's')