def search_vfs_single(data):
name, fps, target_color, threshold, start_time, confidence, y1, x1, y2, x2 = data
end_time = start_time + (1 / fps)
# prefix = uuid.uuid4().hex
with engine.VFS(transient=True, child_process=True):
reconstruction.POOL_SIZE = 1
#prefix = uuid.uuid4().hex
#api.read(name, f'out-{prefix}.rgb', t=(start_time, end_time), roi=(y1, x1, y2, x2), codec='rgb')
# pass
with api.read(name,
t=(start_time, end_time),
roi=(y1, x1, y2, x2),
codec='rgb') as stream:
#fn = api.read(name, t=(start_time, end_time), roi=(y1, x1, y2, x2), codec='rgb')
#with open(fn, 'rb') as stream:
buffer = np.frombuffer(stream.read(), dtype=np.uint8)
frame = buffer.reshape(y2 - y1, x2 - x1, 3)
#except:
# pass
if is_dominant_color(frame, target_color, threshold):
return start_time, confidence, y1, x1, y2, x2
else:
return None #-1, -1, -1, -1, -1, -1
def index_vfs(name, duration, fps, interval, results_filename):
model, names = load_model()
target_class = names.index('car')
#hits = []
read_parameters = []
count = 0
model_resolution = 540, 540
with engine.VFS(transient=True), open(results_filename, "w") as f:
reconstruction.POOL_SIZE = 1
for index in range(duration * interval):
start_time = index * (1 / interval)
end_time = start_time + (1 / fps)
read_parameters.append((name, None, model_resolution, None,
(start_time, end_time), 'rgb', None))
#if start_time > 30:
# break
#fs = api.readmany2(*zip(*read_parameters), workers=16)
#afs = as_completed(fs)
for future in as_completed(
api.readmany2i(*zip(*read_parameters), workers=16)):
with open(future.result(), "rb") as stream:
frame = np.frombuffer(stream.read(), dtype=np.uint8).reshape(
model_resolution[0], model_resolution[1], 3)
start_time = read_parameters[future.index][4][0]
for confidence, y1, x1, y2, x2 in inference(
model, frame, target_class):
f.write(f'{start_time},{confidence},{y1},{x1},{y2},{x2}\n')
count += 1
logging.critical('Index.VFS: %d events indexed', count)
#return hits
"""
filenames = api.readmany(*zip(*read_parameters), workers=2)
#read_parameters = read_parameters[:1]
#filenames = api.preadmany(read_parameters, workers=4)
#for filename in filenames:
for filename in filenames:
##with api.read(name, resolution=(540, 704), t=(start_time, end_time), codec='rgb') as filename:
#filename = api.read(name, resolution=(540,704), t=(start_time, end_time), codec='rgb')
with open(filename, "rb") as stream:
#frame = np.fromfile('out.rgb', dtype=np.uint8).reshape((540,704,3))
frame = np.frombuffer(stream.read(), dtype=np.uint8).reshape(model_resolution[0], model_resolution[1], 3)
for confidence, y1, x1, y2, x2 in inference(model, frame, target_class):
f.write(f'{start_time},{confidence},{y1},{x1},{y2},{x2}\n')
count += 1
logging.critical('Index.VFS: %d events indexed', count)
#return hits
"""
"""
def evaluate_quality(left_name, right_name, reference_directory,
reference_left_filename, reference_right_filename):
with engine.VFS():
logical_left = logicalvideo.LogicalVideo.get_by_name(left_name)
physical_left = list(logical_left.videos())[0]
gops_left = physical_left.gops()
separate_psnr, overlap_psnr = 0, 0
separate_count, overlap_count = 0, 0
for gop in gops_left:
if '{}' not in gop.filename:
left_separate_psnr, left_count = evaluate_quality_separate(
gop, gop.filename, reference_directory)
separate_psnr += left_separate_psnr
separate_count += left_count
pass
else:
left_separate_psnr, left_overlap_psnr, left_count = evaluate_quality_overlap_left(
gop, reference_directory)
separate_psnr += left_separate_psnr
overlap_psnr += left_overlap_psnr
overlap_count += left_count
separate_count += left_count
pass
logical_right = logicalvideo.LogicalVideo.get_by_name(right_name)
physical_right = list(logical_right.videos())[0]
gops_right = physical_right.gops()
for gop in gops_right:
if '{}' not in gop.filename:
right_separate_psnr, right_count = evaluate_quality_separate(
gop, gop.filename, reference_directory)
separate_psnr += right_separate_psnr
separate_count += right_count
pass
else:
right_separate_psnr, right_overlap_psnr, right_count = evaluate_quality_overlap_right(
gop, reference_directory)
separate_psnr += right_separate_psnr
overlap_psnr += right_overlap_psnr
overlap_count += right_count
separate_count += right_count
print(
f'Overall separate: {separate_psnr // separate_count}, overlap: {overlap_psnr // overlap_count}'
)
#ssim_left = evaluate_ssim(left_name, reference_left_filename, source_filename='out_left.mp4')
ssim_right = evaluate_ssim(right_name,
reference_right_filename,
source_filename='out_right.mp4')
return separate_psnr / separate_count, overlap_psnr / overlap_count, ssim_left, ssim_right
def create_cache(n, name, T, R, P):
with engine.VFS(transient=True):
for i in range(n):
r = random.choice(R)
p = random.choice(P)
t1 = random.randint(0, T-1)
t2 = min(random.randint(t1 + 1, t1 + 60), T - 1)
with open('cache.txt', 'w') as f:
f.writelines([f'{i} cache {name} {(t1, t2)} {r} {p}\n'])
print(f'{i} cache {name} {(t1, t2)} {r} {p}')
api.read(name, f"out.{p}", resolution=r, t=(t1, t2), codec=p)
def stream_vfs(name, resolution, fps, index_filename):
prefix = uuid.uuid4().hex
read_parameters = []
with engine.VFS(transient=True):
hits = parse_index_file(index_filename)
for index, (start, end) in enumerate(group_by_frames(hits, fps)):
read_parameters.append(
(name, f'vfsout-{prefix}-{index}.mp4', resolution, None,
(start, end), 'h264', None))
#api.read(name, f'out-{prefix}-{index}.mp4', t=(start, end), resolution=resolution, codec='h264')
wait(
list(
api.readmany2(*zip(*read_parameters),
workers=min(len(read_parameters), 10))))
def temp():
name = 'v'
threshold = 50
fps = 30
with log_runtime('Search.VFS', level=logging.CRITICAL):
with engine.VFS(transient=True):
for start_time, confidence, y1, x1, y2, x2 in parse_index_file(
'index_cars_vfs.csv'):
end_time = start_time + (1 / fps)
api.read(name,
"foo.mp4",
t=(start_time, end_time),
roi=(y1, x1, y2, x2),
codec='rgb')
pass
exit(1)
if not os.path.exists(gop.filename):
return get_random_gop(engine, name, r, t, index, avoid_ids)
elif gop.id in (avoid_ids or []):
return get_random_gop(engine, name, r, t, index, avoid_ids)
else:
return gop
if __name__ == '__main__':
logging.basicConfig(level=logging.INFO)
n = 50
mt = 0.0
with engine.VFS(transient=True) as engine:
api.vacuum()
#api.write('v1', 'inputs/visualroad-4k-30a-gop30.mp4')
#api.write('v2', 'inputs/visualroad-4k-30b-gop30.mp4')
#api.read('v1', 'out.mp4', resolution=(1080, 1920), t=(0, 60))
#api.read('v2', 'out.mp4', resolution=(1080, 1920), t=(0, 60))
#api.read('v1', 'out.mp4', resolution=(540, 960), t=(0, 60))
#api.read('v2', 'out.mp4', resolution=(540, 960), t=(0, 60))
for i in range(n):
r = 540, 960 # 1080, 1920 #2160, 3840 # # #
gop1 = get_random_gop(engine, 'v1', r, 1, i)
gop2 = get_random_gop(engine, 'v2', r, 1, i, [gop1.id])
# Compression
duration = time.time() - start_time
print(f'{i} naive duration {duration:02f}')
def read_random(i, reader, source, r, t, p):
reader(i, source, r, (t, t+1), p)
if __name__ == '__main__':
logging.basicConfig(level=logging.INFO)
n = int(sys.argv[1]) if len(sys.argv) > 1 else 1
R = [(540, 960), (1080, 1920), (2160, 3840)]
P = ['h264', 'hevc']
T = (0, 3600)
with engine.VFS(transient=True):
api.vacuum()
#create_cache(500, "v", 3600, R, P)
#exit(0)
n = 50
ts = [random.randint(*T) for _ in range(n)]
ps = [random.choice(P) for _ in range(n)]
rs = [random.choice(R) for _ in range(n)]
apply_deferred_compression = False
apply_eviction = True
#with engine.VFS(transient=True):
# if 'v' not in api.list():
def search_vfs(name, fps, target_color, threshold, index_filename,
result_filename):
count = 0
read_parameters = []
futures = []
for start_time, confidence, y1, x1, y2, x2 in parse_index_file(
index_filename):
read_parameters.append(
(name, None, None, (y1, x1, y2, x2),
(start_time, start_time + (1 / fps)), 'rgb', None))
#print(len(read_parameters))
#read_parameters = read_parameters[:16]
with ProcessPoolExecutor(max_workers=4) as pool, engine.VFS(
transient=True, child_process=True):
for future in api.readmany2i(*zip(*read_parameters), workers=32):
futures.append(
chain(pool, future, compute_dominant_color,
read_parameters[future.index], target_color, threshold))
# futures.append(pool.submit(compute_dominant_color, future, read_parameters[future.index], target_color, threshold))
#for future in as_completed(api.readmany2i(*zip(*read_parameters), workers=16)):
# futures.append(pool.submit(compute_dominant_color, read_parameters[future.index], future.result(), target_color, threshold))
with open(result_filename, 'w') as f:
for future in futures: #as_completed(futures):
if future.result() is not None:
start_time, confidence, y1, x1, y2, x2 = future.result()
f.write(f'{start_time},{confidence},{y1},{x1},{y2},{x2}\n')
count += 1
"""
with open(future.result(), "rb") as stream:
buffer = np.frombuffer(stream.read(), dtype=np.uint8)
start_time = read_parameters[future.index][4][0]
y1, x1, y2, x2 = read_parameters[future.index][3]
confidence = 0
frame = buffer.reshape(y2 - y1, x2 - x1, 3)
if is_dominant_color(frame, target_color, threshold):
f.write(f'{start_time},{confidence},{y1},{x1},{y2},{x2}\n')
count += 1
"""
logging.critical('Search.VFS: %d events indexed', count)
return
"""
read_parameters = []
for start_time, confidence, y1, x1, y2, x2 in parse_index_file(index_filename):
read_parameters.append((name, None, None, (y1, x1, y2, x2), (start_time, start_time + (1 / fps)), 'rgb', None))
with engine.VFS(transient=True), open(result_filename, 'w') as f:
for i, filename in enumerate(api.readmany(*zip(*read_parameters), workers=16)):
with open(filename, 'rb') as stream:
buffer = np.frombuffer(stream.read(), dtype=np.uint8)
start_time = read_parameters[i][4][0]
y1, x1, y2, x2 = read_parameters[i][3]
confidence = 0
frame = buffer.reshape(y2 - y1, x2 - x1, 3)
if is_dominant_color(frame, target_color, threshold):
f.write(f'{start_time},{confidence},{y1},{x1},{y2},{x2}\n')
"""
futures = []
count = 0
with ProcessPoolExecutor(max_workers=4) as pool, open(
result_filename, 'w') as f:
for data in ((name, fps, target_color, threshold, start_time,
confidence, y1, x1, y2, x2) for start_time, confidence,
y1, x1, y2, x2 in parse_index_file(index_filename)):
future = pool.submit(search_vfs_single, data)
futures.append(future)
#wait(futures)
for result in (f.result() for f in futures):
if result is not None:
start_time, confidence, y1, x1, y2, x2 = result
f.write(f'{start_time},{confidence},{y1},{x1},{y2},{x2}\n')
count += 1
logging.critical('Search.VFS: %d events indexed', count)
#for result in pool.map(search_vfs_single, data):
# if result is not None:
# start_time, confidence, y1, x1, y2, x2 = result
# f.write(f'{start_time},{confidence},{y1},{x1},{y2},{x2}\n')
"""
def ingest_vfs(filename, name=None):
with engine.VFS(transient=True):
api.write(name or "v%d" % int(time.time() * 1000), filename)
if __name__ == '__main__':
logging.basicConfig(level=logging.CRITICAL)
clients = 1
ingest_filename = "inputs/visualroad-2k-30a.mp4"
duration = 3600
fps = 30
query_iterval = 3
target_color = np.array([127, 127, 127])
color_threshold = 50
resolution = (1080, 1920)
# temp()
with engine.VFS(transient=True) as instance:
# api.vacuum()
if 'v' not in api.list():
api.write("v", ingest_filename)
with ProcessPoolExecutor(max_workers=clients) as pool:
#with log_runtime('Index.VFS', level=logging.CRITICAL):
# index_vfs("v", duration, fps, query_iterval, 'index_cars_vfs.csv')
#with log_runtime('Search.VFS', level=logging.CRITICAL):
# search_vfs("v", fps, target_color, color_threshold, 'index_cars_vfs.csv', 'index_colors_vfs.csv')
with log_runtime('Stream.VFS', level=logging.CRITICAL):
stream_vfs('v', resolution, fps, 'index_colors_vfs.csv')
#with log_runtime('Index.FS', level=logging.CRITICAL):
# index_fs(ingest_filename, duration, fps, query_iterval, 'index_cars_fs.csv')
#with log_runtime('Search.FS', level=logging.CRITICAL):
import os
import logging
from vfs import api
from vfs import engine
from vfs.physicalvideo import PhysicalVideo
from vfs.rawcompression import compress
from vfs.videoio import encoded
if __name__ == '__main__':
logging.basicConfig(level=logging.INFO)
t = (0, 12)
level = 15
#with engine.VFS(transient=True):
# api.write('v', 'inputs/visualroad-4k-30a.mp4')
# api.read('v', '/dev/null', t=t, codec='rgb')
#os.remove('out.rgb')
if level is not None:
with engine.VFS(transient=True):
for physical in PhysicalVideo.get_all():
if not encoded[physical.codec]:
for gop in physical.gops():
if gop.zstandard != level:
compress(gop.id, level)
with engine.VFS(transient=True):
api.read('v', '/dev/null', t=t, codec='rgb')