def test_fprint(self):
face_anno = FaceAnnotator(
detector=FaceDetectDlib(), embedding=FaceEmbedVgg2(), freq=4
)
fpobj = FrameProcessor()
fpobj.load_annotator(face_anno)
finput = FrameInput("test-data/video-clip.mp4", bsize=8)
fpobj.process(finput, max_batch=2)
obj_out = fpobj.collect_all()
pa = PeopleAggregator(
face_names=["person 1", "person 2"],
fprint=obj_out["face"]["embed"][[0, 1]],
)
agg = pa.aggregate(obj_out).todf()
assert set(agg.keys()) == set(
[
"video",
"frame",
"top",
"bottom",
"right",
"left",
"confidence",
"person",
"person-dist",
]
)
def test_collect_all(self):
fpobj = FrameProcessor()
fpobj.load_annotator(FrameAnnotator())
fpobj.load_annotator(DiffAnnotator())
finput = FrameInput("test-data/video-clip.mp4", bsize=8)
fpobj.process(finput, max_batch=2)
output = fpobj.collect_all()
assert output["base"] == DictFrame()
assert output["diff"].shape[0] == (2 * 8)
def test_cutoff_empty(self):
fpobj = FrameProcessor()
fpobj.load_annotator(DiffAnnotator(quantiles=[40]))
finput = FrameInput("test-data/video-clip.mp4", bsize=128)
fpobj.process(finput, max_batch=2)
obj_out = fpobj.collect_all()
ca = CutAggregator()
agg = ca.aggregate(obj_out)
assert agg["frame_start"] == list(range(256))
def test_cutoff(self):
fpobj = FrameProcessor()
fpobj.load_annotator(DiffAnnotator(quantiles=[40]))
finput = FrameInput("test-data/video-clip.mp4", bsize=128)
fpobj.process(finput, max_batch=2)
obj_out = fpobj.collect_all()
ca = CutAggregator(cut_vals={"h40": 0.2, "q40": 3})
agg = ca.aggregate(obj_out)
assert set(agg.keys()) == set(["video", "frame_start", "frame_end"])
def test_cutoff_ignore(self):
fpobj = FrameProcessor()
fpobj.load_annotator(DiffAnnotator(quantiles=[40]))
finput = FrameInput("test-data/video-clip.mp4", bsize=128)
fpobj.process(finput, max_batch=2)
obj_out = fpobj.collect_all()
ca = CutAggregator(
cut_vals={"h40": 0.2, "q40": 3}, ignore_vals={"avg_value": 70}
)
agg = ca.aggregate(obj_out)
assert agg == DictFrame()
def main(argv):
try:
opts, args = getopt.getopt(
argv, "hf:q:c:h:",
["file=", "quantiles=", "cutvals=", "histdiff="])
except getopt.GetoptError:
print(
'dvt_to_sat.py -f <filename> -q <quantiles> -c <cutvals> -h <histdiff>'
)
sys.exit(2)
filename = ''
quantiles = 40
cutvals = 3
histdiff = 0
for opt, arg in opts:
if opt == '-h':
print(
'dvt_to_sat.py -f <filename> -q <quantiles> -c <cutvals> -h <histdiff>'
)
sys.exit()
elif opt in ("-f", "--file"):
filename = arg
elif opt in ("-q", "--quantiles"):
quantiles = arg
elif opt in ("-c", "--cutvals"):
cutvals = arg
elif opt in ("-h", "--histdiff"):
cutvals = arg
if (filename == ''):
print('missing param: filename is required')
sys.exit(2)
basename = os.path.basename(filename)
logging.basicConfig(level='INFO')
finput = FrameInput(filename, bsize=128)
fpobj = FrameProcessor()
fpobj.load_annotator(MetaAnnotator())
fpobj.load_annotator(DiffAnnotator(quantiles=[quantiles]))
fpobj.process(finput)
#fpobj.process(finput, max_batch=5)
obj = fpobj.collect_all()
meta = obj['meta'].todf()
obj['diff'].todf().head()
cagg = CutAggregator(cut_vals={
'h40': histdiff,
'q' + str(quantiles): cutvals
})
fps = meta['fps'][0]
print(fps)
df1 = cagg.aggregate(obj).todf()
df1['seconds_start'] = df1['frame_start'] / fps
df1['seconds_end'] = df1['frame_end'] / fps
out = df1.to_csv()
f = open(basename + ".csv", "w")
f.write(out)
f.close()