def process_frame(self, frame: VideoFrame) -> bool:
timestamp = int(round(time.time()*1000))
events = []
new_counts = Counter()
for detection in frame.regions():
new_counts[detection.meta().get_roi_type()] += 1
for key, count in new_counts.items():
if key in self.item_count:
if count > self.item_count[key]:
for x in range(0, count-self.item_count[key]):
events.append({'event_time': timestamp,
'roi_action': 'ENTER',
'object_id': key})
elif count < self.item_count[key]:
for x in range(0, self.item_count[key]-count):
events.append({'event_time': timestamp,
'roi_action': 'DEPART',
'object_id': key})
else:
for x in range(0, count):
events.append({'event_time': timestamp,
'roi_action': 'ENTER',
'object_id': key})
for key, count in self.item_count.items():
if key not in new_counts:
for x in range(0, count):
events.append({'event_time': timestamp,
'roi_action': 'DEPART',
'object_id': key})
if events:
frame.add_message(json.dumps(events))
self.item_count = new_counts
if self.item_count['bottle'] <= 1:
frame.add_region(0, 0, 0, 0, 0, region_tensor=REGION_TENSOR)
else:
frame.add_region(0, 0, 0, 0, 0, region_tensor=VideoFrame.create_labels_structure(
["Bottle Count: " + str(self.item_count['bottle'])]))
if (self.item_count['person'] > 0) and self.redact_person:
with frame.data() as contents:
contents[:] = 0
self.remove_regions(frame)
frame.add_region(0, 0, 0, 0, 1, region_tensor=REGION_TENSOR)
return True
#
# SPDX-License-Identifier: MIT
# ==============================================================================
import sys
import gi
gi.require_version('Gst', '1.0')
from gi.repository import Gst, GObject
from gstgva import VideoFrame
DETECT_THRESHOLD = 0.5
Gst.init(sys.argv)
REGION_TENSOR = VideoFrame.create_labels_structure(
["background", "face", "my_label_2", "etc."])
def process_frame(frame: VideoFrame,
threshold: float = DETECT_THRESHOLD) -> bool:
width = frame.video_info().width
height = frame.video_info().height
for tensor in frame.tensors():
dims = tensor.dims()
data = tensor.data()
object_size = dims[-1]
for i in range(dims[-2]):
image_id = data[i * object_size + 0]
confidence = data[i * object_size + 2]
x_min = int(data[i * object_size + 3] * width + 0.5)
# ==============================================================================
import sys
import json
import time
from collections import Counter
import gi
gi.require_version('Gst', '1.0')
from gi.repository import Gst, GObject
from gstgva import VideoFrame
Gst.init(sys.argv)
REGION_TENSOR = VideoFrame.create_labels_structure(
["LOW COUNT", "PERSON DETECTED FRAME DELETED"])
class BottleCount:
def __init__(self, redact_person: bool = True):
self.redact_person = redact_person
self.item_count = Counter()
def remove_regions(self, frame: VideoFrame):
for _ in range(len(frame.regions())):
frame.pop_region()
def process_frame(self, frame: VideoFrame) -> bool:
timestamp = int(round(time.time()*1000))
events = []