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 = []