# SPDX-License-Identifier: MIT # Copyright (C) Intel Corporation # # Object Counting: DLStreamer pipeline sample. # See README.md for prerequisites and inputs. Run: python3 dlstreamer_sample.py from collections import Counter import gi gi.require_version("Gst", "1.0") gi.require_version("GstAnalytics", "1.0") from gi.repository import Gst, GLib, GstAnalytics Gst.init([]) INPUT_VIDEO = "test_video.mp4" # Only these classes are counted; the sample video contains pedestrians, # a cyclist, and cars. CLASSES_OF_INTEREST = {"person", "bicycle", "car"} # Select the model: "yolo26n" (default) or "detr-resnet-50". MODEL = "yolo26n" # For CPU: change device=GPU to device=CPU. # For NPU: change device=GPU to device=NPU (batch-size=1, nireq=4 recommended). pipeline_str = ( f"filesrc location={INPUT_VIDEO} ! decodebin3 ! " "videoconvert ! " f"gvadetect model={MODEL}_openvino_model/{MODEL}.xml " "device=GPU " "threshold=0.4 ! queue ! " "gvawatermark ! videoconvert ! video/x-raw,format=I420 ! " "openh264enc ! h264parse ! " "mp4mux ! filesink name=sink location=output_dlstreamer.mp4" ) pipeline = Gst.parse_launch(pipeline_str) def on_buffer(pad, info): buf = info.get_buffer() rmeta = GstAnalytics.buffer_get_analytics_relation_meta(buf) if rmeta is None: return Gst.PadProbeReturn.OK counts = Counter() idx = 1 while True: ok, od = rmeta.get_od_mtd(idx) if not ok: break label = GLib.quark_to_string(od.get_obj_type()) if label in CLASSES_OF_INTEREST: counts[label] += 1 idx += 1 if counts: summary = ", ".join(f"{n} {name}" for name, n in counts.items()) print(f"Object counts: {summary}", flush=True) return Gst.PadProbeReturn.OK sink = pipeline.get_by_name("sink") sink.get_static_pad("sink").add_probe(Gst.PadProbeType.BUFFER, on_buffer) pipeline.set_state(Gst.State.PLAYING) bus = pipeline.get_bus() bus.timed_pop_filtered( Gst.CLOCK_TIME_NONE, Gst.MessageType.EOS | Gst.MessageType.ERROR, ) pipeline.set_state(Gst.State.NULL)