# Available Sample Apps
This page indexes all DL Streamer samples by use case. See
[Using Sample Apps](./using_sample_apps.md) for installation, model download, and run
instructions before trying any of the samples below.
Each entry below is a mini "card": name, a one-line preview thumbnail (when available), what it
demonstrates, the elements/models it uses, and its language — `CLI` (`gst-launch` command line),
`Python`, or `C++`.
---
## Browse by category
| | |
| --- | --- |
| [Object detection, classification & segmentation (9)](#object-detection-classification--segmentation) | [Object tracking & analytics (3)](#object-tracking--analytics) |
| [Vision-Language Models (VLM) & GenAI (5)](#vision-language-models-vlm--genai) | [Audio analytics (2)](#audio-analytics) |
| [3D: LiDAR & radar (5)](#3d-lidar--radar) | [Cameras & input sources (4)](#cameras--input-sources) |
| [Metadata: publishing, access & visualization (8)](#metadata-publishing-access--visualization) | [Customization & extensibility (8)](#customization--extensibility) |
| [Performance & benchmarking (2)](#performance--benchmarking) | [Interoperability (2)](#interoperability) |
| [Auto-generated reference applications (8)](#auto-generated-reference-applications) | |
> [!TIP]
> Use your browser's find-in-page (Ctrl+F / Cmd+F) to search across all samples by name,
> element (e.g. `gvadetect`), or model (e.g. `yolo11n`).
---
### Object detection, classification & segmentation
| Preview | Sample |
| --- | --- |
|  | [Detection with YOLO](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/detection_with_yolo) `CLI`
Object detection and classification with publicly available YOLO models.
**Key elements:** `gvadetect`, `gvaclassify`
**Models:** `yolox_s` (default; many YOLO variants) |
|  | [Face Detection and Classification](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/face_detection_and_classification) `CLI`
Detect faces and estimate age, gender, emotions and facial landmarks.
**Key elements:** `gvadetect`, `gvaclassify`
**Models:** `centerface`, `dima806_facial_age_image_detection`, `dima806_fairface_gender_image_detection`, `dima806_face_emotions_image_detection` |
|  | [Instance Segmentation](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/instance_segmentation) `CLI`
Instance segmentation with YOLO-seg models visualized by `gvawatermark`.
**Key elements:** `gvadetect`, `gvawatermark`
**Models:** `yolo26s-seg` (default; also `yolo11s-seg`) |
|  | [Human Pose Estimation](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/human_pose_estimation) `CLI`
Full-frame human pose estimation.
**Key elements:** `gvaclassify`
**Models:** `yolo26s-pose` |
|  | [Depth Estimation](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/depth_estimation) `CLI`
YOLO11n detection followed by Depth Anything V2 depth estimation on detected regions.
**Key elements:** `gvadetect`, `gvainference`
**Models:** `yolo11n`, `Depth-Anything-V2-Small-hf` |
|  | [License Plate Recognition](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/license_plate_recognition) `CLI`
YOLO detector combined with an optical character recognition model.
**Key elements:** `gvadetect`, `gvainference`
**Models:** `yolov8` license-plate detector, `PP-OCRv4` |
|  | [Prompt-based Object Detection](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/python/prompted_detection) `Python`
Search a video for user-defined objects using an open-vocabulary model (YOLOE).
**Key elements:** `gvadetect`
**Models:** `yoloe-26s-seg` (text-prompt, class baked in at export) |
|  | [Deployment of Geti™ models](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/geti_deployment) `CLI`
Deploy Geti™-trained models for detection, anomaly detection and classification.
**Key elements:** `gvadetect`, `gvaclassify`
**Models:** Geti™-trained (Padim / STFPM / UFlow) |
|  | [Motion Detect](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/motion_detect) `CLI`
Run detection only over motion ROIs (GPU and CPU paths).
**Key elements:** `gvamotiondetect`, `gvadetect`
**Models:** `yolov8n` |
### Object tracking & analytics
| Preview | Sample |
| --- | --- |
|  | [Vehicle and Pedestrian Tracking](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/vehicle_pedestrian_tracking) `CLI`
Object tracking across frames.
**Key elements:** `gvatrack`, `gvadetect`, `gvaclassify`
**Models:** `yolo26s`, `dima806_vehicle_10_types_image_detection` |
|  | [Vehicle Counter with gvaanalytics Tripwires](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/python/gvaanalytics_tripwire) `Python`
Count vehicles crossing a virtual line in both directions using tripwires.
**Key elements:** `gvaanalytics`, `gvatrack`
**Models:** `yolo11n` |
|  | [Smart NVR for Lane Hogging Detection](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/python/smart_nvr) `Python`
Build an NVR with custom analytics and video storage to detect lane-hogging events.
**Key elements:** `gvaanalytics_py`, `gvarecorder_py`
**Models:** `rtdetr_v2_r50vd` (RT-DETRv2) |
### Vision-Language Models (VLM) & GenAI
| Preview | Sample |
| --- | --- |
|  | [Using VLM Models with gvagenai](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/gvagenai) `CLI`
Video summarization with MiniCPM-V.
**Key elements:** `gvagenai`
**Models:** `MiniCPM-V`, `Phi-4-multimodal-instruct` or `Gemma-3` |
|  | [VLM Alerts](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/python/vlm_alerts) `Python`
Edge alerting pipeline that generates structured JSON alerts per frame with annotated video.
**Key elements:** `gvagenai`
**Models:** Configurable VLM (e.g. `Qwen2.5-VL`, `InternVL`) |
|  | [VLM-assisted Self Checkout](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/python/vlm_self_checkout) `Python`
Combine CV object detection with a VLM for item classification, running both locally on edge.
**Key elements:** `gvadetect`, `gvagenai`
**Models:** `yolo26s`, `MiniCPM-V-4_5` |
|  | [ONVIF Camera Analytics Validation](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/python/onvif_camera_analytics_validation) `Python`
Use a VLM as an additional validation layer for ONVIF-enabled analytics cameras.
**Key elements:** `gvagenai`
**Models:** Configurable VLM |
|  | [Image Embeddings Generation with ViT](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/lvm) `CLI`
Generate image embeddings using the Vision Transformer component of a CLIP model.
**Key elements:** `gvainference`
**Models:** `clip-vit-large-patch14` (CLIP ViT) |
### Audio analytics
| Preview | Sample |
| --- | --- |
|  | [Audio Event Detection](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/audio_detect) `CLI`
Audio event detection, converting results to JSON.
**Key elements:** `gvaaudiodetect`, `gvametaconvert`, `gvametapublish`
**Models:** `aclnet` |
|  | [Audio Transcription](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/audio_transcribe) `CLI`
Speech transcription using an OpenVINO GenAI Whisper model.
**Key elements:** `gvaaudiotranscribe`
**Models:** `whisper` |
### 3D: LiDAR & radar
| Preview | Sample |
| --- | --- |
|  | [PointPillars Inference with g3dinference](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/g3dinference) `CLI`
Complete LiDAR-only 3D detection pipeline.
**Key elements:** `g3dlidarparse`, `g3dinference`
**Models:** `PointPillars` |
|  | [LiDAR Parse](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/g3dlidarparse) `CLI`
LiDAR parsing pipeline.
**Key elements:** `g3dlidarparse`
**Models:** — (parsing only) |
|  | [Live LiDAR Capture](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/g3dlidarsrc) `CLI`
Real-time LiDAR capture from a physical device (RoboSense via rs_driver).
**Key elements:** `g3dlidarsrc`, `g3dinference`
**Models:** `PointPillars` |
|  | [Camera + 3D Object Fusion](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/g3dobjectfuser) `CLI`
Fuse 2D camera detections with 3D LiDAR detections.
**Key elements:** `g3dobjectfuser`, `gvastreammux`
**Models:** `yolo11n`, `PointPillars` |
|  | [Radar Signal Process](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/g3dradarprocess) `CLI`
mmWave radar signal processing with point-cloud detection, clustering and tracking.
**Key elements:** `g3dradarprocess`
**Models:** — (signal processing) |
### Cameras & input sources
| Preview | Sample |
| --- | --- |
|  | [RealSense™ Camera](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/gvarealsense) `CLI`
Capture a video stream from a 3D Intel RealSense™ Depth Camera.
**Key elements:** `gvarealsense`
**Models:** — (capture only) |
|  | [ONVIF Camera Discovery](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/python/onvif_cameras_discovery) `Python`
Automatically discover ONVIF cameras on the network and launch pipelines for each.
**Key elements:** `gvadetect`
**Models:** Configurable detector |
|  | [Multi-camera deployments](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/multi_stream) `CLI`
Handle video streams from multiple cameras in a single application.
**Key elements:** `gvadetect`, `gvafpscounter`
**Models:** `yolo11s` (many YOLO variants) |
|  | [Multi-Stream Mux/Demux](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/stream_mux_and_demux) `CLI`
Share a single inference pipeline across streams with per-source routing.
**Key elements:** `gvastreammux`, `gvastreamdemux`
**Models:** Configurable detector |
### Metadata: publishing, access & visualization
| Preview | Sample |
| --- | --- |
|  | [Metadata Publishing](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/metapublish) `CLI`
Convert inference metadata to JSON and publish to file or Kafka/MQTT.
**Key elements:** `gvametaconvert`, `gvametapublish`
**Models:** `centerface`, `dima806_fairface_gender_image_detection`, `dima806_facial_age_image_detection` |
|  | [gvaattachroi](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/gvaattachroi) `CLI`
Define the regions on which inference should be performed.
**Key elements:** `gvaattachroi`, `gvadetect`
**Models:** `yolov8s` |
|  | [FPS Throttle](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/gvafpsthrottle) `CLI`
Throttle framerate independently of sink sync, without frame duplication or dropping.
**Key elements:** `gvafpsthrottle`
**Models:** — |
|  | [Watermark Metadata](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/python/watermark_meta) `Python`
Attach custom drawing primitives (hexagons, lines, circles, text) and render them.
**Key elements:** `gvawatermark`
**Models:** — (drawing only) |
|  | [Draw Face Attributes (C++)](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/cpp/draw_face_attributes) `C++`
Set a C callback to access frame metadata and visualize inference results.
**Key elements:** `gvadetect`, `gvaclassify`
**Models:** `centerface`, `dima806_facial_age_image_detection`, `dima806_fairface_gender_image_detection`, `dima806_face_emotions_image_detection` |
|  | [Draw Face Attributes (Python)](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/python/draw_face_attributes) `Python`
Set a Python callback to access frame metadata and visualize inference results.
**Key elements:** `gvadetect`, `gvaclassify`
**Models:** `centerface`, `dima806_facial_age_image_detection`, `dima806_fairface_gender_image_detection`, `dima806_face_emotions_image_detection` |
|  | [Open Close Valve](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/python/open_close_valve) `Python`
Open/close a GStreamer `valve` branch from a callback based on detection results.
**Key elements:** `gvadetect`, `valve`
**Models:** `yolo11s`, `dima806_vehicle_10_types_image_detection` |
|  | [Hello DL Streamer](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/python/hello_dlstreamer) `Python`
Build a detection pipeline, analyze metadata to count objects, and visualize results.
**Key elements:** `gvadetect`, `gvawatermark`
**Models:** `yolo11n` |
### Customization & extensibility
| Preview | Sample |
| --- | --- |
|  | [Custom Post-Processing Library — Classification](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/custom_postproc/classify) `CLI`, `C++`
Write a custom post-processing library that converts emotion-classification outputs to GstAnalytics metadata.
**Key elements:** `gvaclassify`
**Models:** `centerface`, `hsemotion` |
|  | [Custom Post-Processing Library — Detection](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/custom_postproc/detect) `CLI`, `C++`
Write a custom post-processing library that converts YOLOv11 tensor outputs to detection metadata.
**Key elements:** `gvadetect`
**Models:** `yolo11s` |
|  | [gvapython — Face Detection and Classification](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/gvapython/face_detection_and_classification) `CLI`, `Python`
Customize a pipeline with a Python script for inference post-processing.
**Key elements:** `gvapython`, `gvadetect`, `gvaclassify`
**Models:** `centerface`, `dima806_fairface_gender_image_detection`, `dima806_facial_age_image_detection` |
|  | [gvapython — Save Frames with ROI](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/gvapython/save_frames_with_ROI_only) `CLI`, `Python`
Use `gvapython` to save video frames containing detected objects to disk.
**Key elements:** `gvapython`, `gvadetect`
**Models:** `centerface` |
|  | [python-elements — Face Detection and Classification](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/python-elements/face_detection_and_classification) `CLI`, `Python`
Build a custom Python GStreamer element using the GstAnalytics metadata API.
**Key elements:** `gvaagelogger_py`, `gvadetect`, `gvaclassify`
**Models:** `YOLOv8-Face-Detection`, `fairface_age_image_detection`, `fairface_gender_image_detection` |
|  | [python-elements — Save Frames with ROI](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/python-elements/save_frames_with_ROI_only) `CLI`, `Python`
Build a custom Python GStreamer element to save frames with detected objects.
**Key elements:** `gvaframesaver_py`, `gvadetect`
**Models:** `YOLOv8-Face-Detection` |
|  | [python-elements — Loitering Detection](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/gst_launch/python-elements/loitering_detection) `CLI`, `Python`
Measure object dwell time with a custom Python element and render a visual alert when the threshold is exceeded.
**Key elements:** `gvaanalytics`, `gvawatermark`
**Models:** `yolo11s` |
|  | [Face Detection and Classification (Python)](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/python/face_detection_and_classification) `Python`
Download models from Hugging Face, export to OpenVINO IR, and run inference.
**Key elements:** `gvadetect`, `gvaclassify`
**Models:** `YOLOv8-Face-Detection`, `fairface` |
### Performance & benchmarking
| Preview | Sample |
| --- | --- |
|  | [Benchmark](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/benchmark) `CLI`, `Python`
Measure the performance of single- or multi-channel video analytics pipelines.
**Key elements:** `gvadetect`, `gvafpscounter`
**Models:** `centerface` (configurable) |
|  | [DL Streamer E2E Performance](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/e2e_performance) `Python`
Compare DL Streamer vs. OpenCV + OpenVINO throughput with a YOLO26s INT8 model.
**Key elements:** `gvadetect`
**Models:** `yolo26s` (INT8) |
### Interoperability
| Preview | Sample |
| --- | --- |
|  | [DL Streamer and DeepStream Coexistence](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/python/coexistence) `Python`
Run pipelines on DL Streamer and/or NVIDIA DeepStream side by side.
**Key elements:** `gvadetect`
**Models:** `yolov8` license-plate detector, `PP-OCRv4` |
|  | [Coexistence Benchmark](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/gstreamer/python/coexistence_benchmark) `Python`
Measure the maximum number of concurrent LPR streams on systems combining Intel and NVIDIA hardware.
**Key elements:** `gvadetect`
**Models:** `yolov8` license-plate detector, `PP-OCRv4` |
## Auto-generated reference applications
These end-to-end reference apps combine multiple elements into complete solutions.
Find them under
[samples/auto_generated_samples](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/auto_generated_samples).
| Preview | Sample |
| --- | --- |
|  | [DeepStream Test4 → DL Streamer Conversion](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/auto_generated_samples/deepstream_python_conversion) `CLI`
DL Streamer equivalent of NVIDIA's deepstream-test4 with YOLO11n detection and metadata publishing.
**Key elements:** `gvadetect`, `gvametaconvert`, `gvametapublish`
**Models:** `yolo11n` |
|  | [DeepStream LPR App Conversion (C++)](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/auto_generated_samples/deepstream_cpp_conversion) `C++`
C++ conversion of NVIDIA's DeepStream LPR app — license plate detection, tracking and text recognition.
**Key elements:** `gvadetect`, `gvatrack`, `gvaclassify`
**Models:** YOLOv11, PaddleOCR |
|  | [License Plate Recognition](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/auto_generated_samples/license_plate_recognition) `CLI`
Detect license plates with YOLOv11 and recognize text with PaddleOCR.
**Key elements:** `gvadetect`, `gvainference`
**Models:** `YOLOv11`, `PaddleOCR` |
|  | [Multi-Stream Compose](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/auto_generated_samples/multi_stream_compose) `CLI`
Multi-camera analytics with composite WebRTC output, on-demand recording and a 2x2 GPU-accelerated mosaic.
**Key elements:** `gvadetect`, `gvastreammux`, `gvawatermark`
**Models:** `yolo11s` |
|  | [People Detection and Tracking with Deep SORT](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/auto_generated_samples/people_detection_tracking) `CLI`
Detect and track people using YOLO26m and Deep SORT with a Mars-Small-128 re-ID model.
**Key elements:** `gvadetect`, `gvatrack`
**Models:** `yolo26m`, `mars-small128` |
|  | [Pose Estimation Compose](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/auto_generated_samples/pose_estimation_compose) `CLI`
Run 4 YOLO pose models in parallel on the same video and composite results into a 2x2 mosaic.
**Key elements:** `gvaclassify`, `gvawatermark`
**Models:** `yolo26n-pose`, `yolo11n-pose`, `yolov8n-pose`, `yolov8l-pose` |
|  | [Safety Compliance Monitor](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/auto_generated_samples/safety_compliance) `CLI`
Detect and track workers and use Qwen2.5-VL to verify helmet and harness compliance.
**Key elements:** `gvadetect`, `gvatrack`, `gvagenai`
**Models:** `yolo26m`, `Qwen2.5-VL-3B` |
|  | [Smart NVR — Event-Based Recording](https://github.com/open-edge-platform/dlstreamer/tree/main/samples/auto_generated_samples/smart_nvr) `CLI`
Detect people with YOLO11n and record video only when a person is present.
**Key elements:** `gvadetect`
**Models:** `yolo11n` |