Here are several sample pipeline configurations that solve typical object recognition tasks. Get one of the available templates and load it while creating a new template.
Vehicle counters
This vehicle counting pipeline detects vehicles, tracks their movements and, if a vehicle crosses virtual line, generates a 'line_cross' event, that can be sent to an Output.
Pipeline element | Description |
---|---|
Vehicle detector | The neural net searches for all vehicles in the frame |
↓ | |
General object tracker | The tracking processor builds a track for each detected object, adding information about objects' movements. |
↓ | |
various filters | Add filters here to remove unwanted objects |
↓ | |
Line cross detector | The line cross processors checks if an object's path has crossed the virtual line and adds a 'line_cross' event. |
↓ | |
System DB | System DB output saves all line_cross events to the local DB. |
↓ | |
Notifications | In addition to the statistics, the notification output allows sending warnings if someone crosses a line. |
Downloads:
- Vehicle counting
- Trucks subclass recognition based on the size
- Vehicle counting, make and model recognition
License plate recognition
This pipeline detects and recognizes license plates. It generates 'lp_detected' event, that can be sent to an Output.
Pipeline element | Description |
---|---|
License plate detector | The neural net searches for all license plates in the detection area |
↓ | |
General object tracker | The tracking processor builds a track for each detected object, adding information about objects' movements. |
↓ | |
License plate recognition | The recognition converts license plate image into symbols. |
↓ | |
General event trigger | This trigger is needed to generate 'lp_detected' events. |
↓ | |
System DB | System DB output saves all events to the local DB. |
Downloads:
People gender/recognition plus counter
This people counting pipeline detects faces, recognizes age/gender, tracks their movements and, if a person crosses virtual line, saves this event to the DB.
Pipeline element | Description |
---|---|
Face detector | The neural net searches for all faces in the frame |
↓ | |
General object tracker | The tracking processor builds a track for each detected object, adding information about objects' movements. |
↓ | |
various filters | Add filters here to remove unwanted objects |
↓ | |
Age, gender, emotions recognition | The neural net recognizes person's age/gender. |
↓ | |
Pixelate | This processor can apply a pixel mask to the faces to match privacy requirements. |
↓ | |
Line cross detector | The line cross processors checks if an object's path has crossed the virtual line and adds a 'line_cross' event. |
↓ | |
System DB | System DB output saves all line_cross events to the local DB. |
Downloads:
Important
After you create the pipeline, don't forget to update 'active area', 'counting lines', etc and add an Output to the bottom of the pipeline (for example a [SYSTEM_DB])