# Add System Timestamps to Metadata

This tutorial will help you add a timestamp to the metadata of each frame. This tutorial shows
how to use the GST element `timecodestamper` that adds timestamps to frames.

## Steps
1. Update default `config.json` present at `[WORKDIR]/edge-ai-libraries/microservices/dlstreamer-pipeline-server/configs/default/config.json` with below configurations.

- Update "pipeline" variable as follows -
```sh
"pipeline": "{auto_source} ! decodebin ! timecodestamper set=always ! videoconvert ! gvadetect name=detection model-instance-id=inst0 ! queue ! gvafpscounter ! gvametaconvert add-empty-results=true name=metaconvert ! gvametapublish name=destination ! appsink name=appsink",
```

> **NOTE**: Make sure that proprety `set` of `timecodestamper` is set to `always`. The
> `timecodestamper` element follows SMPTE format of storing data (hours:minutes:seconds:frames).

`set` property can have anyone of the 3 values shown below
| Value  | Description |
| ------------- |:-------------:|
| never | Never set timecodes |
| keep | Keep upstream timecodes and only set if no upstream timecode |
| always | Always set timecode and remove upstream timecode |

Ensure that the changes made to the `config.json` are reflected in the container by volume mounting it as mentioned in this [tutorial](./change-dlstreamer-pipeline.md)

2. Start the DL Streamer Pipeline Server
```sh
cd [WORKDIR]/edge-ai-libraries/microservices/dlstreamer-pipeline-server/docker/
docker compose up
```

3. Open another terminal and run the following curl command to start the pipeline.
```sh
curl http://localhost:8080/pipelines/user_defined_pipelines/pallet_defect_detection -X POST -H 'Content-Type: application/json' -d '{
    "source": {
        "uri": "file:///home/pipeline-server/resources/videos/warehouse.avi",
        "type": "uri"
    },
    "destination": {
        "metadata": {
            "type": "file",
            "path": "/tmp/results.jsonl",
            "format": "json-lines"
        }
    },
    "parameters": {
        "detection-properties": {
            "model": "/home/pipeline-server/resources/models/geti/pallet_defect_detection/deployment/Detection/model/model.xml",
            "device": "CPU"
        }
    }
}'
```

4. To view the metadata, open another terminal and run the following command
```sh
tail -f /tmp/results.jsonl
```

You should see an attribute called `system_timestamp` in the metadata of each frame. Sample output of a metadata from one frame shown below -
```json
{"objects":[{"detection":{"bounding_box":{"x_max":0.37195673026144505,"x_min":0.02789940871298313,"y_max":0.7120070457458496,"y_min":0.17735711733500162},"confidence":0.9217351078987122,"label":"box","label_id":0},"h":257,"region_id":2319,"roi_type":"box","w":220,"x":18,"y":85},{"detection":{"bounding_box":{"x_max":0.17977098003029823,"x_min":0.06219940260052681,"y_max":0.42195435365041095,"y_min":0.3419050375620524},"confidence":0.9094383120536804,"label":"shipping_label","label_id":1},"h":38,"region_id":2320,"roi_type":"shipping_label","w":75,"x":40,"y":164}],"resolution":{"height":480,"width":640},"system_timestamp":"2025-06-02T08:15:14.870:+0000","tags":{},"timestamp":7766666666}
```