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Fix Typos and Minor Corrections in Multi-Stream GStreamer README #439

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Fix Typos and Minor Corrections in Multi-Stream GStreamer README #439

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8 changes: 4 additions & 4 deletions samples/gstreamer/gst_launch/multi_stream/README.md
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# Video streams from multiple cameeras (gst-launch command line)
# Video streams from multiple cameras (gst-launch command line)

This sample demonstrates how to construct multi-stream pipeline via `gst-launch-1.0` command-line utility using detection and classification models.
It combines four pipelines. By default, the first streams run on NPU [Intel® Core™ Ultra processors] and the other two using the GPU device.
It combines four pipelines. By default, the first two streams run on NPU [Intel® Core™ Ultra processors] and the other two using the GPU device.

## How It Works
This sample utilizes GStreamer command-line tool `gst-launch-1.0` which can build and run GStreamer pipeline described in a string format.
Expand Down Expand Up @@ -65,9 +65,9 @@ gvadetect model=${DETECTION_MODEL} device=GPU pre-process-backend=vaapi-surface-
gvawatermark ! gvafpscounter ! vaapih264enc ! h264parse ! mp4mux ! filesink location=${OUTPUT_VIDEO_FILE_4}
```

The next pipeline illustrates how to construct a plipeline with multiple AI models and a single video stream.
The next pipeline illustrates how to construct a pipeline with multiple AI models and a single video stream.
In addition, this pipeline runs AI inference every 3 frames ('inference-inteval=3') and uses 'gvatrack' to keep analytics results for non-inferenced frames.
The example also batches inference requests ('batch-size=8') to maximize AI model throughput at the expense of single-reqeust lantency.
The example also batches inference requests ('batch-size=8') to maximize AI model throughput at the expense of single-request lantency.

```sh
gst-launch-1.0 \
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