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A quick example to set up a monitor on a live stream #127

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76 changes: 76 additions & 0 deletions docs/docs/getting-started/5-streaming.md
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# A Quick Example: Live Stream Alert

A quick example to get used to setting up detectors and asking good questions: set up a monitor on a live stream.

## Requirements

- [Groundlight SDK](/docs/installation/) with Python 3.7 or higher
- The video ID of a YouTube live stream you'd like to monitor
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## Installation

Ensure you have Python 3.7 or higher installed, and then install the Groundlight SDK and OpenCV library:

```bash
pip install groundlight pillow ffmpeg yt-dlp typer
```

## Creating the Application

1. Save this command as a shell script `get_last_frame.sh`:
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```
#!/bin/bash

ffmpeg -i "$(yt-dlp -g $1 | head -n 1)" -vframes 1 last.jpg -y
```

This will download the last frame from a YouTube live stream and save it to a local file `last.jpg`.

2. Log in to the [Groundlight application](https://app.groundlight.ai) and get an [API Token](api-tokens).

3. Next, we'll write the Python script for the application.

```python notest
import os
import subprocess
import typer
from groundlight import Groundlight
from PIL import Image

GROUNDLIGHT_API_TOKEN=os.getenv("GROUNDLIGHT_API_TOKEN")
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def main(*, video_id: str = None, detector_name: str = None, query: str = None, confidence: float = 0.75, wait: int = 60):
"""
Run the script to get the stream's last frame as a subprocess, and submit result as an image query to a Groundlight detector
:param video_id: Video ID of the YouTube live stream
:param detector_name: Name for your Groundlight detector
:param query: Question you want to ask of the stream (we will alert on the answer of NO)
"""
gl = Groundlight(api_token=GROUNDLIGHT_API_TOKEN)
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detector = gl.create_detector(name=detector_name, query=query, confidence_threshold=confidence)

while True:
p = subprocess.run(["./get_last_frame.sh", video_id])
if p.returncode != 0:
raise RuntimeError(f"Could not get image from video ID: {video_id}. Process exited with return code {p.returncode}.")

image = Image.open("last.jpg").convert("RGB")
response = gl.submit_image_query(detector=detector, image=image, wait=wait)

if response.result.label == "NO":
os.system("say 'Alert!'") # this may not work on all operating systems


if __name__ == "__main__":
typer.run(main)

```

4. Save the script as `streaming_alert.py` and run it:

```bash
python streaming_alert.py <VIDEO_ID> --detector_name <DETECTOR_NAME> --query <QUERY IN QUOTATION MARKS>
```

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