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docs: clarify project structure [closes #5] #6

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33 changes: 33 additions & 0 deletions README.md
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Expand Up @@ -9,6 +9,39 @@ This project is about videosources emergency detection made with ZeroMQ infrastr
- OpenCV
- Multiprocessing & Threading

## Project structure
```
videoanalytics/
├── run.py # Entry point: spawns broker, workers, cameras and GUI processes
├── broker.py # ZeroMQ router: subscribes to cameras, fans frames out to workers
├── cameras/
│ └── cam.py # Reads videosources and publishes encoded frames over ZeroMQ
├── workers/
│ └── worker.py # Runs YOLO detection + PSNR per frame, pushes results to the GUI
├── gui.py # Pulls results, draws detections/warnings on a grid canvas
├── config.py # Loads config.json into a global `config` dict
├── config.json # Sources, workers, models, GUI address and PSNR threshold
├── psnr.py # CLI tool to generate meanframes for PSNR ("normal" reference)
├── colors.py # Standalone helper to inspect a video's color distribution
├── requirements.txt # Python dependencies
├── models/ # YOLO model weights (download separately, see Preparations)
├── videos/ # Test videos and their meanframes (download separately)
└── media/ # Demo assets used in this README
```

### Data flow
```
cameras/cam.py ──(PUB frames)──▶ broker.py ──(PUSH frame)──▶ workers/worker.py
│
(PUSH detections + PSNR)
▼
gui.py
```
- **cameras/cam.py** runs one process per source, encodes frames as JPEG and publishes them.
- **broker.py** routes each frame to the worker matching its source id.
- **workers/worker.py** runs the fire and forklift YOLO models plus a PSNR check against the source meanframe, then forwards the annotated data.
- **gui.py** renders every source in a grid, overlaying detections and `WARNING!`/`FIRE!` alerts.

## Prerequisites

- Torch with CUDA
Expand Down