# tarsoliyaansh/ai-based-traffic-management architecture

> Architecture diagram of the GitHub repository tarsoliyaansh/ai-based-traffic-management, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-09-27). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/tarsoliyaansh/ai-based-traffic-management
- Repository: https://github.com/tarsoliyaansh/ai-based-traffic-management

## Overview

This is a web-based adaptive traffic-management system: a user uploads four intersection videos, the backend estimates vehicle counts for each, and a genetic algorithm returns recommended green-light times for the web interface. The graph follows the sampled React upload flow and Flask orchestration. The README documents the major capabilities; detection and optimization details are supported by sampled source, while model assets are shown as detector inputs.

Main entry points: [`backend/yolov4.py`](https://github.com/tarsoliyaansh/ai-based-traffic-management/blob/main/backend/yolov4.py) (Vehicle detection), [`backend/app.py`](https://github.com/tarsoliyaansh/ai-based-traffic-management/blob/main/backend/app.py) (Upload endpoint), [`frontend/src/App.js`](https://github.com/tarsoliyaansh/ai-based-traffic-management/blob/main/frontend/src/App.js) (Upload and results), [`backend/algo.py`](https://github.com/tarsoliyaansh/ai-based-traffic-management/blob/main/backend/algo.py) (Genetic optimizer)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_web["Web interface"]
  node_ui["Upload and results<br/>[App.js]"]
end

subgraph group_api["Request orchestration"]
  node_api_route["Upload endpoint<br/>[app.py]"]
  node_video_files["Uploaded videos<br/>[app.py]"]
  node_timings["Green-time recommendations<br/>[algo.py]"]
end

subgraph group_analysis["Traffic analysis"]
  node_detector["Vehicle detection<br/>[yolov4.py]"]
  node_class_names["Class names<br/>[classes.txt]"]
  node_yolo_config["YOLO configuration<br/>[yolov4-tiny.cfg]"]
  node_yolo_weights["YOLO weights"]
  node_optimizer["Genetic optimizer<br/>[algo.py]"]
end

node_user(("Traffic manager"))

node_user -->|"selects videos"| node_ui
node_ui -->|"posts four videos"| node_api_route
node_api_route -->|"saves videos"| node_video_files
node_api_route -->|"calls detection"| node_detector
node_detector -->|"reads videos"| node_video_files
node_detector -->|"reads classes"| node_class_names
node_detector -->|"loads config"| node_yolo_config
node_detector -->|"loads weights"| node_yolo_weights
node_detector -->|"returns counts"| node_api_route
node_api_route -->|"calls optimization"| node_optimizer
node_optimizer -->|"produces timings"| node_timings
node_api_route -->|"returns JSON"| node_ui
node_ui -->|"displays results"| node_timings

click node_ui "https://github.com/tarsoliyaansh/ai-based-traffic-management/blob/main/frontend/src/App.js"
click node_api_route "https://github.com/tarsoliyaansh/ai-based-traffic-management/blob/main/backend/app.py"
click node_video_files "https://github.com/tarsoliyaansh/ai-based-traffic-management/blob/main/backend/app.py"
click node_detector "https://github.com/tarsoliyaansh/ai-based-traffic-management/blob/main/backend/yolov4.py"
click node_class_names "https://github.com/tarsoliyaansh/ai-based-traffic-management/blob/main/backend/classes.txt"
click node_yolo_config "https://github.com/tarsoliyaansh/ai-based-traffic-management/blob/main/backend/yolov4-tiny.cfg"
click node_yolo_weights "https://github.com/tarsoliyaansh/ai-based-traffic-management/blob/main/backend/yolov4-tiny.weights"
click node_optimizer "https://github.com/tarsoliyaansh/ai-based-traffic-management/blob/main/backend/algo.py"
click node_timings "https://github.com/tarsoliyaansh/ai-based-traffic-management/blob/main/backend/algo.py"

classDef toneNeutral fill:#f8fafc,stroke:#334155,stroke-width:1.5px,color:#0f172a
classDef toneBlue fill:#dbeafe,stroke:#2563eb,stroke-width:1.5px,color:#172554
classDef toneAmber fill:#fef3c7,stroke:#d97706,stroke-width:1.5px,color:#78350f
classDef toneMint fill:#dcfce7,stroke:#16a34a,stroke-width:1.5px,color:#14532d
classDef toneRose fill:#ffe4e6,stroke:#e11d48,stroke-width:1.5px,color:#881337
classDef toneIndigo fill:#e0e7ff,stroke:#4f46e5,stroke-width:1.5px,color:#312e81
classDef toneTeal fill:#ccfbf1,stroke:#0f766e,stroke-width:1.5px,color:#134e4a
class node_ui toneBlue
class node_api_route,node_video_files,node_timings toneAmber
class node_detector,node_class_names,node_yolo_config,node_yolo_weights,node_optimizer toneMint
class node_user toneIndigo
```

## Components

### Web interface

- [Upload and results](https://github.com/tarsoliyaansh/ai-based-traffic-management/blob/main/frontend/src/App.js): `frontend/src/App.js`

### Request orchestration

- [Upload endpoint](https://github.com/tarsoliyaansh/ai-based-traffic-management/blob/main/backend/app.py): `backend/app.py`
- [Uploaded videos](https://github.com/tarsoliyaansh/ai-based-traffic-management/blob/main/backend/app.py): `backend/app.py`
- [Green-time recommendations](https://github.com/tarsoliyaansh/ai-based-traffic-management/blob/main/backend/algo.py): `backend/algo.py`

### Traffic analysis

- [Vehicle detection](https://github.com/tarsoliyaansh/ai-based-traffic-management/blob/main/backend/yolov4.py): `backend/yolov4.py`
- [Class names](https://github.com/tarsoliyaansh/ai-based-traffic-management/blob/main/backend/classes.txt): `backend/classes.txt`
- [YOLO configuration](https://github.com/tarsoliyaansh/ai-based-traffic-management/blob/main/backend/yolov4-tiny.cfg): `backend/yolov4-tiny.cfg`
- [YOLO weights](https://github.com/tarsoliyaansh/ai-based-traffic-management/blob/main/backend/yolov4-tiny.weights): `backend/yolov4-tiny.weights`
- [Genetic optimizer](https://github.com/tarsoliyaansh/ai-based-traffic-management/blob/main/backend/algo.py): `backend/algo.py`

### Other components

- **Traffic manager**

## Connections

- Traffic manager → Upload and results: selects videos
- Upload and results → Upload endpoint: posts four videos
- Upload endpoint → Uploaded videos: saves videos
- Upload endpoint → Vehicle detection: calls detection
- Vehicle detection → Uploaded videos: reads videos
- Vehicle detection → Class names: reads classes
- Vehicle detection → YOLO configuration: loads config
- Vehicle detection → YOLO weights: loads weights
- Vehicle detection → Upload endpoint: returns counts
- Upload endpoint → Genetic optimizer: calls optimization
- Genetic optimizer → Green-time recommendations: produces timings
- Upload endpoint → Upload and results: returns JSON
- Upload and results → Green-time recommendations: displays results