https://github.com/anzo52/pyouthere
Checks if human is in a picture or not
https://github.com/anzo52/pyouthere
album batch-processing gallery haarcascade human-detection human-or-not person-detection photo-organizer photo-sorter
Last synced: 8 months ago
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Checks if human is in a picture or not
- Host: GitHub
- URL: https://github.com/anzo52/pyouthere
- Owner: Anzo52
- License: gpl-3.0
- Created: 2023-12-31T19:22:21.000Z (almost 2 years ago)
- Default Branch: main
- Last Pushed: 2024-01-06T07:17:39.000Z (almost 2 years ago)
- Last Synced: 2025-01-01T19:13:37.029Z (9 months ago)
- Topics: album, batch-processing, gallery, haarcascade, human-detection, human-or-not, person-detection, photo-organizer, photo-sorter
- Language: Python
- Homepage:
- Size: 490 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# pyouthere
## Overview
pyouthere is a Python application that checks if a human is present in a picture. It utilizes various Haar cascades for detecting different parts of the human body and faces in images.
## Features
- Detection of humans in images using Haar cascades.
- Support for detecting full body, upper body, lower body, frontal face, and profile face.
- Functionality to process a single image or a directory of images.
- Organizing images into folders based on detection results.
## Requirements
The application requires the following Python packages:
- numpy>=1.26.2
- opencv-python>=4.9.0.80
- simple-term-menu>=1.6.4
These can be installed using the `requirements.txt` file.
## Usage
To use pyouthere, you can either process a single file or an entire directory of images. The application will then detect the presence of people in these images and organize them accordingly.
### Main Functions
- `detect_people(image_path)`: Detects people in a single image.
- `detect_in_dir(dir_path)`: Detects people in all images within a specified directory.
- `organize_files(with_people, no_people)`: Organizes images into 'with_people' and 'no_people' directories.
### Running the Application
Run `main.py` to start the application. You will be presented with options to choose between processing a single file, a directory, or exiting the application.
## Haar Cascades
The application uses several Haar cascade files for detection:
- haarcascade_frontalface_alt.xml
- haarcascade_fullbody.xml
- haarcascade_lowerbody.xml
- haarcascade_profileface.xml
- haarcascade_upperbody.xml
## Contributing
Contributions to pyouthere are welcome. Please ensure to follow the coding standards and guidelines of the project.
## License
This project is licensed under the [MIT License](https://github.com/Anzo52/pyouthere/blob/main/LICENSE).