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.
- 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.
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.
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.
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.
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.
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
Contributions to pyouthere are welcome. Please ensure to follow the coding standards and guidelines of the project.
This project is licensed under the MIT License.