VisualAIProjects

This repository contains various projects related to computer vision and artificial intelligence.

Projects

DogCatClassifier

• Description: This project is a deep learning model that can classify images of dogs and cats.
• Link: DogCatClassifier

DrowsinessDetection

• Description: This project detects drowsiness in drivers using computer vision techniques.
• Link: DrowsinessDetection

FaceMaskDetection

• Description: This project detects whether a person is wearing a face mask or not in real-time.
• Link: FaceMaskDetection

FlowerClassifier17

• Description: This project is a deep learning model that classifies images of flowers into 17 different categories.
• Link: FlowerClassifier17

HousingPricePrediction

• Description: This project predicts housing prices using machine learning algorithms.
• Link: HousingPricePrediction

SegmentAnythingAI

• Description: This project performs image segmentation using advanced deep learning techniques.
• Link: SegmentAnythingAI

SatelliteImageClustering

• Description: This project applies clustering algorithms to satellite images for analyzing patterns.
• Link: SatelliteImageClustering

TransformerObjectDetection

• Description: This project utilizes transformer-based models for object detection in images.
• Link: TransformerObjectDetection

ImageRecognition

• Description: This project performs real-time image recognition using a webcam feed.
• Link: ImageRecognition

XrayDiseaseDetection

• Description: This project uses deep learning to detect diseases from X-ray images.
• Link: XrayDiseaseDetection

Getting Started

To get started with the projects in this repository, you can clone the repository locally by running the following command:

git clone https://github.com/MohammadMoradpoor/VisualAIProjects.git

Make sure you have Git installed on your system. After cloning the repository, you can navigate to each project's directory and explore the code.

Contribution

Contributions to this repository are welcome. If you would like to contribute, please follow these guidelines:

• Fork the repository and clone it locally.
• Create a new branch for your feature or bug fix.
• Make your changes and commit them with descriptive commit messages.
• Push your changes to your forked repository.
• Submit a pull request detailing your changes.