zyxwvo / ai-classification

🌟 This repository houses a collection of image classification models for various purposes, including vehicle, object, animal, and flower classification. Each classifier is built using deep learning techniques and pre-trained models to accurately identify and categorize images based on their respective classes.

AI Classifiers

This repository contains Python scripts for vehicle classification and object classification using pre-trained deep learning models. The vehicle classification logic uses the YOLOv3 model for vehicle detection and classification, while the object classification logic uses a pre-trained model for object classification. These scripts can be used to classify vehicles in videos and objects in images, respectively.

This repository contains two directories: one for vehicle classification logic and another for object classification logic, namely vehicle_classification and object_classification. Each directory contains the necessary files and instructions to run the respective classification logic.

Table of Contents

• Vehicle Classification
  • Files Included
  • Getting Started
  • Output
  • Contact Information
  • License
• Flower Classification
  • Files Included
  • Getting Started
  • Output
• Object Classification
  • Files Included
  • Getting Started
  • Output
• Animal Classification
  • Files Included
  • Getting Started
  • Output

Vehicle Classification

Files Included

• coco.names: Class names used for vehicle detection.
• traffic.mp4: Sample video for vehicle detection.
• yolov3.cfg: YOLOv3 model configuration file.
• yolov3.weights: Pre-trained YOLOv3 model weights.
• vehicle_detection.py: Python script for vehicle detection and classification.

Getting Started

1. Clone the Repository

   git clone https://github.com/hoangsonww/AI-Classification.git
   cd AI-Classification/Vehicle-Classification

2. Download Model Weights Download the pre-trained YOLOv3 model weights (yolov3.weights) from the official YOLO website or another trusted source and place it in the Vehicle-Classification directory.

3. Install Dependencies Install the required Python dependencies.

   pip install -r requirements.txt

4. Run Vehicle Detection Replace <video_path> in the vehicle_detection.py script with the path to your video file (traffic.mp4 or another video).

   python vehicle_detection.py

The script will then process the video frame by frame, detect vehicles, and classify them based on the detected classes. The output video will be saved as output.avi in the vehicle_classification directory.

Feel free to change the video path, output video name, and other parameters in the script to suit your needs.

Output

The output video will display the detected vehicles along with their class labels. The class labels are based on the COCO dataset, which includes various classes such as car, truck, bus, motorcycle, and bicycle.

Example output:

License

This project is licensed under the MIT License - see the LICENSE file for details.

Flower Classification

Files Included

• flower_classification.py: Python script for flower classification.
• daisy.jpg: Sample JPEG image for flower classification (Daisy).
• marigold.jpg: Sample JPEG image for flower classification (Marigold).

Getting Started

Getting Started

1. Clone the Repository

   git clone https://github.com/hoangsonww/AI-Classification.git
   cd AI-Classification/Flowers-Classification

2. Install Dependencies Install the required Python dependencies.

   pip install -r requirements.txt

3. Run Object Classification Replace <image_path> in the flower_classification.py script with the path to your image file (objects.jpg, objects.png, or another image).

   python flower_classification.py

Output

The output will display the class label of the flower detected in the image along with the confidence score.

Example output: Here are the sample image of Daisy flowers.

Object Classification

Files Included

• object_classification.py: Python script for object classification.
• objects.jpg: Sample JPEG image for object classification.
• objects.png: Sample PNG image for object classification.

Getting Started

1. Clone the Repository

   git clone https://github.com/hoangsonww/AI-Classification.git
   cd AI-Classification/object_classification

2. Install Dependencies Install the required Python dependencies.

   pip install -r requirements.txt

3. Run Object Classification Replace <image_path> in the object_classification.py script with the path to your image file (objects.jpg, objects.png, or another image).

   python object_classification.py

The script will then classify the objects in the image and display the class labels along with the confidence scores.

Feel free to change the image path and other parameters in the script to suit your needs.

Output

The output will display the class labels of the objects detected in the image along with the confidence scores.

Animal Classification

Files Included

• animal_classification.py: Python script for animal classification.
• cow.jpg: Sample JPEG image for animal classification (Cow).
• ox.jpg: Sample JPEG image for animal classification (Ox).

Getting Started

1. Clone the Repository

   git clone https://github.com/hoangsonww/AI-Classification.git
   cd AI-Classification/Animal-Classification

2. Install Dependencies Install the required Python dependencies.

   pip install -r requirements.txt

3. Run Object Classification Replace <image_path> in the animal_classification.py script with the path to your image file (objects.jpg, objects.png, or another image).

   python animal_classification.py

Output

The output will display the class labels of the animals detected in the image along with the confidence scores.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contact Information

For any questions or issues, please contact:

• Name: Son Nguyen
• Email: [email protected]

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