🖼️ Image Caption Generator

Overview

The Image Caption Generator is a machine learning project that generates captions for images using deep learning techniques. This project utilizes a combination of Convolutional Neural Networks (CNNs) for image feature extraction and Recurrent Neural Networks (RNNs), specifically Long Short-Term Memory (LSTM) networks, for sequence generation.

✨ Features

• 📸 Extracts features from images using a pre-trained CNN (e.g., InceptionV3, VGG16).
• 📝 Generates captions using an LSTM-based RNN.
• 📂 Supports training on custom datasets.
• 🌐 Provides a user interface for uploading images and displaying generated captions.

🚀 Getting Started

Prerequisites

• 🐍 Python 3.7 or higher
• 📦 TensorFlow 2.x
• 🧮 NumPy
• 🐼 Pandas
• 📊 Matplotlib
• 🖼️ Pillow
• 🖥️ Flask (for the web interface)

📥 Installation

1. Clone the repository:

   git clone https://github.com/your-username/image-caption-generator.git
   cd image-caption-generator

2. Install the required packages:

   pip install -r requirements.txt

📚 Dataset

For training, we use the MS COCO dataset. Download and extract the dataset.

🏋️‍♂️ Training the Model

1. Extract image features using a pre-trained CNN:

   python extract_features.py --dataset_path path/to/coco/images --output_path path/to/save/features

2. Preprocess the captions and prepare the dataset:

   python preprocess_captions.py --annotations_path path/to/coco/annotations --output_path path/to/save/preprocessed/data

3. Train the model:

   python train.py --features_path path/to/saved/features --captions_path path/to/preprocessed/data --output_model_path path/to/save/model

🖼️ Generating Captions

To generate captions for new images:

1. Run the caption generation script:

   python generate_caption.py --image_path path/to/image --model_path path/to/saved/model

2. Or, use the web interface:

   python app.py

   Open your browser and go to http://127.0.0.1:5000 to upload an image and get the caption.

📂 Project Structure

• extract_features.py: Script to extract image features using a pre-trained CNN.
• preprocess_captions.py: Script to preprocess captions and prepare the dataset.
• train.py: Script to train the image captioning model.
• generate_caption.py: Script to generate captions for new images.
• app.py: Flask application for the web interface.
• model.py: Contains the model architecture and related functions.
• utils.py: Utility functions for data processing and model operations.

📑 References

• Show and Tell: A Neural Image Caption Generator
• MS COCO Dataset

📜 License

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

🙏 Acknowledgements

• The TensorFlow and Keras teams for their excellent deep learning libraries.
• The creators of the MS COCO dataset for providing a valuable resource for training image captioning models.