Image Captioning with CNN-LSTM

An implementation of an image captioning system using a CNN encoder and LSTM decoder. This project generates natural language descriptions of images using deep learning.

Features

• Encoder: ResNet-152 pretrained on ImageNet for image feature extraction
• Decoder: LSTM network for sequence generation
• Attention Mechanism: Generates captions by focusing on relevant parts of the image
• Pre-trained Models: Ready-to-use models available for quick inference

Installation

1. Clone the repository:

   git clone https://github.com/Saksham7685/image-captioning.git

2. Install dependencies:

   pip install -r requirements.txt

Training

To train the model:

1. Download the COCO dataset from download.sh file
2. Preprocess the data:

   python build_vocab.py
   python resize.py

3. Start training:

   python train.py

Sample Image

Input

Output

a dog is sitting on a green grass covered field