📚 Cartoon Captioning Project

Welcome to the Cartoon Captioning Project! This project aims to generate captions for cartoon images using deep learning or transformer based techniques. You can choose between two model architectures: LSTM-CNN and ViT-GPT2.

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🌟 Features

• Data Loading and Preprocessing
• Exploratory Data Analysis (EDA)
• Model Training and Evaluation
• Visualization of Results

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🏗️ Directory Structure

cartoon_captioning/
│
├── config/
│   └── config.yaml
├── data/
│   ├── dataset.py
│   └── load_data.py
├── eda/
│   ├── eda.py
│   └── plot.py
├── models/
│   ├── lstm_cnn.py
│   ├── vit_gpt2.py
│   ├── build_model.py
│   ├── train_model.py
│   └── evaluate_model.py
├── utils/
│   ├── image_processing.py
│   └── text_processing.py
├── train.py
└── requirements.txt

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⚙️ Installation

  cd cartoon-image-generator
  python -m venv cap_env
  source cap_env/bin/activate
  pip install -r requirements.txt

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🔧 Configuration

embedding_dim: 256
units: 256
vocab_size : 10000
image_feature_dim : 100352
batch_size: 32
epochs: 2
model_save_path: 'models/saved_model'
tokenizer_path: 'models/tokenizer.pkl'
max_length: 40
model_type: 'lstm_cnn'  # or 'vit_gpt2' for using 'ViT-GPT2' model

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🚀 Running Script

python train.py --config config/config.yaml --model_type lstm_cnn

python train.py --config config/config.yaml --model_type vit_gpt2

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🖼️ Example Outputs

EDA

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Models Training

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🌐 Running App

python app.py --config config/config.yaml
http://127.0.0.1:5000