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🌟 E-commerce Product Image Augmentation Using GANs 🌟

📂 Project Structure

ecommerce-gan-augmentation/
├── 📁 data/
│   ├── 📁 raw/
│   ├── 📁 processed/
│   ├── 📁 augmented/
├── 📁 models/
│   ├── 📁 generator/
│   ├── 📁 discriminator/
│   ├── 📁 trained_model/
├── 📁 notebooks/
│   ├── 📓 data_preprocessing.ipynb
│   ├── 📓 model_training.ipynb
│   ├── 📓 model_evaluation.ipynb
├── 📁 scripts/
│   ├── 📝 train_gan.py
│   ├── 📝 evaluate_gan.py
│   ├── 📝 deploy_model.py
├── 📄 README.md
├── 📄 requirements.txt
└── 🗂️ .gitignore

🛠️ Setup Instructions

  1. Install the required packages:

    pip install -r requirements.txt
  2. Preprocess the dataset:

    jupyter notebook notebooks/data_preprocessing.ipynb
  3. Train the GAN model:

    python scripts/train_gan.py
  4. Evaluate the GAN model:

    jupyter notebook notebooks/model_evaluation.ipynb
  5. Deploy the GAN model as a web service:

    python scripts/deploy_model.py

🚀 Usage

  • Generate new product images: Access the deployed model at http://localhost:5000/generate.
  • Data preprocessing and model evaluation: Use the provided notebooks.

📜 Project Description

This project leverages the power of Generative Adversarial Networks (GANs) to augment product images for e-commerce platforms. The GAN generates high-resolution images from different angles and in various settings, enhancing product listings to attract more customers and boost sales.

Highlights:

  • 🔍 Data Preprocessing: Clean and prepare raw product images for training.
  • 🧠 Model Training: Train a GAN to generate realistic and diverse product images.
  • 📊 Model Evaluation: Assess the performance of the trained GAN.
  • 🌐 Deployment: Deploy the GAN as a web service to generate images on demand.

Enhance your e-commerce platform with stunning product images!


Feel free to reach out if you have any questions or need further assistance. Happy coding! 💻🚀

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