ecommerce-gan-augmentation/
βββ π data/
β βββ π raw/
β βββ π processed/
β βββ π augmented/
βββ π models/
β βββ π generator/
β βββ π discriminator/
β βββ π trained_model/
βββ π notebooks/
β βββ π data_preprocessing.ipynb
β βββ π model_training.ipynb
β βββ π model_evaluation.ipynb
βββ π scripts/
β βββ π train_gan.py
β βββ π evaluate_gan.py
β βββ π deploy_model.py
βββ π README.md
βββ π requirements.txt
βββ ποΈ .gitignore
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Install the required packages:
pip install -r requirements.txt
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Preprocess the dataset:
jupyter notebook notebooks/data_preprocessing.ipynb
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Train the GAN model:
python scripts/train_gan.py
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Evaluate the GAN model:
jupyter notebook notebooks/model_evaluation.ipynb
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Deploy the GAN model as a web service:
python scripts/deploy_model.py
- Generate new product images: Access the deployed model at
http://localhost:5000/generate
. - Data preprocessing and model evaluation: Use the provided notebooks.
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.
- π Data Preprocessing: Clean and prepare raw product images for training.
- π§ Model Training: Train a GAN to generate realistic and diverse product images.
- π Model Evaluation: Assess the performance of the trained GAN.
- π Deployment: Deploy the GAN as a web service to generate images on demand.
β¨ Enhance your e-commerce platform with stunning product images! β¨
Feel free to reach out if you have any questions or need further assistance. Happy coding! π»π