sagnik1511/Conv-AE-Tensorflow-Keras
Convolutional Auto Encoder in Tensorflow >= 2.2.0
This project helps machine learning practitioners learn how to implement a convolutional autoencoder for image processing. It takes a dataset of images, specifically Pokemon images in its example, and trains a model to compress and then reconstruct them. The output includes the trained model and visualizations of its performance, showing how well it can recreate images. This tool is ideal for developers, data scientists, and machine learning engineers looking to understand or apply autoencoders for tasks like image denoising or anomaly detection.
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Use this if you are a developer or machine learning engineer who wants a practical example of implementing a convolutional autoencoder using TensorFlow and Keras, especially with image data.
Not ideal if you are a non-technical user looking for a ready-to-use application to process images without writing code.
Stars
7
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Language
Jupyter Notebook
License
MIT
Last pushed
Nov 11, 2021
Commits (30d)
0
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