affinelayer/pix2pix-tensorflow
Pix2pix Tensorflow
This project is a TensorFlow implementation of an image-to-image translation framework based on conditional generative adversarial networks. It provides the tools to train models that map input images to output images based on learned visual patterns, as well as a server for processing image translation requests and serving trained model checkpoints to web clients.
The framework includes a system for converting trained model weights into a portable format for browser-based inference. It also features a validation process that generates comparative reports by analyzing input, output, and target image sets using a trained checkpoint.
The codebase covers the full pipeline from data engineering, including image dataset preparation and pair-based pipelining, to conditional adversarial training. It supports specific visual transformations such as grayscale image colorization and synthetic imagery generation.
Features
- Image-to-Image Translation - Implements a framework for mapping images from one visual domain to another using conditional GANs.
- Image-to-Image Synthesis Frameworks - Implements a TensorFlow-based framework for transforming images from one domain to another.
- Image Translation Training - Provides a system for training conditional adversarial networks to map visual patterns across domains.
- Adversarial Training Procedures - Uses conditional adversarial training to generate synthetic imagery based on specific input constraints.
- Generative Adversarial Networks - Implements a conditional generative adversarial network to map input images to output images.
- Paired Image Dataset Preparation - Provides a pipeline to process image sets into synchronized input and target pairs for training.
- Inference Services - Provides a server for processing image translation requests and serving model checkpoints to web clients.
- Translation Validation - Generates reports comparing input, output, and target image sets by processing validation images.
- Model Inference Servers - Ships a server implementation to process image translation requests and serve model checkpoints.
- Model Checkpoint Converters - Provides utilities to convert trained model weights into portable formats for browser-based inference.
- Model Performance Evaluators - Includes tools to measure model accuracy by comparing input, output, and target images.
- TensorFlow Model Inference - Runs trained TensorFlow models on a server to process image translation requests for web applications.
- Visual Comparison Reports - Generates comparative reports analyzing input, output, and target image sets using trained checkpoints.
- General Image Colorization - Supports transforming grayscale images into full color by using lightness values as input.
- Web-Compatible Format Converters - Converts TensorFlow weights into a portable JSON format for browser-based inference.
- Graphical Models and RNNs - Pix2pix implementation in TensorFlow.
- Model Architectures - TensorFlow implementation of conditional adversarial networks.
Star history
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