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Learning To Paint with RL

This problem aims at training an agent to generate paintings using stroke based sequential actions. We plan to break down the given target image into a set number of strokes, using a RL agent, which can generate a painted image. Compare On Policy (PPO) and Off Policy (DDPG) methods for solving the problem. We also aim at incorporating style transfer while painting.

Quickstart

For training and testing on MNIST

Open In Colab

For training and testing on celeb

Open In Colab

For training Style transfer RL on MNIST

Open In Colab

Style transfer

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Demo

Style Transfer on MNIST

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Using DDPG on CelebA

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Using PPO on MNIST

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Version Info

Version : 1.0.0

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