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+# Color Diffusion (Evaluating Model Perception of Color Illusions in Photorealistic Scenes)
+
+Authors: Lingjun Mao, Zineng Tang, Alane Suhr
+
+---
+
+![examples](https://github.com/mao1207/RCID/blob/main/images/color-diffusion.gif?raw=true)
+
+
+## Model Overview
+
+The **Color Diffusion** model used in the paper "Evaluating Model Perception of Color Illusions in Photorealistic Scenes" is designed to generate images for RCID dataset based on a color sketch. By simply providing the model with a colored draft image, it can generate realistic images that match both the shape and color patterns of the provided sketch, according to a given text prompt. This model is built upon ControlNet and has been trained for 20 epochs on the MS COCO 2017 dataset.
+
+## RCID Dataset
+
+![RCID](https://github.com/mao1207/RCID/blob/main/images/main_figure.png?raw=true)
+
+The construction of our dataset involves three steps:
+
+1. **Image Generation.** For contrast and stripe illusions, we use procedural code to generate simple illusion images, which are then processed by our **Color Diffusion** model to create realistic illusion images. For filter illusions, we directly apply contrasting color filters to the original images. Each type of illusion also includes a corresponding control group without any illusions for comparison.
+
+2. **Question Generation.** We use GPT-4o to generate image-specific questions that are designed to evaluate the model's understanding of the illusion.
+
+3. **Human Feedback.** We collect human participants' feedback on these images and adjust the original classification of “illusion” and “non-illusion” based on whether participants are deceived.
+
+Our data can be found in the following link: [RCID Dataset](https://huggingface.co/datasets/mao1207/RCID)
+
+The code is released on [https://github.com/mao1207/RCID](https://huggingface.co/datasets/mao1207/RCID)
+
+## License
+
+The source code of this repository is released under the Apache License 2.0. The model license and dataset license are listed on their corresponding webpages.
+
+For more information, access to the dataset, and to contribute, please visit our [Website](https://color-illusion.github.io/Color-Illusion/).