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README.md
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![images_4)](./000006_scribble_concat.webp)
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### Examples Anime(Note that you need to change the base model to CounterfeitXL, others remains the same)
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![images_50)](./000081.webp)
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## How to Get Started with the Model
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## Training Details
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![images_4)](./000006_scribble_concat.webp)
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### Examples Anime(Note that you need to change the base model to CounterfeitXL, others remains the same)
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![images_5)](./000013_scribble_concat.webp)
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![images_6)](./000034_scribble_concat.webp)
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![images_8)](./000078_scribble_concat.webp)
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![images_9)](./000097_scribble_concat.webp)
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## How to Get Started with the Model
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```
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## Evaluation Metric
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1 Laion Aesthetic Score [https://laion.ai/blog/laion-aesthetics/]
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2 PerceptualSimilarity [https://github.com/richzhang/PerceptualSimilarity]
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## Evaluation Data
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The test data is randomly sample from midjourney upscale images with prompts, as the purpose of the project is to letting people draw images like midjourney. midjourney’s users include a large number of professional designers,
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and the upscale image tend to have more beauty score and prompt consistency, it is suitable to use it as the test set to judge the ability of controlnet. We select 300 prompt-image pairs randomly and generate 4 images per prompt,
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totally 1200 images generated. We caculate the Laion Aesthetic Score to measure the beauty and the PerceptualSimilarity to measure the control ability, we find the quality of images have a good consistency with the meric values.
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We compare our methods with other SOTA huggingface models and list the result below. We are the models that have highest aesthectic score, and can generate visually appealing images if you prompt it properly.
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## Training Details
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