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| import os | |
| import gradio as gr | |
| from inference import CityAestheticsMultiModelPipeline, get_model_path | |
| TOKEN = os.environ.get("HFS_TOKEN") | |
| HFREPO = "City96/CityAesthetics" | |
| MODELS = [ | |
| "CityAesthetics-Anime-v1.8", | |
| ] | |
| article = """\ | |
| # About | |
| This is the live demo for the CityAesthetics class of predictors. | |
| For more information, you can check out the [Huggingface Hub](https://huggingface.co/city96/CityAesthetics) or [GitHub page](https://github.com/city96/CityClassifiers). | |
| ## CityAesthetics-Anime | |
| This flavor is optimized for scoring anime images with at least one subject present. | |
| ### Intentional biases: | |
| - Completely negative towards real life photos (ideal score of 0%) | |
| - Strongly Negative towards text (subtitles, memes, etc) and manga panels | |
| - Fairly negative towards 3D and to some extent 2.5D images | |
| - Negative towards western cartoons and stylized images (chibi, parody) | |
| ### Expected output scores: | |
| - Non-anime images should always score below 20% | |
| - Sketches/rough lineart/oekaki get around 20-40% | |
| - Flat shading/TV anime gets around 40-50% | |
| - Above 50% is mostly scored based on my personal style preferences | |
| ### Issues: | |
| - Tends to filter male characters. | |
| - Requires at least 1 subject, won't work for scenery/landscapes. | |
| - Noticeable positive bias towards anime characters with animal ears. | |
| - Hit-or-miss with AI generated images due to style/quality not being correlated. | |
| """ | |
| pipeline = CityAestheticsMultiModelPipeline( | |
| [get_model_path(x, HFREPO, TOKEN) for x in MODELS], | |
| ) | |
| gr.Interface( | |
| fn = pipeline, | |
| title = "CityAesthetics demo", | |
| article = article, | |
| inputs = gr.Image(label="Input image", type="pil"), | |
| outputs = gr.Label(label="Model prediction", show_label=False), | |
| examples = "./examples" if os.path.isdir("./examples") else None, | |
| allow_flagging = "never", | |
| analytics_enabled = False, | |
| ).launch() | |