mrm8488/hf-diffusers

1from diffusers import DDPMPipeline2import gradio as gr3from ui import title, description, examples4 5 6RES = None7 8models = [9    {'type': 'pokemon', 'res': 64, 'id': 'mrm8488/ddpm-ema-pokemon-64'},10    {'type': 'flowers', 'res': 64, 'id': 'mrm8488/ddpm-ema-flower-64'},11    {'type': 'anime_faces', 'res': 128, 'id': 'mrm8488/ddpm-ema-anime-v2-128'},12    {'type': 'butterflies', 'res': 128, 'id': 'mrm8488/ddpm-ema-butterflies-128'},13    #{'type': 'human_faces', 'res': 256, 'id': 'fusing/ddpm-celeba-hq'}14]15for model in models:16    print(model)17    pipeline = DDPMPipeline.from_pretrained(model['id'])18    pipeline.save_pretrained('.')19    model['pipeline'] = pipeline20 21 22def predict(type):23    pipeline = None24    for model in models:25        if model['type'] == type:26            pipeline = model['pipeline']27            RES = model['res']28            break29    # run pipeline in inference30    image = pipeline()["sample"]31 32    return image[0]33 34 35gr.Interface(36    predict,37    inputs=[gr.components.Dropdown(choices=[model['type'] for model in models], label='Choose a model')38            ],39    outputs=[gr.Image(shape=(64,64), type="pil",40                      elem_id="generated_image")],41    title=title,42    description=description43).launch()44