import gradio as gr import spaces from gradio_imageslider import ImageSlider from image_gen_aux import UpscaleWithModel from image_gen_aux.utils import load_image # This uses https://github.com/asomoza/image_gen_aux/blob/main/src/image_gen_aux/upscalers/README.md # Also this space has been duplicated from their official huggingface space, https://huggingface.co/spaces/OzzyGT/basic_upscaler # They did great work, and I was happy to see them to also use my models :) I thought Id duplicate it and extend it. # It basically made me get a pro account so I can make a Zero GPU space. And I will also upload more of my models as a model card now to use here. # Start out with my own models. If others like kim, sirosky, and other model trainers would like their models added here, then thats great. # I simply want them to message me first so I know that everythings okay with having their model as a selection here since they are the author of that model. If they want their model on here or not basically. # I load models from huggingface model cards though, so the model should be hosted on huggingface. MODELS = { "4xNomos2_hq_drct-l": "Phips/4xNomos2_hq_drct-l", "4xNomosWebPhoto_RealPLKSR": "Phips/4xNomosWebPhoto_RealPLKSR", "4xRealWebPhoto_v4_dat2": "Phips/4xRealWebPhoto_v4_dat2", "4xRealWebPhoto_v3_atd": "Phips/4xRealWebPhoto_v3_atd", "4xNomos8k_atd_jpg": "Phips/4xNomos8k_atd_jpg", "4xNomosUni_rgt_multijpg": "Phips/4xNomosUni_rgt_multijpg", "4xTextures_GTAV_rgt-s_dither": "Phips/4xTextures_GTAV_rgt-s_dither", "4xTextureDAT2_otf": "Phips/4xTextureDAT2_otf", "2xHFA2k_LUDVAE_compact": "Phips/2xHFA2k_LUDVAE_compact", "2xEvangelion_dat2": "Phips/2xEvangelion_dat2", "1xDeJPG_realplksr_otf": "Phips/1xDeJPG_realplksr_otf", "1xDeH264_realplksr": "Phips/1xDeH264_realplksr", "1xDeNoise_realplksr_otf": "Phips/1xDeNoise_realplksr_otf", "1xExposureCorrection_compact": "Phips/1xExposureCorrection_compact", "1xUnderExposureCorrection_compact": "Phips/1xUnderExposureCorrection_compact", "1xOverExposureCorrection_compact": "Phips/1xOverExposureCorrection_compact", } @spaces.GPU def upscale_image(image, model_selection): original = load_image(image) upscaler = UpscaleWithModel.from_pretrained(MODELS[model_selection]).to("cuda") image = upscaler(original, tiling=True, tile_width=1024, tile_height=1024) return original, image def clear_result(): return gr.update(value=None) title = """

Image Upscaler

Use this Space to upscale your images, makes use of the Image Generation Auxiliary Tools library.
For now makes use of my self trained models, but can be extended to more models from other authors if they message me.
""" with gr.Blocks() as demo: gr.HTML(title) with gr.Row(): with gr.Column(): input_image = gr.Image(type="pil", label="Input Image") model_selection = gr.Dropdown( choices=list(MODELS.keys()), value="4xNomos2_hq_drct-l", label="Model", ) run_button = gr.Button("Upscale") with gr.Column(): result = ImageSlider( interactive=False, label="Generated Image", ) run_button.click( fn=clear_result, inputs=None, outputs=result, ).then( fn=upscale_image, inputs=[input_image, model_selection], outputs=result, ) demo.launch(share=False)