import gradio as gr import spaces from omni_zero import OmniZeroSingle @spaces.GPU def generate( seed=42, prompt="A person", negative_prompt="blurry, out of focus", guidance_scale=3.0, number_of_images=1, number_of_steps=10, base_image="https://github.com/okaris/omni-zero/assets/1448702/2ca63443-c7f3-4ba6-95c1-2a341414865f", base_image_strength=0.15, composition_image="https://github.com/okaris/omni-zero/assets/1448702/2ca63443-c7f3-4ba6-95c1-2a341414865f", composition_image_strength=1.0, style_image="https://github.com/okaris/omni-zero/assets/1448702/64dc150b-f683-41b1-be23-b6a52c771584", style_image_strength=1.0, identity_image="https://github.com/okaris/omni-zero/assets/1448702/ba193a3a-f90e-4461-848a-560454531c58", identity_image_strength=1.0, depth_image=None, depth_image_strength=0.5, ): omni_zero = OmniZeroSingle( base_model="frankjoshua/albedobaseXL_v13", ) images = omni_zero.generate( seed=seed, prompt=prompt, negative_prompt=negative_prompt, guidance_scale=guidance_scale, number_of_images=number_of_images, number_of_steps=number_of_steps, base_image=base_image, base_image_strength=base_image_strength, composition_image=composition_image, composition_image_strength=composition_image_strength, style_image=style_image, style_image_strength=style_image_strength, identity_image=identity_image, identity_image_strength=identity_image_strength, depth_image=depth_image, depth_image_strength=depth_image_strength, ) # for i, image in enumerate(images): # image.save(f"oz_output_{i}.jpg") return images with gr.Blocks() as demo: with gr.Row(): with gr.Column(): with gr.Row(): prompt = gr.Textbox(label="Prompt", value="A person") with gr.Row(): negative_prompt = gr.Textbox(label="Negative Prompt", value="blurry, out of focus") with gr.Row(): seed = gr.Slider(label="Seed",step=1, minimum=0, maximum=10000000, value=42) number_of_images = gr.Slider(label="Number of Outputs",step=1, minimum=1, maximum=4, value=1) with gr.Row(): guidance_scale = gr.Slider(label="Guidance Scale",step=0.1, minimum=0.0, maximum=14.0, value=3.0) number_of_steps = gr.Slider(label="Number of Steps",step=1, minimum=1, maximum=50, value=10) with gr.Row(): with gr.Column(): with gr.Row(): base_image = gr.Image(label="Base Image", value="https://github.com/okaris/omni-zero/assets/1448702/2ca63443-c7f3-4ba6-95c1-2a341414865f") with gr.Row(): base_image_strength = gr.Slider(label="Base Image Strength",step=0.01, minimum=0.0, maximum=1.0, value=0.15) with gr.Column(): with gr.Row(): composition_image = gr.Image(label="Composition", value="https://github.com/okaris/omni-zero/assets/1448702/2ca63443-c7f3-4ba6-95c1-2a341414865f") with gr.Row(): composition_image_strength = gr.Slider(label="Composition Image Strength",step=0.01, minimum=0.0, maximum=1.0, value=1.0) # with gr.Row(): with gr.Column(): with gr.Row(): style_image = gr.Image(label="Style Image", value="https://github.com/okaris/omni-zero/assets/1448702/64dc150b-f683-41b1-be23-b6a52c771584") with gr.Row(): style_image_strength = gr.Slider(label="Style Image Strength",step=0.01, minimum=0.0, maximum=1.0, value=1.0) with gr.Column(): with gr.Row(): identity_image = gr.Image(label="Identity Image", value="https://github.com/okaris/omni-zero/assets/1448702/ba193a3a-f90e-4461-848a-560454531c58") with gr.Row(): identity_image_strength = gr.Slider(label="Identitiy Image Strenght",step=0.01, minimum=0.0, maximum=1.0, value=1.0) # with gr.Column(): # with gr.Row(): # depth_image = gr.Image(label="depth_image", value=None) # with gr.Row(): # depth_image_strength = gr.Slider(label="depth_image_strength",step=0.01, minimum=0.0, maximum=1.0, value=0.5) with gr.Column(): with gr.Row(): out = gr.Image(label="Output(s)", value=None) with gr.Row(): # clear = gr.Button("Clear") submit = gr.Button("Generate") submit.click(generate, inputs=[ seed, prompt, negative_prompt, guidance_scale, number_of_images, number_of_steps, base_image, base_image_strength, composition_image, composition_image_strength, style_image, style_image_strength, identity_image, identity_image_strength, ], outputs=[out] ) # clear.click(lambda: None, None, chatbot, queue=False) demo.launch()