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| import gradio as gr | |
| from diffusers import AutoPipelineForText2Image | |
| import numpy as np | |
| import math | |
| import spaces | |
| import torch | |
| import random | |
| theme = gr.themes.Base( | |
| font=[gr.themes.GoogleFont('Libre Franklin'), gr.themes.GoogleFont('Public Sans'), 'system-ui', 'sans-serif'], | |
| ) | |
| device="cuda" | |
| pipe_xlc = AutoPipelineForText2Image.from_pretrained( | |
| "temp-org-cc/CommonCanvas-XLC", | |
| custom_pipeline="multimodalart/sdxl_perturbed_attention_guidance", | |
| torch_dtype=torch.float16 | |
| ).to(device) | |
| pipe_xlnc = AutoPipelineForText2Image.from_pretrained( | |
| "temp-org-cc/CommonCanvas-XLNC", | |
| custom_pipeline="multimodalart/sdxl_perturbed_attention_guidance", | |
| torch_dtype=torch.float16 | |
| ).to(device) | |
| pipe_sc = AutoPipelineForText2Image.from_pretrained( | |
| "temp-org-cc/CommonCanvas-SC", | |
| custom_pipeline="hyoungwoncho/sd_perturbed_attention_guidance", | |
| torch_dtype=torch.float16 | |
| ).to(device) | |
| pipe_snc = AutoPipelineForText2Image.from_pretrained( | |
| "temp-org-cc/CommonCanvas-SNC", | |
| custom_pipeline="hyoungwoncho/sd_perturbed_attention_guidance", | |
| torch_dtype=torch.float16 | |
| ).to(device) | |
| def run_xlc(prompt, negative_prompt=None, guidance_scale=7.0, pag_scale=3.0, pag_layers=["mid"], randomize_seed=True, seed=42, progress=gr.Progress(track_tqdm=True)): | |
| if(randomize_seed): | |
| seed = random.randint(0, 9007199254740991) | |
| generator = torch.Generator(device="cuda").manual_seed(seed) | |
| image = pipe_xlc(prompt, negative_prompt=negative_prompt, guidance_scale=guidance_scale, pag_scale=pag_scale, pag_applied_layers=pag_layers, generator=generator, num_inference_steps=25, width=512, height=512).images[0] | |
| return image, seed | |
| def run_xlnc(prompt, negative_prompt=None, guidance_scale=7.0, pag_scale=3.0, pag_layers=["mid"], randomize_seed=True, seed=42, progress=gr.Progress(track_tqdm=True)): | |
| if(randomize_seed): | |
| seed = random.randint(0, 9007199254740991) | |
| generator = torch.Generator(device="cuda").manual_seed(seed) | |
| image = pipe_xlnc(prompt, negative_prompt=negative_prompt, guidance_scale=guidance_scale, pag_scale=pag_scale, pag_applied_layers=pag_layers, generator=generator, num_inference_steps=25, width=512, height=512).images[0] | |
| return image, seed | |
| def run_sc(prompt, negative_prompt=None, guidance_scale=7.0, pag_scale=3.0, pag_layers=["mid"], randomize_seed=True, seed=42, progress=gr.Progress(track_tqdm=True)): | |
| if(randomize_seed): | |
| seed = random.randint(0, 9007199254740991) | |
| generator = torch.Generator(device="cuda").manual_seed(seed) | |
| image = pipe_sc(prompt, negative_prompt=negative_prompt, guidance_scale=guidance_scale, pag_scale=pag_scale, pag_applied_layers=pag_layers, generator=generator, num_inference_steps=25).images[0] | |
| return image, seed | |
| def run_snc(prompt, negative_prompt=None, guidance_scale=7.0, pag_scale=3.0, pag_layers=["mid"], randomize_seed=True, seed=42, progress=gr.Progress(track_tqdm=True)): | |
| if(randomize_seed): | |
| seed = random.randint(0, 9007199254740991) | |
| generator = torch.Generator(device="cuda").manual_seed(seed) | |
| image = pipe_sc(prompt, negative_prompt=negative_prompt, guidance_scale=guidance_scale, pag_scale=pag_scale, pag_applied_layers=pag_layers, generator=generator, num_inference_steps=25).images[0] | |
| return image, seed | |
| css = ''' | |
| .gradio-container{ | |
| max-width: 768px !important; | |
| margin: 0 auto; | |
| } | |
| ''' | |
| with gr.Blocks(css=css, theme=theme) as demo: | |
| gr.Markdown('''# CommonCanvas | |
| Demo for the [CommonCanvas suite of models](https://huggingface.co/collections/temp-org-cc/commoncanvas-66226ef9688b3580a5954653) trained on the [CommonCatalogue](https://huggingface.co/collections/temp-org-cc/commoncatalogue-6530907589ffafffe87c31c5), a dataset with ~70M images dedicated to the Creative Commons. | |
| ''') | |
| with gr.Group(): | |
| with gr.Tab("CommonCanvas XLC"): | |
| with gr.Row(): | |
| prompt_xlc = gr.Textbox(show_label=False, scale=4, placeholder="Your prompt") | |
| button_xlc = gr.Button("Generate", min_width=120) | |
| with gr.Tab("CommonCanvas XLNC"): | |
| with gr.Row(): | |
| prompt_xlnc = gr.Textbox(show_label=False, scale=4, placeholder="Your prompt") | |
| button_xlnc = gr.Button("Generate", min_width=120) | |
| with gr.Tab("CommonCanvas SC"): | |
| with gr.Row(): | |
| prompt_sc = gr.Textbox(show_label=False, scale=4, placeholder="Your prompt") | |
| button_sc = gr.Button("Generate", min_width=120) | |
| with gr.Tab("CommonCanvas SNC"): | |
| with gr.Row(): | |
| prompt_snc = gr.Textbox(show_label=False, scale=4, placeholder="Your prompt") | |
| button_snc = gr.Button("Generate", min_width=120) | |
| output = gr.Image(label="Your result", interactive=False) | |
| with gr.Accordion("Advanced Settings", open=False): | |
| guidance_scale = gr.Number(label="CFG Guidance Scale", info="The guidance scale for CFG, ignored if no prompt is entered (unconditional generation)", value=7.0) | |
| negative_prompt = gr.Textbox(label="Negative prompt", info="Is only applied for the CFG part, leave blank for unconditional generation") | |
| pag_scale = gr.Number(label="Pag Scale", value=3.0) | |
| pag_layers = gr.Dropdown(label="Model layers to apply Pag to", info="mid is the one used on the paper, up and down blocks seem unstable", choices=["up", "mid", "down"], multiselect=True, value="mid") | |
| randomize_seed = gr.Checkbox(label="Randomize seed", value=True) | |
| seed = gr.Slider(minimum=1, maximum=9007199254740991, step=1, randomize=True) | |
| with gr.Accordion("Use it with diffusers, ComfyUI, AUTOMATIC111", open=False): | |
| gr.Markdown('''The CommonCanvas S and CommonCanvas XL collections are drop-in replacements of Stable Diffusion 2 and Stable Diffusion XL respectively and can be used as such with `diffusers` or in UIs such as ComfyUI, AUTOMATIC1111, SDNext, InvokeAI, etc. | |
| ## Using it with diffusers | |
| ```py | |
| from diffusers import AutoPipelineForText2Image | |
| pipe = AutoPipelineForText2Image.from_pretrained( | |
| "temp-org-cc/CommonCanvas-XLC", #here you can pick between | |
| custom_pipeline="multimodalart/sdxl_perturbed_attention_guidance", | |
| torch_dtype=torch.float16 | |
| ).to(device) | |
| prompt = "a cat" | |
| image = pipe_xlc(prompt, num_inference_steps=25).images[0] | |
| ``` | |
| ## Using it ComfyUI/Automatic1111 | |
| - [CommonCanvasSC.safetensors](#) (SD2 drop-in, commercial) | |
| - [CommonCanvasSNC.safetensors](#) (SD2 drop-in, non-commercial - trained on more data) | |
| - [CommonCanvasXLC.safetensors](#) (SDXL drop-in, commercial) | |
| - [CommonCanvasXLNC.safetensors](#) (SDXL drop-in, non-commercial - trained on more data) | |
| ''') | |
| #gr.Examples(fn=run, examples=[" ", "an insect robot preparing a delicious meal, anime style", "a photo of a group of friends at an amusement park"], inputs=prompt, outputs=[output, seed], cache_examples=True) | |
| gr.on( | |
| triggers=[ | |
| button_xlc.click, | |
| prompt_xlc.submit | |
| ], | |
| fn=run_xlc, | |
| inputs=[prompt_xlc, negative_prompt, guidance_scale, pag_scale, pag_layers, randomize_seed, seed], | |
| outputs=[output, seed], | |
| ) | |
| gr.on( | |
| triggers=[ | |
| button_xlnc.click, | |
| prompt_xlnc.submit | |
| ], | |
| fn=run_xlnc, | |
| inputs=[prompt_xlnc, negative_prompt, guidance_scale, pag_scale, pag_layers, randomize_seed, seed], | |
| outputs=[output, seed], | |
| ) | |
| gr.on( | |
| triggers=[ | |
| button_sc.click, | |
| prompt_sc.submit | |
| ], | |
| fn=run_sc, | |
| inputs=[prompt_sc, negative_prompt, guidance_scale, pag_scale, pag_layers, randomize_seed, seed], | |
| outputs=[output, seed], | |
| ) | |
| gr.on( | |
| triggers=[ | |
| button_snc.click, | |
| prompt_snc.submit | |
| ], | |
| fn=run_sc, | |
| inputs=[prompt_snc, negative_prompt, guidance_scale, pag_scale, pag_layers, randomize_seed, seed], | |
| outputs=[output, seed], | |
| ) | |
| if __name__ == "__main__": | |
| demo.launch(share=True) |