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import gradio as gr
from diffusers import StableDiffusionXLPipeline, EDMEulerScheduler
from custom_pipeline import CosStableDiffusionXLInstructPix2PixPipeline
import spaces
edit_file = hf_hub_download(repo_id="stabilityai/cosxl", filename="cosxl_edit.safetensors")
normal_file = hf_hub_download(repo_id="stabilityai/cosxl", filename="cosxl.safetensors")
def set_timesteps_patched(self, num_inference_steps: int, device = None):
self.num_inference_steps = num_inference_steps
ramp = np.linspace(0, 1, self.num_inference_steps)
sigmas = torch.linspace(math.log(self.config.sigma_min), math.log(self.config.sigma_max), len(ramp)).exp().flip(0)
sigmas = (sigmas).to(dtype=torch.float32, device=device)
self.timesteps = self.precondition_noise(sigmas)
self.sigmas = torch.cat([sigmas, torch.zeros(1, device=sigmas.device)])
self._step_index = None
self._begin_index = None
self.sigmas = self.sigmas.to("cpu") # to avoid too much CPU/GPU communication
EDMEulerScheduler.set_timesteps = set_timesteps_patched
pipe_edit = CosStableDiffusionXLInstructPix2PixPipeline.from_single_file(
edit_file, num_in_channels=8
)
pipe_edit.scheduler = EDMEulerScheduler(sigma_min=0.002, sigma_max=120.0, sigma_data=1.0, prediction_type="v_prediction")
pipe_edit.to("cuda")
pipe_normal = StableDiffusionXLPipeline.from_single_file(normal_file, torch_dtype=torch.float16)
pipe_normal.scheduler = EDMEulerScheduler(sigma_min=0.002, sigma_max=120.0, sigma_data=1.0, prediction_type="v_prediction")
pipe_normal.to("cuda")
@spaces.GPU
def run_normal(prompt):
return pipe_normal(prompt, num_inference_steps=20).images[0]
@spaces.GPU
def run_edit(image, prompt):
resolution = 1024
image.resize((resolution, resolution))
return pipe_edit(prompt=prompt,image=image,height=resolution,width=resolution,num_inference_steps=20).images[0]
with gr.Blocks() as demo:
gr.Markdown('''# CosXL demo
Unofficial demo for CosXL, a SDXL model tuned to produce full color range images. CosXL Edit allows you to perform edits on images. Both have a [non-commercial community license](https://huggingface.co/stabilityai/cosxl/blob/main/LICENSE)
''')
with gr.Tab("CosXL"):
with gr.Group():
with gr.Row():
prompt_normal = gr.Textbox(show_label=False, scale=4, placeholder="Your prompt, e.g.: backlit photography of a dog")
button_normal = gr.Button("Generate", min_width=120)
output_normal = gr.Image(label="Your result image", interactive=False)
with gr.Accordion("Advanced Settings", open=False):
pass
with gr.Tab("CosXL Edit"):
with gr.Group():
image_edit = gr.Image(label="Image you would like to edit", type="pil")
with gr.Row():
prompt_edit = gr.Textbox(show_label=False, scale=4, placeholder="Edit instructions, e.g.: Make the day cloudy")
button_edit = gr.Button("Generate", min_width=120)
output_edit = gr.Image(label="Your result image", interactive=False)
with gr.Accordion("Advanced Settings", open=False):
pass
button_normal.click(
fn=run_normal,
inputs=[prompt_normal],
outputs=[output_normal]
)
button_edit.click(
fn=run_edit,
inputs=[image_edit, prompt_edit],
outputs=[output_edit]
)
if __name__ == "__main__":
demo.launch(share=True)
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