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| import gradio as gr | |
| import os | |
| hf_token = os.environ.get("HF_TOKEN") | |
| import spaces | |
| import torch | |
| from pipeline_bria import BriaPipeline, BriaTransformer2DModel | |
| import time | |
| resolutions = ["1024 1024","1280 768","1344 768","768 1344","768 1280"] | |
| # Ng | |
| default_negative_prompt= "Logo,Ugly,Morbid,Extra fingers,Poorly drawn hands,Mutation,Blurry,Extra limbs,Gross proportions,Missing arms,Mutated hands,Long neck,Duplicate,Mutilated,Mutilated hands,Poorly drawn face,Deformed,Bad anatomy,Cloned face,Malformed limbs,Missing legs,Too many fingers" | |
| transformer = BriaTransformer2DModel.from_pretrained("briaai/BRIA-3.2",subfolder='transformer',torch_dtype=torch.bfloat16) | |
| pipe = BriaPipeline.from_pretrained("briaai/BRIA-3.1", transformer=transformer, torch_dtype=torch.bfloat16,trust_remote_code=True) | |
| pipe.to(device="cuda") | |
| def infer(prompt,negative_prompt,seed,resolution): | |
| print(f""" | |
| —/n | |
| {prompt} | |
| """) | |
| # generator = torch.Generator("cuda").manual_seed(555) | |
| t=time.time() | |
| if seed=="-1": | |
| generator=None | |
| else: | |
| try: | |
| seed=int(seed) | |
| generator = torch.Generator("cuda").manual_seed(seed) | |
| except: | |
| generator=None | |
| w,h = resolution.split() | |
| w,h = int(w),int(h) | |
| image = pipe(prompt,num_inference_steps=30, negative_prompt=negative_prompt,generator=generator,width=w,height=h).images[0] | |
| print(f'gen time is {time.time()-t} secs') | |
| # Future | |
| # Add amound of steps | |
| # if nsfw: | |
| # raise gr.Error("Generated image is NSFW") | |
| return image | |
| css = """ | |
| #col-container{ | |
| margin: 0 auto; | |
| max-width: 580px; | |
| } | |
| """ | |
| with gr.Blocks(css=css) as demo: | |
| with gr.Column(elem_id="col-container"): | |
| gr.Markdown("## BRIA 3.2") | |
| gr.HTML(''' | |
| <p style="margin-bottom: 10px; font-size: 94%"> | |
| This is a demo for | |
| <a href="https://huggingface.co/briaai/BRIA-3.2" target="_blank">BRIA 3.2 text-to-image </a>. | |
| is our new text-to-image model that achieves high-quality generation while being trained exclusively on fully licensed data. We offer both API access and direct access to the model weights, making integration seamless for developers. </p> | |
| ''') | |
| with gr.Group(): | |
| with gr.Column(): | |
| prompt_in = gr.Textbox(label="Prompt", value="""photo of mystical dragon eating sushi, text bubble says "Sushi Time".""") | |
| resolution = gr.Dropdown(value=resolutions[0], show_label=True, label="Resolution", choices=resolutions) | |
| seed = gr.Textbox(label="Seed", value=-1) | |
| negative_prompt = gr.Textbox(label="Negative Prompt", value=default_negative_prompt) | |
| submit_btn = gr.Button("Generate") | |
| result = gr.Image(label="BRIA-3.2 Result") | |
| # gr.Examples( | |
| # examples = [ | |
| # "Dragon, digital art, by Greg Rutkowski", | |
| # "Armored knight holding sword", | |
| # "A flat roof villa near a river with black walls and huge windows", | |
| # "A calm and peaceful office", | |
| # "Pirate guinea pig" | |
| # ], | |
| # fn = infer, | |
| # inputs = [ | |
| # prompt_in | |
| # ], | |
| # outputs = [ | |
| # result | |
| # ] | |
| # ) | |
| submit_btn.click( | |
| fn = infer, | |
| inputs = [ | |
| prompt_in, | |
| negative_prompt, | |
| seed, | |
| resolution | |
| ], | |
| outputs = [ | |
| result | |
| ] | |
| ) | |
| demo.queue().launch(show_api=False) |