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import gradio as gr | |
import torch | |
from PIL import Image, ImageDraw, ImageFont | |
from src.condition import Condition | |
from diffusers.pipelines import FluxPipeline | |
import numpy as np | |
from src.generate import seed_everything, generate | |
pipe = None | |
def init_pipeline(): | |
global pipe | |
pipe = FluxPipeline.from_pretrained( | |
"black-forest-labs/FLUX.1-schnell", torch_dtype=torch.bfloat16 | |
) | |
#pipe = pipe.to("cuda") | |
pipe.load_lora_weights( | |
"Yuanshi/OminiControl", | |
weight_name=f"omini/subject_512.safetensors", | |
adapter_name="subject", | |
) | |
pipe.enable_model_cpu_offload() | |
def process_image_and_text(image, text): | |
# center crop image | |
w, h, min_size = image.size[0], image.size[1], min(image.size) | |
image = image.crop( | |
( | |
(w - min_size) // 2, | |
(h - min_size) // 2, | |
(w + min_size) // 2, | |
(h + min_size) // 2, | |
) | |
) | |
image = image.resize((512, 512)) | |
condition = Condition("subject", image) | |
if pipe is None: | |
init_pipeline() | |
result_img = generate( | |
pipe, | |
prompt=text.strip(), | |
conditions=[condition], | |
num_inference_steps=8, | |
height=512, | |
width=512, | |
).images[0] | |
return result_img | |
def get_samples(): | |
sample_list = [ | |
{ | |
"image": "assets/oranges.jpg", | |
"text": "A very close up view of this item. It is placed on a wooden table. The background is a dark room, the TV is on, and the screen is showing a cooking show. With text on the screen that reads 'Omini Control!'", | |
}, | |
{ | |
"image": "assets/penguin.jpg", | |
"text": "On Christmas evening, on a crowded sidewalk, this item sits on the road, covered in snow and wearing a Christmas hat, holding a sign that reads 'Omini Control!'", | |
}, | |
{ | |
"image": "assets/rc_car.jpg", | |
"text": "A film style shot. On the moon, this item drives across the moon surface. The background is that Earth looms large in the foreground.", | |
}, | |
{ | |
"image": "assets/clock.jpg", | |
"text": "In a Bauhaus style room, this item is placed on a shiny glass table, with a vase of flowers next to it. In the afternoon sun, the shadows of the blinds are cast on the wall.", | |
}, | |
] | |
return [[Image.open(sample["image"]), sample["text"]] for sample in sample_list] | |
demo = gr.Interface( | |
fn=process_image_and_text, | |
inputs=[ | |
gr.Image(type="pil"), | |
gr.Textbox(lines=2), | |
], | |
outputs=gr.Image(type="pil"), | |
title="OminiControl / Subject driven generation", | |
examples=get_samples(), | |
) | |
if __name__ == "__main__": | |
init_pipeline() | |
demo.launch( | |
debug=True, share = True | |
) | |