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Running
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Zero
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import gradio as gr
import numpy as np
import spaces
import torch
import random
import os
from diffusers import QwenImageEditInpaintPipeline
from PIL import Image
# Set environment variable for parallel loading
os.environ["HF_ENABLE_PARALLEL_LOADING"] = "YES"
MAX_SEED = np.iinfo(np.int32).max
MAX_IMAGE_SIZE = 2048
# Initialize Qwen Image Edit pipeline
pipe = QwenImageEditInpaintPipeline.from_pretrained("Qwen/Qwen-Image-Edit", torch_dtype=torch.bfloat16).to("cuda")
@spaces.GPU
def infer(edit_images, prompt, negative_prompt="", seed=42, randomize_seed=False, strength=1.0, num_inference_steps=35, true_cfg_scale=4.0, progress=gr.Progress(track_tqdm=True)):
image = edit_images["background"]
mask = edit_images["layers"][0]
if randomize_seed:
seed = random.randint(0, MAX_SEED)
# Generate image using Qwen pipeline
result_image = pipe(
prompt=prompt,
negative_prompt=negative_prompt,
image=image,
mask_image=mask,
strength=strength,
num_inference_steps=num_inference_steps,
true_cfg_scale=true_cfg_scale,
generator=torch.Generator(device="cuda").manual_seed(seed)
).images[0]
return result_image, seed
examples = [
"change the hat to red",
"make the background a beautiful sunset",
"replace the object with a flower vase",
]
css="""
#col-container {
margin: 0 auto;
max-width: 1000px;
}
"""
with gr.Blocks(css=css) as demo:
with gr.Column(elem_id="col-container"):
gr.Markdown(f"""# Qwen Image Edit Inpainting
Advanced image inpainting using Qwen's Image Edit model
[[model](https://huggingface.co/Qwen/Qwen-Image-Edit)] [[paper](https://arxiv.org/abs/2412.20710)]
""")
with gr.Row():
with gr.Column():
edit_image = gr.ImageEditor(
label='Upload and draw mask for inpainting',
type='pil',
sources=["upload", "webcam"],
image_mode='RGB',
layers=False,
brush=gr.Brush(colors=["#FFFFFF"], color_mode="fixed"),
height=600
)
prompt = gr.Text(
label="Prompt",
show_label=False,
max_lines=1,
placeholder="Enter your prompt (e.g., 'change the hat to red')",
container=False,
)
negative_prompt = gr.Text(
label="Negative Prompt",
show_label=True,
max_lines=1,
placeholder="Enter what you don't want (optional)",
container=False,
value=""
)
run_button = gr.Button("Run")
result = gr.Image(label="Result", show_label=False)
with gr.Accordion("Advanced Settings", open=False):
seed = gr.Slider(
label="Seed",
minimum=0,
maximum=MAX_SEED,
step=1,
value=42,
)
randomize_seed = gr.Checkbox(label="Randomize seed", value=True)
with gr.Row():
strength = gr.Slider(
label="Strength",
minimum=0.0,
maximum=2.0,
step=0.1,
value=1.0,
info="Controls how much the inpainted region should change"
)
true_cfg_scale = gr.Slider(
label="True CFG Scale",
minimum=1.0,
maximum=20.0,
step=0.5,
value=4.0,
info="Classifier-free guidance scale"
)
num_inference_steps = gr.Slider(
label="Number of inference steps",
minimum=10,
maximum=100,
step=1,
value=35,
)
gr.on(
triggers=[run_button.click, prompt.submit],
fn = infer,
inputs = [edit_image, prompt, negative_prompt, seed, randomize_seed, strength, num_inference_steps, true_cfg_scale],
outputs = [result, seed]
)
demo.launch() |